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In this paper, an image cipher is presented based on DNA sequence operations, image filtering and memrisitve chaotic system. Firstly, plain image is preprocessed by a self-updating transformation based on dynamic image filtering (STDIF), which may solve the problem that conventional filtering is invalid for special image such as all-zeros. Subsequently, the resulting image is converted into the DNA sequences by the dynamic DNA encoding rules, and the rules are produced by plain image information and chaotic system. Next, the DNA matrix is permutated by a double random 3D matrix scrambling (DR3DMS), thus every element may arbitrarily move to other position. Thereafter, the permutated matrix is diffused by a plane diffusion of 3D DNA matrix controlled by plain image information (PD3DPI) to resist statistical attacks. Finally, the obtained DNA matrix is transformed into cipher image via DNA decoding rules. Additionally, SHA 256 hash function value of plain image is applied to choose keystreams from the obtained chaotic sequences, which not only solves the problem of repeatedly generating chaotic sequences when encrypting different images, but also results into higher difficulty for hackers to decipher the method by use of plaintext attack. Experimental results and security analyses demonstrate its security and effectiveness.

With rapid evaluation of technologies, huge amount of critical information can exchange over unsecure network every day, secure and fast encryption schemes become more and more urgent need to provide the desirable confidentiality and thwart unauthorized access, lately and for many reasons, chaotic based encryption algorithms become more and more popular technique due to exceptionally superior characteristics such as simplicity, resistance attacks and high speed, in this paper the advantages of two nonlinear hyper-chaotic systems will utilized to strength the proposed encryption algorithm, the random sequences generated from systems will used to position scramble and value change of the plaintext, the main features of such method are efficiency, large key space, low computational overhead, and simple design as well as the experimental results demonstrate that the proposed method have more ability to thwart attacks.

The Rao-Nam cryptosystem is a symmetric version of the McEliece code-based cryptosystem proposed to get rid of the shortcomings inherent in the first symmetric code-based encryption schemes. Almost immediately after the publication of this cryptosystem, attacks on it based on selected plaintexts appeared, which led to the emergence of various improvements and modifications of the original cryptosystem. The secret key in the traditional Rao-Nam scheme is a certain Boolean matrix and a set of binary vectors used to generate distortions during encryption. Such vectors must have different syndromes, that is, be different modulo of the code generated by the rows of the specified matrix. The original work of Rao and Nam considered two methods of forming the set of these vectors, the first of which consists in using predetermined vectors of sufficiently large weight, and the second is random selection of these vectors according to the equiprobable scheme. It is known that the first option does not provide the proper security of the Rao – Nam cryptosystem (due to the small number and simple structure of these vectors), but the second option is more meaningful and requires additional research. The purpose of this paper is to obtain estimates of the effectiveness (time complexity for a given upper bound of the error probability) of attacks on a cryptosystem, which generalizes the traditional Rao – Nam scheme to the case of a finite Abelian group (note that the need to study such versions of the Rao – Nam cryptosystem is due to their consideration in recent publications). Two attacks, based on selected plaintext, are presented. The first of them is not mentioned in the works known to the authors of this article and, under certain well-defined conditions, it allows recovering the secret key of the cryptosystem with quadratic complexity. The second attack is a generalized and simplified version of the well-known Struik-van Tilburg attack. It is shown that the complexity of this attack depends on the power of the stabilizer of the set of vectors, which forms the second part of the key, in the translation group of the Abelian group, over which the Rao – Nam cryptosystem is considered. In this paper, a bound is obtained for the probability of triviality of the stabilizer under the condition of random choice of this set. From the obtained bound, it follows that Struik-van Tilburg attack is, on average, noticeably more efficient than the worst case considered earlier.

Perceptual encryption has received widespread attention as a technology for protecting multimedia visual information. In multimedia applications, perceptual encryption only protects a portion of the content without previewing all the information. At present, perceptual encryption is mostly oriented to conventional plain images while few methods aim at visual security measures for perceptually encrypted images. Existing solutions usually adopt well-known quality assessment metrics to measure the visual quality of encrypted images. However, they often exhibit undesired behavior on perceptually encrypted images with low quality. As a typical representation of three-dimensional scenes, light field images record the intensity and direction of light during propagation which is distinct from 2-D images. In this paper, we construct a perceptually encrypted light field image database (PE-LFID) for quality assessment based on 14 reference light field plaintext images. For each scene, we employ four encryption methods, each of which has six levels. Additionally, a novel visual security evaluation method based on PE-LFID is proposed by taking into account the local and global features of the light field images. First, we use a multi-threshold edge detection method to obtain the edge similarity in the spatial domain of the light field image. Afterwards, the epipolar plane image (EPI) generated from the angular domain of the light field image is used to calculate the gradient magnitude similarity, which is expressed as a global feature. Furthermore, the final quality prediction score is calculated by adaptively weighting between local and global features. We conduct extensive experiments on the proposed PE-LFID to assess the performance of classical and state-of-the-art IQA models. The experimental results demonstrate the effectiveness of the proposed method for visual security evaluation of perceptually encrypted light field images, as well as the scalability of PE-LFID.

This paper presents a generalization of chaotic systems using two-dimensional affine transformations with six introduced parameters to achieve scaling, reflection, rotation, translation and/or shearing. Hence, the location of the strange attractor in space can be controlled without changing its chaotic dynamics. In addition, the embedded parameters enhance the randomness and sensitivity of the system and control its response. This approach overpasses performing the transformations as post-processing stages by applying them on the resulting time series. Trajectory control through dynamic parameters is demonstrated. Simulation results validate the proposed analysis for both the simplest and Lorenz chaotic systems. An image encryption scheme is implemented using transformed Lorenz system resulting in a more secure encryption scheme in comparison to Lorenz and other recent related works. The scheme exhibits good performance when assessed using the PRNG properties, encrypted image histogram and its uniformity through chi square test, pixel correlation, Mean Squared Error (MSE), entropy, Peak Signal-to-Noise Ratio (PSNR), the National Institute of Standards & Technology (NIST) test, key space, key sensitivity, resistance to differential, ciphertext-only, known plaintext, and chosen plaintext attacks, robustness against noise and computation time.

Recently many substitution box based encryption algorithms ensuring privacy have been proposed. Many, chaotic map based S-boxes have been generated posing high nonlinearity and strong cryptographic properties. Encryption schemes depending on the substitution box (S-box) only are weak and easily breakable with the help of chosen plaintext and ciphertext attacks. In this work, we have completely cryptanalyzed S-box based encryption scheme successfully by two types of attacks. Cryptanalysis in both types of attacks is performed by only one selected image. Moreover, we have suggested some improvements in the algorithm to defeat attacks.

In-network storage is recognized as a vital component of many emerging network architectures, which facilitates high-quality and efficient content-centric services. In this trend, providing content-based near-duplicate detection (NDD) services among in-network storage becomes naturally necessary for network traffic alleviation and resource optimization. However, due to the increasing attacking surfaces, storing data in the networked environment inevitably raises new concerns about user privacy exposure and unauthorized data access. Therefore, we aim to design a secure NDD service in the context of encrypted in-network storage. For efficiency, we first leverage the fingerprint techniques and locality-sensitive hashing to convert the problem of NDD into the keyword search. We then adopt an efficient multi-key searchable encryption scheme, which requires only one encrypted query from the user even the data are from multiple content providers encrypted with different keys. As simply combining the above methods does not appear to directly locate accurate results, we then devise a secure result refining scheme via Yao’s garbled circuits to avoid user-side post-processing. Furthermore, we enhance our design to address the potential malicious behavior of in-network servers. Extensive evaluations of real-world image dataset demonstrate that our design can achieve comparable accuracy to the plaintext with modest security overhead.

Vehicles gather data collected by sensor nodes, combined with messages obtained from the other nodes in vehicular ad hoc networks (VANETs), to achieve safe driving. An announcement type of message is sent in the VANET; it is collected by mobile vehicles, uploaded to a cloud server for storage, and provided to other vehicles for reference. However, in an open cloud environment, plaintext data are vulnerable to unauthorized access and even malicious tampering. To solve this issue, we propose an attribute-based encryption algorithm using blockchain, which is maintained by a roadside unit (RSU). The uploader’s symmetric key is recorded on the blockchain, and all uploaded and accessed transactions are recorded for auditing. Our scheme can achieve the function of securely accessing different types of announcement messages according to different vehicle attributes. Security analysis and experimental results indicate that our scheme has achieved a balance between security and efficiency.

This paper proposes a lossless data hiding scheme in learning with errors (LWE)-encrypted domain based on key-switching technique. Lossless data hiding and extraction could be realized by a third party without knowing the private key for decryption. Key-switching-based least-significant-bit (KSLSB) data hiding method has been designed during the lossless data hiding process. The owner of the plaintext first encrypts the plaintext by using LWE encryption and uploads ciphertext to a (trusted or untrusted) third server. Then the server performs KSLSB to obtain a marked ciphertext. To enable the third party to manage ciphertext flexibly and keep the plaintext secret, the embedded data can be extracted from the marked ciphertext without using the private key of LWE encryption in the proposed scheme. Experimental results demonstrate that data hiding would not compromise the security of LWE encryption, and the embedding rate is 1 bit per bit of plaintext without introducing any loss into the directly decrypted result.

Attribute-based encryption (ABE) provides a fine-grained access control mode for multiuser network environments. The popularity of 5th generation (5G) mobile network applications has greatly increased the data transmission rate, but mobile terminal devices with limited resources in the network have difficulty with the high computational overhead of ABE in wireless communication. In response to this problem, this paper proposes a hybrid encryption online/offline ciphertext policy attribute-based encryption (CP-ABE) scheme for 5G. In the scheme, the data owner uses symmetric encryption technology to perform data encapsulation on plaintext and outsources the encapsulated plaintext to the cloud user assistant (CUA) for offline calculation. Key encapsulation is performed on a symmetric key to form the final ciphertext, and it is uploaded to the cloud server. After the data user obtains the ciphertext, it is handed over to the CUA for offline decryption calculation. If the access structure is satisfied, the encapsulated ciphertext can be obtained, and then the symmetric key is used to decrypt the ciphertext. In the scheme, the correctness of the symmetric key can be verified to prevent malicious tampering in the process of transmission. It is indicated that the scheme is secure after being tested with the decisional q-Parallel Bilinear Diffie-Hellman Exponent (BDHE). Numerical analysis shows that the scheme has decreased computational overhead and can achieve fine-grained access control of user decryption rights.

In this paper, a multi-image encryption scheme based on compressed sensing (CS) and deep learning in the optical gyrator domain is proposed. Firstly, multiple plaintext images are compressed by CS to obtain multiple measurements, and then the pixels of each measurement are scrambled by using a chaotic system. Secondly, the scrambled measurements are combined into a matrix and diffused by XOR operation with a chaotic matrix. Finally, the diffused matrix is encoded with a random phase and an optical gyrator transform to obtain a complex-valued matrix, and the amplitude of the complex-valued matrix is taken as the ciphertext. In decrypt, plaintext images are reconstructed from the CS measurements by a neural network, which achieves high reconstruction speed and quality compared with the traditional algorithm. Especially, the data amount of plaintext images can be compressed by up to 8 times while achieving high decryption quality. To our best knowledge, CS reconstruction algorithms based on deep learning is firstly used for image encryption. Moreover, the proposed scheme is highly robust against occlusion, noise, and chosen-plaintext attack.

Proxy re-encryption (PRE) allows a proxy to transform one ciphertext to another under different encryption keys while keeping the underlying plaintext secret. Because of the ciphertext transformability of PRE, there are many potential private communicating applications of this feature. However, existing PRE schemes are not as full-fledged as expected. The lack of necessary features makes them hard to apply in real-world scenarios. So far, there does not exist a unidirectional multihop PRE scheme with constant decryption efficiency and constant ciphertext size without extensions. Impractical performance and weak scalability also hinder PRE from most real-world applications. In this work, we present a new PRE scheme with secure hardware enclave named hPRESS (hardware-enhanced PRE scheme using secure enclave). To the best of our knowledge, hPRESS is the first unidirectional multihop PRE scheme which achieves both constant decryption efficiency and constant ciphertext size without extensions. A detailed security analysis demonstrates that our proposal is CCA secure based on the security of the underlying encryption schemes and the secure enclave. We also implement a prototype based on Intel SGX, one of the most popular secure enclave techniques in recent years, and evaluate its performance. The experimental results show that, compared with previous PRE schemes, our hPRESS is almost one order of magnitude faster in terms of the decryption and transformation.

Highlights: • A novel chaotic asymmetric-key color image encryption algorithm is proposed. • The multiplicative coupled Chebyshev-based encryption scheme allows arbitrary sizes of keyspace. • One pixel may appear in any position throughout the image. • The proposed technique uses tries to achieve the benefits of the one-time pad. Abstract: In this paper, a novel randomized chaotic asymmetric-key algorithm is proposed for color image encryption. Using the multiplicative coupled Chebyshev-based encryption algorithm, a novel chaotic key establishment algorithm using Chebyshev polynomials is proposed. This key establishment algorithm is used to generate three chaotic pseudo-random number sequences to permute the rows and the columns of the plain image randomly. Then, each pixel is XORed with respect to a random value obtained based on its new position to mask its value. The whole encryption algorithm is randomized, so it can resist chosen plaintext attacks. The experimental and security analysis of the proposed algorithm shows that the proposed algorithm has a large keyspace, a good level of security, and an acceptable level of robustness.

The science of hiding messages in a media is an interesting science to learn. Inserting messages either in text, image, sound and video messages requires input in the form of digital files that will be inserted messages, messages to be inserted (message), and keys (keys). More MP3 are chosen for use than using image files. In hiding messages, a format that is more common is used will be chosen so as not to cause excessive suspicion. Encryption is very important in cryptography, is the security of the data sent to maintain its confidentiality. The type of data in writing this report is the data obtained from the literature study to obtain theoretical data that is used as supporting literature to support the research conducted. The source of the data obtained is primary data as a reference, in this case the author gets data from previous researchers that are related to the research that the author did. The steganography method used in this research is parity coding, which is inserting messages / information into the carrier media in the form of MP3 audio files by first being encrypted using cipher caesarean cryptography encryption technique, which is an algorithm with substitution techniques where each letter in the bright text (plaintext ) replaced by another letter that has a certain position difference in the alphabet. This research was made using Visual Basic.Net software. The results of this study in the form of data that has been encrypted using caesar cipher method and hidden into MP3 Audio File then extracted to get text messages and decrypted to get the original message contained in the mp3 file.

To overcome the worse statistical proprieties of digital chaotic maps, this paper proposes a modified version of the Henon chaotic map using a cosine function. What is new in this proposal is that the cosine function replaces only the nonlinear part of the chaotic map which increases the chaotic proprieties compared to other proposals. On the other hand, adding a constant with a high value ( $$F > 10^4$$ ) to the new control parameter eliminates the small zones of stability that cannot be observed easily. The improved Henon map has been evaluated in terms of randomness quality using a set of mathematical tools, in which good results have been obtained. The improved map is used to design a cryptosystem; we have proposed an efficient method for the aim of ensuring the diffusion property by feeding back the encrypted message to the modified map. So, a very small change on the plaintext leads to a different chaotic state. The proposed encryption scheme has been evaluated in terms of security, in which some known cryptographic attacks have been performed on it. The results showed that the proposed encryption scheme meets the nowadays security requirements. The proposed encryption scheme is evaluated in real-time using low-cost ARM (Cortex-M3 32-bit RISC core) under two different scenarios, emitter, and receiver, which are connected wirelessly. A comparison with some existing solutions showed that our proposal provides a good ratio between randomness, implementation cost, and performance.

To protect the privacy of medical images, as well as the patient personal information associated with it, this paper proposes a reversible data hiding scheme for encrypted medical images; whose reversibility is completely separable by allowing additional data extraction and restoration of the region of interest both from the plaintext and the cipher domain of medical images. To this purpose, the pixels in the image are reordered according to the region of interest selected by the content owner and encrypted with a block cipher in counter mode; to subsequently embed additional data into the encrypted image, such as the patient’s personal information and clinical diagnosis, via less significant bit substitution. Finally, according to the proper key, a legitimate receiver can perform the following tasks: a) Obtain a high visual quality approximate image with respect to the original version by directly decrypting the cryptogram with the encryption key, b) With the data hiding key, the embedded data can be extracted free of any error, either from the encrypted image or its approximate version respectively, and c) In case of having both keys, the embedded data can be extracted and the recovered image with the region of interest fully restored can be obtained without loss of information. The proposed method is suitable for applications where the information security and the management of medical images need to be ensured in terms of reliability, integrity, and confidentiality. Comparison performance with the state of the art is performed, in terms of imperceptibility, capacity and steganalysis.

To enhance the security of single-chaotic systems, we propose a novel image encryption cryptosystem based on true random numbers and chaotic systems. First, we select any one of several chaotic systems. Next, the hash function is used to calculate the initial value of the chaotic system using a plaintext image. Then, we obtain a solution of this chaotic system and use the k-medoids clustering machine-learning algorithm and chaotic sequence to scramble the original image. Finally, new random numbers obtained using a chaotic signal and true random numbers are used to perform the exclusive-OR operator on the scrambled results. To illustrate the effectiveness of our method, a one-dimensional (1D) logistic chaotic system is selected for image encryption. The simulation results show that compared with the existing models, such as image encryption based on chaos and image encryption based on the advanced encryption standar (AES), our method is simpler with a higher security and resists different classical attacks.

Cryptography is essential for computer and network security. When cryptosystems are deployed in computing or communication systems, it is extremely critical to protect the cryptographic keys. In practice, keys are loaded into the memory as plaintext during cryptographic computations. Therefore, the keys are subject to memory disclosure attacks that read unauthorized data from RAM. Such attacks could be performed through software exploitations, such as OpenSSL Heartbleed, even when the integrity of the victim system’s binaries is maintained. They could also be done through physical methods, such as cold-boot attacks, even if the system is free of software vulnerabilities. This paper presents Mimosa , to protect RSA private keys against both software-based and physical memory disclosure attacks. Mimosa uses hardware transactional memory (HTM) to ensure that ( a ) whenever a malicious thread other than Mimosa attempts to read the plaintext private key, the transaction aborts and all sensitive data are automatically cleared with hardware, due to the strong atomicity guarantee of HTM; and ( b ) all sensitive data, including private keys and intermediate states, appear as plaintext only within CPU-bound caches, and are never loaded to RAM chips. To the best of our knowledge, Mimosa is the first solution to use transactional memory to protect sensitive data against memory attacks. However, the fragility of TSX transactions introduces extra cache-clogging denial-of-service (DoS) threats, and attackers could sharply degrade the performance by concurrent memory-intensive tasks. To mitigate the DoS threats, we further partition an RSA private-key computation into multiple transactional parts by analyzing the distribution of aborts, while (sensitive) intermediate results are still protected across transactional parts. Through extensive experiments, we show that Mimosa effectively protects cryptographic keys against attacks that attempt to read sensitive data in memory, and introduces only a small performance overhead, even with concurrent cache-clogging workloads.

Large volumes of images are being exponentially generated today, which poses high demands on the services of storage, processing, and management. To handle the explosive image growth, a natural choice nowadays is cloud computing. However, coming with the cloud-based image services is acute data privacy concerns, which has to be well addressed. In this paper, we present a secure cloud-based image service framework, which allows privacy-preserving and effective image denoising on the cloud side to produce high-quality image content, a key for assuring the quality of various image-centric applications. We resort to state-of-the-art image denoising techniques based on deep neural networks (DNNs), and show how to uniquely bridge cryptographic techniques (like lightweight secret sharing and garbled circuits) and image denoising in depth to support privacy-preserving DNN based image denoising services on the cloud. By design, the image content and the DNN model are all kept private along the whole cloud-based service flow. Our extensive empirical evaluation shows that our security design is able to achieve denoising quality comparable to that in plaintext, with high cost efficiency on the local side and practically affordable cost on the cloud side.

Researchers proposed several data-driven methods to efficiently guess user-chosen passwords for password strength metering or password recovery in the past decades. However, these methods are usually evaluated under ad hoc scenarios with limited data sets. Thus, this motivates us to conduct a systematic and comparative investigation with a very large-scale data corpus for such state-of-the-art cracking methods. In this paper, we present the large-scale empirical study on password-cracking methods proposed by the academic community since 2005, leveraging about 220 million plaintext passwords leaked from 12 popular websites during the past decade. Specifically, we conduct our empirical evaluation in two cracking scenarios, i.e., cracking under extensive-knowledge and limited-knowledge. The evaluation concludes that no cracking method may outperform others from all aspects in these offline scenarios. The actual cracking performance is determined by multiple factors, including the underlying model principle along with dataset attributes such as length and structure characteristics. Then, we perform further evaluation by analyzing the set of cracked passwords in each targeting dataset. We get some interesting observations that make sense of many cracking behaviors and come up with some suggestions on how to choose a more effective password-cracking method under these two offline cracking scenarios.

Compared to 1D compressed sensing (CS), 2D CS is more efficient for compressing the plaintext image from two directions, but security level of current 2D CS-based ciphers is unsatisfactory. To solve this problem, this paper presents a novel color image compression and encryption algorithm by combining 2D CS, information entropy and chaos. Firstly, the color image is decomposed into red, green and blue components, then they are sparsely transformed by the discrete wavelet transform (DWT) to get three sparse matrices. Next, the obtained matrices are observed by two asymptotical deterministic random measurement matrices based on information entropy and counter (ADMMIC), which not only encrypts the plaintext image, but also compresses it in proportion to reduce the transmission bandwidth and storage space. Subsequently, the corresponding measurement value matrices are shuffled by a double random scrambling based on Arnold map and index vector (DRSAIV) to eliminate the correlation between adjacent pixels. Furthermore, the obtained permutated matrices are diffused by a simultaneous multiple random diffusion of inter–intra components (SMRDIC) to obtain the final cipher image, the plaintext pixel to be diffused, the key matrix involved in diffusion and the position of the obtained ciphertext pixel are all unpredictable, which makes statistical attack invalid. In addition, information entropy values of plaintext image are obtained to generate the initial values of the used chaotic systems, which greatly improve the ability to resist the known-plaintext and chosen-plaintext attacks. Simulation results and security analyses verify that this algorithm has good compression and high security.

The development of information technology has grown exponentially and various of data collections and its method has been obtained. In the era of big data, data has now become an asset that held important values, while in the implementation of data delivery, it clearly is not always safe. One of the method to secure data delivery is data encryption using Cryptography. Cryptography provides an encryption service to secure data delivery by transforming it to random values so that it can no longer be read. The goal in this study was to produce an application that could be used to encrypt data, using ElGamal's cryptography method and hash checking using the SHA256 algorithm. After encryption, to ensure the encrypted data is still the original data without any changes or manipulation by unauthorized 3rd party then done by checking the hash generated using SHA256 algorithm. The data used in this study was a sample of raw data from the ATPWTP survey (ability to pay and willing to pay) conducted by the BPS Cirebon (Central Statistics) in 2019 and the data was in the form of Excel and txt files. The encryption process resulted in a cipher larger than the plaintext and takes longer for the data encryption process than during the data cipher decryption process.

As the world keeps advancing, the need for automated interconnected devices has started to gain significance; to cater to the condition, a new concept Internet of Things (IoT) has been introduced that revolves around smart devicesʼ conception. These smart devices using IoT can communicate with each other through a network to attain particular objectives, i.e., automation and intelligent decision making. IoT has enabled the users to divide their household burden with machines as these complex machines look after the environment variables and control their behavior accordingly. As evident, these machines use sensors to collect vital information, which is then the complexity analyzed at a computational node that then smartly controls these devicesʼ operational behaviors. Deep learning-based guessing attack protection algorithms have been enhancing IoT security; however, it still has a critical challenge for the complex industries’ IoT networks. One of the crucial aspects of such systems is the need to have a significant training time for processing a large dataset from the networkʼs previous flow of data. Traditional deep learning approaches include decision trees, logistic regression, and support vector machines. However, it is essential to note that this convenience comes with a price that involves security vulnerabilities as IoT networks are prone to be interfered with by hackers who can access the sensor/communication data and later utilize it for malicious purposes. This paper presents the experimental study of cryptographic algorithms to classify the types of encryption algorithms into the asymmetric and asymmetric encryption algorithm. It presents a deep analysis of AES, DES, 3DES, RSA, and Blowfish based on timing complexity, size, encryption, and decryption performances. It has been assessed in terms of the guessing attack in real-time deep learning complex IoT applications. The assessment has been done using the simulation approach and it has been tested the speed of encryption and decryption of the selected encryption algorithms. For each encryption and decryption, the tests executed the same encryption using the same plaintext for five separate times, and the average time is compared. The key size used for each encryption algorithm is the maximum bytes the cipher can allow. To the comparison, the average time required to compute the algorithm by the three devices is used. For the experimental test, a set of plaintexts is used in the simulation—password-sized text and paragraph-sized text—that achieves target fair results compared to the existing algorithms in real-time deep learning networks for IoT applications.

A flexible image cipher based on orthogonal arrays is proposed in this paper. Orthogonal array is a typical combinatorial configuration. It has discreteness and uniformity, which makes orthogonal array a natural candidate for cryptography. In particular, an orthogonal array can provide multiple substitution sequences and permutation maps for image cipher. To control the selection of substitution sequences and permutation maps, two public parameters are introduced in the proposed algorithm. If the parameter values vary, the substitution sequences and permutation maps will be different, then the same plaintext image corresponds to different cipher images. By the utilization of orthogonal arrays, the proposed algorithm is flexible and secure, so it is quite applicable to the complex network environment.

Attribute-based proxy re-encryption (ABPRE), which combines the notions of proxy re-encryption (PRE) and attribute-based encryption (ABE), allows a semi-trusted proxy to transform a ciphertext under a particular access-policy into a ciphertext under another access policy, without revealing any information about the underlying plaintext. This primitive is very useful in some applications, where encrypted data needs to be stored in untrusted environments, such as cloud storage. In its key-policy flavor, the secret key is associated with an access policy that specifies which type of ciphertexts can be decrypted by that key, where ciphertexts are marked with different sets of attributes. However, all existing key-policy attribute-based proxy re-encryption (KP-ABPRE) schemes are based on classical number-theoretic assumptions, which are vulnerable to quantum attacks. This paper proposes the first KP-ABPRE scheme based on the learning with errors (LWE) problem, which is widely believed to be quantum-resistant. Our scheme is multi-hop, supports polynomial-depth policy circuits and has short private keys, where the size of the keys is dependent only on the depth of the supported policy circuits. In addition, we prove that our scheme is CPA secure in the selective security model, based on the LWE assumption.

Deduplication, which can save storage cost by enabling us to store only one copy of identical data, becomes unprecedentedly significant with the dramatic increase in data stored in the cloud. For the purpose of ensuring data confidentiality, they are usually encrypted before outsourced. Traditional encryption will inevitably result in multiple different ciphertexts produced from the same plaintext by different users’ secret keys, which hinders data deduplication. Convergent encryption makes deduplication possible since it naturally encrypts the same plaintexts into the same ciphertexts. One attendant problem is how to reliably and effectively manage a huge number of convergent keys. Several deduplication schemes have been proposed to deal with the convergent key management problem. However, they either need to introduce key management servers or require interaction between data owners. In this paper, we design a novel client-side deduplication protocol named KeyD without such an independent key management server by utilizing the identity-based broadcast encryption (IBBE) technique. Users only interact with the cloud service provider (CSP) during the process of data upload and download. Security analysis demonstrates that KeyD ensures data confidentiality and convergent key security, and well protects the ownership privacy simultaneously. A thorough and detailed performance comparison shows that our scheme makes a better tradeoff among the storage cost, communication and computation overhead.

This paper describes an image encryption algorithm that utilises a plaintext‐related quantisation scheme. Various plaintext‐related approaches from other algorithms are presented and their properties are briefly discussed. Main advantage of the proposed solution is the achievement of a similar behaviour like that of more complex approaches with a plaintext‐related technique used in a rather simple step such as quantisation. This design should result in a favourable computational complexity of the whole algorithm. The properties of the proposal are evaluated by a number of commonly used numerical parameters. Also, the statistical properties of a pseudo‐random sequence that is quantised according to the plain image pixel intensities are investigated by tests from NIST 800‐22 suite. Obtained results are compared to values reported in related works and they imply that the proposed solution produces encrypted images with comparable statistical properties but authors' design is faster and more efficient.

This paper developed for the risk free and person oriented Online Voting System. The Online Voting gadget is made for the humans of the united states living round the world and needs to vote for their representative. The election can be carried out in two methods the paper ballot election and the computerized ballot elections. The automatic ballot elections are referred to as the digital voting. The on line vote casting device is rather developed and the on-line polling machine can be changed through precisely and at once vote casting on line and on the spot results. The on line balloting gadget is completed by using the net so it can be known as the Internet Voting. The gadget proceeds the on-line vote casting machine in a new approach known as Homomorphic Encryption . Homogeneous encryption is the form of encryption, which lets the computer generate encrypted end results in ciphertexts, as though they were performed in a plaintext, when decrypted, which matches the end result of the operations. In this paper we have a digital voting device based on homomorphic encryption to make sure that the vote is confidential. The benefits of multi-homorphic encryption systems are all presented in our suggestion. The proposed electoral system is suitable for elections that include non-partial votes and for multi-candidate elections. For outsourced storage and counting, homomorphic encryption can be used.

Internet of Things (IoT) makes great development and gains popularity with a mature combination with cloud computing. Plaintext data can be encrypted when data owners try to secure the confidentiality, while the encrypted data retrieval can be achieved by a cryptographic primitive named searchable encryption. Public-key encryption with keyword search (PEKS) is built on the asymmetric setting, however, the “honest-but-curious” assumption in PEKS creates challenges on the search reliability when malicious behaviors happen. It is nontrivial to enable the reliable search while preserving keyword privacy, as users who have paid need to receive either correct-and-wanted results or compensations. In this work, we apply blockchain to resolve this problem and design SearchBC, a blockchain-based PEKS framework supporting private, reliable, and fair encrypted search over the asymmetric setting. SearchBC is built on top of the blockchain and a keyword server to allow fairness in transactions and keyword preprocessing. We present a SearchBC instantiation and formally prove its security under the newly defined security model. SearchBC guarantees that search operations are fair and reliable and that the used keyword keeps privacy. The implementation results show that SearchBC provides a feasible means with reasonable communication and computation costs.

This paper presents a novel encryption scheme based on genetic operations and Mixed Linear-Nonlinear Coupled Logistic Map Lattice (MLNCML) spatiotemporal chaotic system. The initial values of the MLNCML system are related to the plain-image. Therefore, this scheme is sensitive to the plaintext and keys. For the simplicity and efficiency of the encryption process, expanded XOR (eXOR) operation and genetic operations are applied in the scheme. Spatiotemporal chaotic system can resist dynamical degradation and periodic phenomena, which offers good randomness for encryption. Moreover, the eXOR operation in this paper can effectively avoid the chosen-plaintext attack of traditional XOR operation. The DNA mutation and crossover operations are controlled by chaotic sequences, which overcome man-in-the-middle attack in the traditional DNA addition and subtraction operation. The experimental results indicate that the proposed scheme has good security to resist common attacks.

A new image encryption scheme is proposed with a combination of block scrambling, closed-loop diffusion, and DNA molecular mutation. The new chaotic block scrambling mechanism is put forward to replace the traditional swapping rule by combining the rectangular-ambulatory-plane cyclic shift with the bidirectional random disorganization. The closed-loop diffusion strategy is designed to form a feedback system, which improves the anti-interference capacity of the algorithm. To further destroy the blocks characteristics and eliminate the correlations among adjacent blocks, two efficient methods of DNA molecular mutation are adopted in the mutation stage. Moreover, the proposed algorithm possesses a large key space and the keys are highly related with the plaintext image. Experimental results demonstrate that the suggested image encryption strategy is practicable and has strong ability against a variety of common attacks.

In recent years, attribute-based encryption (ABE) provides a new idea to help researchers solving the problem of data privacy protection in cloud. But there are two issues in traditional ABE, the first issue is that the attributes in the access structures will be sent to users in cleartext together with the ciphertext. So a attacker has the opportunity to obtain some of the private information from the plaintext access structure. And the other issue is the traditional ABE scheme cannot revoke the users' illegal keys in an efficient way. To handle both of the above challenges, we come up with a large universe ciphertext-policy ABE (CP-ABE) scheme which supports partially hidden access structures (PHAS) and highly efficient key revocation at the same time in this paper. What's more, unlike most previous schemes, first our access structure is based on the expressive linear secret sharing scheme (LSSS) which supports both AND and OR gates in access formulas and second our scheme is built from the prime-order bilinear pairing groups. The comparison with other relevant works presents that our scheme is more comprehensive and efficient. Finally we rigorously prove and analyze that our scheme is selectively indistinguishable secure under chosen plaintext attacks (IND-CPA) in the random oracle model (ROM) and our access structure is really anonymous against off-line dictionary attacks.

In this paper, a new four-dimensional hyperchaotic system that has better unpredictability, more complex dynamic behavior, and a larger key space is proposed. The initial chaos value is calculated by using the Secure Hash Algorithm-512 (SHA-512) function, and the hyperchaotic sequence is then used as the key stream to encrypt the original image through pixel scrambling and pixel diffusion. The experimental results show that the image encryption algorithm has a strong ability to resist exhaustive attacks, statistical attacks and plaintext attacks.

In order to increase encryption capacity and improve transmission efficiency, this paper investigates an encryption scheme for multiple-image based on cascaded gyrator transforms and high-dimensional chaos. Firstly, each plainimage is converted into a real matrix through modulation, quaternion gyrator transform and sharing. The real matrices are connected in turn by plural coding and gyrator transforms. During the process of cascade, phase truncation and preservation operations are performed. The phase of the preceding transformation is modulated by that of the latter complex matrix to enhance security. Followed by splicing and scrambling, a real-valued ciphertext can be obtained. At the receiver end, all the plaintext images can be restituted by the reverse operation of the encryption process using the authorized keys. The adoption of high-dimensioanl chaos and Kronecker product further guarantees the security of the cryptosystem. The numerical results performed on 300 color images have demonstrated that the average PSNR of correctly decrypted images is up to 303.9939 dB, the NMSE is as low as 2.8024 × 10−28 and SSIM is equal to 1.0000. The analysis of sensitivity, statistical characteristic and robustness proves the feasibility and relibility of the proposed encryption scheme.

In this paper, we propose a hyperchaotic image encryption system based on particle swarm optimization algorithm (PSO) and cellular automata (CA). Firstly, to improve the ability to resist plaintext attacks, the initial conditions of the hyperchaotic system are generated by the hash function value which is closely related to the plaintext image to be encrypted. In addition, the fitness of PSO is the correlation coefficient between adjacent pixels of the image. Moreover, On the basis of hyperchaotic system, cellular automata technology is adopted, which can enhance the randomness of population distribution and increase the complexity and diversity of the population so that the security of the encryption system can be improved and avoid falling into local optimum. The simulation results and security analysis of the proposed encryption system demonstrate that the hyperchaotic image encryption system has high resistance against plaintext attack and statistical attack.

In recent years, people have put forward various image encryption algorithms based on pixel level. In fact, bit level encryption has better effect than pixel level encryption. Therefore, this paper proposes a new bit-level image encryption algorithm based on Back Propagation (BP) neural network and Gray code. Firstly, the plaintext image is conversioned into binary image, then, the hyperchaotic Lorentz system is used to generate two sets of chaotic sequences for the Gray code bit-level permutation operation to generate the permutation matrix. Secondly, the permutation matrix is converted into a bit matrix reverse order output to generate a diffusion matrix. Finally, the algorithm uses a BP neural network composed of Logistic map and Piece-Wise Linear Chaotic (PWLCM) map to generate a key stream. The key stream is xored with the diffusion matrix to generate a ciphertext matrix. The experimental results show that the algorithm improves the encryption efficiency, has good security and can resist common attack methods.

A modified XXTEA “M-XXTEA” symmetric block cipher that has a simple construction compared to the advanced encryption standard (AES) is proposed. It is efficient for protecting limited-resource devices such as IoT smart devices. The M-XXTEA will be able to achieve confidentiality during transmission of data over the internet. Since the original XXTEA was vulnerable against key-related and chosen-plaintext attacks. Therefore, this paper introduces a new and robust version of the original XXTEA by employing an improved S-box to enhance security to overcome such types of attacks. Besides, the M-XXTEA is coupled with a chaotic key generator system adding a layer of security achieving the idea behind the one-time pad. The cipher keys are dynamically changing for each block of plaintext when encrypted. Thus, it provides a more robust security mechanism than the original XXTEA and the AES. Besides enhancing data security, the M-XXTEA can function with different sizes of text blocks and with different key sizes. Several experiments are implemented to compare the performance of the M-XXTEA with the original XXTEA and with the AES. Results show that the M-XXTEA encryption and decryption time efficiencies outperform AES by 60%. Besides, the M-XXTEA achieves speed efficiency 57% better than the AES. It can be used efficiently for protecting IoT smart devices in the industry, and e-health systems, and smart cities.

In this paper, in order to solve the problem of un-rigorous scrambling method and single diffusion method in image encryption, a new method based on arithmetic sequence scrambling model, DNA coding sequence and one-dimensional Logistic mapping is proposed. First, the Hash array is obtained by combining the information of the original plaintext image with the Hash algorithm SHA-512. The Hash array generates the initial value and control parameters of the chaotic system, and then generates the chaotic key flow. Second, the arithmetic progression of partitioned matrix after scrambling, change the position of the original image pixels, replacement and operation, and then for DNA combines images and the chaotic sequence of chaotic system to produce DNA, DNA encoding, decoding rules for operation, change the original data bits of pixel values, thus further destruction of the original information. Finally, a chaotic diffusion operation is performed to further change the pixel information of the original image and output the cipher-text image. The experimental results and various security analyses show that the algorithm has good encryption effect and can resist the common plaintext attack, clipping attack and noise attack. The algorithm can be used for image encryption.

With the rapid development of distributed system technologies, one of the biggest challenges facing the digital world is ensuring the security of sensitive and confidential data during transport and storage, which are considered the most critical challenges facing cloud computing. There are many techniques to enhance data security on cloud computing storage environment. Encryption is the most significant method for data protection. Therefore, many available encryption algorithms are used to provide security, integrity, and authorized access using many methods such as DNA. However, they still have some limitations. In this paper, a novel variant of cryptography techniques is designed to improve cloud computing security by using two layers of encryption. The first layer is inspired by Shannon’s theory of diffusion and confusion by the involvement of logical operations, such as (XOR, XNOR, shifting) with split the original plaintext and key into equal parts. The second layer is inspired from structures of genetics based on the Central Dogma of Molecular Biology for cryptographic purpose through simulation of the natural processes of genetic cryptography (translation from binary to DNA bases), transcription (regeneration from DNA to mRNA), and translation (regeneration from mRNA to protein). The experimental results enhanced data security that can be used to secure applications on cloud computing. The proposed algorithm’s experimental results presented a strong security level, an apparent enhancement of cipher size and execution time compared to existing techniques widely used in cloud computing.

Information security has become an intrinsic part of data communication. Cryptanalysis using deep learning–based methods to identify weaknesses in ciphers has not been thoroughly studied. Recently, long short-term memory (LSTM) networks have shown promising performance in sequential data processing by modeling the dependencies and data dynamics. Given an encrypted ciphertext sequence and corresponding plaintext, by taking advantage of sequential processing, LSTM can adaptively discover the decryption function regardless of the complexity level, which substantially outperforms traditional methods. However, a lengthy ciphertext sequence causes LSTM to lose important information along the sequence, leading to a decrease in network performance. To tackle these problems, we propose adding an attention mechanism to enhance the LSTM sequential processing power. This paper presents a novel, dynamic way to attack classical ciphers by using an attention-based LSTM encoder-decoder for different ciphertext sequence lengths. The proposed approach takes in a sequence of ciphertext and outputs a sequence of plaintext. The effectiveness and flexibility of the proposed model were evaluated on different classical ciphers. We got close to 100% accuracy in breaking all types of classical ciphers in character-level and word-level attacks. We empirically provide further insights into our results on two datasets with short and long ciphertext lengths. In addition, we provide a performance comparison of the proposed method against state-of-the-art methods. The proposed approach has the potential to attack modern ciphers. To the best of our knowledge, this is the first time an attention-based LSTM encoder-decoder has been applied to attack classical ciphers.

Based on Sun et al. ’s multi-client symmetric searchable encryption (SSE) scheme (at ESORICS 2016), and combining Zhao’s identity-concealed authenticated encryption (CCS 2016), a new SSE scheme with multi-data-owner functionalities is proposed. By setting two key generation centers, our scheme first implements multi-data-owner SSE. In particular, compared with Sun et al. ’s scheme, the new scheme not only meets the same security requirements stated by them, but also further strengthens the securities of the same category relevant scheme by providing identity-concealment, authentication of data user to server and confidentiality of search token. The identity-concealment aims to provide privacy protection (Forward ID-Privacy) for data users by hiding their identity information, while the authentication is to resist the camouflage attack by applying certificate-based mechanism to our scheme. In particular, the confidentiality of the search token provides replay-attack-resistant by encrypting the plaintext search token generated by data user. While in other works, the adversary can employ the previously generated plaintext search tokens to force the server to perform the same search queries. Furthermore, by efficiency analysis, our scheme reaches almost the same level of efficiency as Sun et al. ’s scheme.

To further improve the security of SHA-256, a compression function construction scheme based on chaotic S-box is proposed. Through the reasonable design of the iteration mode and using the nonlinearity, confusion, and anti-difference of chaotic S-box, the relationship between the plaintext and the hash value becomes more complicated and unpredictable, by the diffusion of the linear transformation P-box, the dependence between the plaintext and the hash value is further improved. The compression function is applied to the SHA-256 Hash Algorithm to test and analyze the distribution, sensitivity, confusion, diffusion, and collision resistance, and compared with the original SHA-256 and the mainstream Hash Algorithms. The results show that the proposed scheme can effectively improve the collision resistance of the SHA-256 Hash Algorithm and enhance the stability of confusion and diffusion with fewer cryptographic components and lower operational consumption to provide more reliable security guarantee for its application.

This paper proposes a novel chaotic block image encryption algorithm based on deep convolutional generative adversarial networks (DCGANs), quaternions, an improved Feistel network, and an overall scrambling and diffusion mechanism. First, a new hyperchaotic system is introduced and combined with DCGANs to generate a random sequence with better randomness and complexity as a key stream. This sequence is then combined with a quaternion and an improved Feistel network encryption of a colour plaintext image by utilizing the key block matrix to ultimately achieve overall scrambling and diffusion of the cipher image. Finally, the security of this algorithm is quantitatively and qualitatively analysed. The simulation results show that the proposed hyperchaotic system has a large key space and good random characteristics and that the new algorithm yields adequate security and can resist brute-force attacks and chosen-plaintext attacks. Therefore, this approach provides a new way to achieve secure transmission and protection of image information.

The present-day society depends heavily on digital technology where it is used in many applications such as banking and e-commerce transactions, computer passwords, etc. Therefore, it is important to protect information when storing and sharing them. Cryptography is the study of secret writing which applies complex math rules to convert the original message into an incomprehensible form. Graph theory is applied in the field of cryptography as graphs can be simply converted into matrices There are two approaches of cryptography; symmetric cryptography and asymmetric cryptography. This paper proposes a new connection between graph theory and symmetric cryptography to protect the information from the unauthorized parties. This proposed methodology uses a matrix as the secret key which adds more security to the cryptosystem. It converts the plaintext into several graphs and represents these graphs in their matrix form. Also, this generates several ciphertexts. The size of the resulting ciphertexts are larger than the plaintext size.

This paper proposes a novel hybrid public/private key cryptography scheme based on perfect Gaussian integer sequences (PGISs) of period $N=pq$ . First, a review study of construction degree-4 PGIS is addressed. We show that circular convolution over PGISs is a trapdoor one-way permutation function that enables simultaneous cipher encryption and digital signatures. To implement the proposed cipher encryption scheme, a private PGIS is assigned as the encryption key sequence for circular convolution with the plaintext to generate the ciphertext. The reverse decryption key sequence involves the time reflection and complex conjugation of the encryption sequence, which can be regenerated using a pair of public and private keys. The security level of the proposed scheme is the same as that of the Rivest-Shamir-Adleman (RSA) system; however, the capacity of a cryptosystem based on PGISs may outperform that of based on RSA, because abundant PGISs are available. Simulation results show that the approximation error when finite digits are used to represent the irrational coefficients of a normalized PGIS can be relatively small compared with the noise. This contributes to the simplicity of this scheme’s implementation. With the fast development of IoT (internet of things), the adaptation and applicability of the proposed scheme to IoT platforms are also addressed, where lightweight cryptographic functions are preferable due to the limited resources of IoT devices.

Polynomial approximation has for the past few years been used to derive polynomials as an approximation to activation functions for use in image prediction or inference employing homomorphic encryption technique to induce data privacy and security. Most proposed works thus far have only been limited to deriving very few polynomials to use for these tasks. While the literature has considered forming new activation functions as pairwise multiplication of well-known activation functions, the design space is mostly unexplored. In some practical applications, there is usually a mix of activation functions used, so looking ahead, there is the need to explore into using other potential functions that can also improve performance whiles not relying on a few ones proposed such as ReLU and Swish. This paper explores the design space of such pairwise, multiplied activation functions and their application in homomorphic image inference or prediction using the widely popular MNIST and CIFAR-10 benchmark datasets. Moreover, we analyzed corresponding curve fitting parameters (range and degree), homomorphic-friendly pooling methods, and optimization methods in the ciphertext domain to avoid incurring huge computation costs but not compromising accuracy. Results show new activation function combinations yielding similar or better results in ciphertext as compared to the ones in plaintext.

Multimedia data security has become a noticeable problem in the continuous development of multimedia technology. Traditional chaotic systems usually require larger bit-width iterative calculations to affect the generation rate of chaotic systems when generating. To solve this problem, we proposed a general Residual Chaotic System (RCS) for image security in heterogeneous multimedia signal processing environments. Based on the Residue Number System (RNS) commonly used in VLSI, we generate the general chaotic sequences by iterating unary polynomial function through it in Galois Field (GF). Moreover, we make use of the Box-Muller algorithm to generate RCS, which improved the speed of operation by a large margin when doing R/B backward transformation. Experiments show that the key sensitivity and plaintext sensitivity of the proposed encryption system are good, and the system can encrypt pictures efficiently and safely. Then, we proposed a watermark embedding and extraction algorithm with block selection. Based on the proposed new judgment conditions, the $4\times 4$ brightness blocks are divided into five categories, then the appropriate types of blocks are selected accordingly. After testing the performance indexes of cypher-text images, including statistical and sensitivity-related tests, all results indicate that our algorithm has good randomness and security. The invisibility is good, the watermark capacity has been significantly improved, and the video bit-rate growth rate is in a good range. The watermark can resist attacks such as noise and the bit error rate under re-encoding and Gaussian low-pass filtering attacks. Compared with other algorithms, the algorithm that we proposed is faster, much more efficient, and more secure. Therefore, it is a practical alternative scheme for heterogeneous communication environments.

In this paper, a noise-resistant image encryption scheme is proposed. We have used a cubic-logistic map, Discrete Wavelet Transform (DWT), and bit-plane extraction method to encrypt the medical images at the bit-level rather than pixel-level. The proposed work is divided into three sections; In the first and the last section, the image is encrypted in the spatial domain. While the middle section of the proposed algorithm is devoted to the frequency domain encryption in which DWT is incorporated. As the frequency domain encryption section is a sandwich between the two spatial domain encryption sections, we called it a ”sandwich encryption.” The proposed algorithm is lossless because it can decrypt the exact pixel values of an image. Along with this, we have also gauge the proposed scheme’s performance using statistical analysis such as entropy, correlation, and contrast. The entropy values of the cipher images generated from the proposed encryption scheme are more remarkable than 7.99, while correlation values are very close to zero. Furthermore, the number of pixel change rate (NPCR) and unified average change intensity (UACI) for the proposed encryption scheme is higher than 99.4% and 33, respectively. We have also tested the proposed algorithm by performing attacks such as cropping and noise attacks on enciphered images, and we found that the proposed algorithm can decrypt the plaintext image with little loss of information, but the content of the original image is visible.

Hundreds of image encryption algorithms have been developed for the security and integrity of images through the combination of DNA computing and chaotic maps. This combination of the two instruments is not sufficient enough to thwart the potential threats from the cryptanalysis community as the literature review suggests. To inject more robustness and security stuff, a novel image encryption scheme has been written in this research by fusing the chaotic system, DNA computing and Castle—a chess piece. As the plain image is input, its pixels are shifted to the scrambled image at the randomly chosen pixel addresses. This scrambling has been realized through the routine called Image Scrambler using Castle (ISUC). Castle randomly moves on the hypothetical large chessboard. Pixels taken from the plain image are shifted to the addresses of the scrambled image, where Castle lands in each iteration. After the plain image is scrambled, it is DNA encoded. Two mask images are also DNA encoded. Then to throw the diffusion effects in the cipher, DNA Addition and DNA XOR operations between the DNA encoded pixels data and the DNA encoded mask images have been conducted. Next, the pixels data are converted back into their decimal equivalents. Four dimensional chaotic system has been used to get the chaotic vectors. The hash codes given by the SHA-256 function have been used in the cipher to introduce the plaintext sensitivity in its design. We got an information entropy of 7.9974. Simulation carried out through the machine, and the thorough security analyses demonstrate the good security effects, defiance to the varied attacks from the cryptanalysis community, and the bright prospects for some real world application of the proposed image cipher.

This paper introduces an image encryption algorithm shorted as CITSPD, manipulated by circle index table scrambling and partition diffusion. Firstly, the circle index table is obtained through the generation, circle shift and transposition of the benchmark sequence. Secondly, the plain image is transformed into the wavelet coefficient and is then scrambled by the circle index table. Thirdly, the permutated image is disturbed by different noises and is further divided into four subsections. Finally, the forward and inverse partition diffusions are performed to the subsections for getting the cipher image. The main feature of this algorithm is that the robust chaos-based keystream and encryption process are highly sensitive to the plaintext, which will effectively resist against chosen-plaintext and known-plaintext attacks. In addition, the encryption scheme is free of noise attack since the inverse diffusion differs from the forward one. And the diffusion effect can be effectively enhanced by, as much as possible, increasing the small pixel value and decreasing the large pixel value. Experimental tests and security analyses are carried out to verify the advantages of the scheme.