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The need of keeping medical information safe and secure stems from the fact that doctors rely on it to make accurate diagnoses. If this information is altered in any way, no matter how minor, there is a risk of an inaccurate diagnosis, which could result in severe medical issues and death. The transition from paper to electronic health records (EHRs) has considerably improved patient care quality and efficiency. However, for many healthcare service providers, it has extended the attack surface. Because of the value of a patient's medical information, this has posed a threat to both patients and healthcare providers. When security is not taken into account in healthcare systems, patients' privacy is jeopardized. The intended solution to this challenge is to create a modified AES algorithm to secure patient medical information. Although, the AES algorithm is secure, however, there is always a need for improvement on any cryptographic algorithms in terms of computational cost. This study implements AES and modified the last round of the AES and their performance has been measured by scrambling input datasets of various contents and volumes. The experimental results show that modified AES outperforms AES algorithms in terms of Encryption time while AES outperform modified AES in terms of decryption time. Also, the Avalanche effect results revealed that modified AES has a higher avalanche effect for small-size files while a smaller avalanche effect for larger file sizes. This signifies that modified AES security is stronger for a small size file while conventional AES has higher security for larger file sizes. The average encryption time of the AES algorithm for text files is 1513.3ms while the modified AES average encryption time gives 1293.837ms. The average decryption time for conventional AES is 1289.627ms while the average decryption time for modified AES give 1400.136ms. Modified AES uses lesser time complexity during the encryption of all categories of data files while conventional AES uses lesser time complexity during the decryption of all categories of data files. [ABSTRACT FROM AUTHOR]

This is our first IET Information Security special issue from the Internation Conference on Information Security and Cryptology, which was held from December 1 to December 3, Seoul, South Korea, 2021. TOPIC B Paper 3 by K. Yamamura, Y. Wang, and E. Fujisaki investigates an enumeration algorithm that is used as a subroutine for the BKZ algorithm, which is one of the most practical reduction algorithms. [Extracted from the article]

The widespread adoption of Internet of Things (IoT) devices in home, industrial, and business environments has made available the deployment of innovative distributed measurement systems (DMS). This paper takes into account constrained hardware and a security-oriented virtual local area network (VLAN) approach that utilizes local message queuing telemetry transport (MQTT) brokers, transport layer security (TLS) tunnels for local sensor data, and secure socket layer (SSL) tunnels to transmit TLS-encrypted data to a cloud-based central broker. On the other hand, the recent literature has shown a correlated exponential increase in cyber attacks, mainly devoted to destroying critical infrastructure and creating hazards or retrieving sensitive data about individuals, industrial or business companies, and many other entities. Much progress has been made to develop security protocols and guarantee quality of service (QoS), but they are prone to reducing the network throughput. From a measurement science perspective, lower throughput can lead to a reduced frequency with which the phenomena can be observed, generating, again, misevaluation. This paper does not give a new approach to protect measurement data but tests the network performance of the typically used ones that can run on constrained hardware. This is a more general scenario typical for IoT-based DMS. The proposal takes into account a security-oriented VLAN approach for hardware-constrained solutions. Since it is a worst-case scenario, this permits the generalization of the achieved results. In particular, in the paper, all OpenSSL cipher suites are considered for compatibility with the Mosquitto server. The most used key metrics are evaluated for each cipher suite and QoS level, such as the total ratio, total runtime, average runtime, message time, average bandwidth, and total bandwidth. Numerical and experimental results confirm the proposal's effectiveness in foreseeing the minimum network throughput concerning the selected QoS and security. Operating systems yield diverse performance metric values based on various configurations. The primary objective is identifying algorithms to ensure suitable data transmission and encryption ratios. Another aim is to explore algorithms that ensure wider compatibility with existing infrastructures supporting MQTT technology, facilitating secure connections for geographically dispersed DMS IoT networks, particularly in challenging environments like suburban or rural areas. Additionally, leveraging open firmware on constrained devices compatible with various MQTT protocols enables the customization of the software components, a crucial necessity for DMS. [ABSTRACT FROM AUTHOR]

Data outsourcing has become more and more popular due to its low cost and flexibility. However, there is a problem that the cloud server used to store data is partially trusted. Searchable encryption is an efficient technology that is devoted to helping people conduct accurate searches without leaking information. Nonetheless, most existing schemes cannot support dynamic updates or meet the privacy requirements of all users. There have been some experiments to solve these issues by implementing a dynamically searchable asymmetric encryption scheme. This paper proposes an efficient searchable encryption scheme based on the Authenticator Bloom Filter (ABF). The solution can support dynamic updates and multiple users and meet forward and backward security. This paper uses an ABF to improve the efficiency of searches and updates while playing a significant role in dynamic updates. This paper designs a new token encryption scheme and file set encryption scheme, which not only helps users reduce time in searches and updates but also supports multi-user modes. Experiments show that the proposed scheme takes less time in searching and updating algorithms, especially when the keyword does not exist. The solution also takes into account the problem of history storage when updating, which reduces the unnecessary consumption of memory and avoids multiple storage states for the same file. [ABSTRACT FROM AUTHOR]

Midori64 is a lightweight SPN block cipher introduced by Banik et al. at ASIACRYPT 2015 and it operates on 64-bit states through 16 rounds using a 128-bit key. In the last decade, Midori64 has been exposed to several attacks. In this paper, to the best of our knowledge, we provide the first boomerang attack on Midori64 in the literature. For this purpose, firstly, we present a practical single key 7-round boomerang attack on Midori64, improving the mixture idea of Biryukov by a new technique which we call “mixture pool”, and then extend our attack up to 9 rounds with time complexity 2122.3, and memory and data complexity 236. (The authors of Midori stated that they expect much smaller rounds than eight rounds of Midori64 are secure against boomerang-type attacks.) We also emphasize that the mixture pool idea provides a kind of data-memory tradeoff and presents more usefulness for boomerang-type attacks. [ABSTRACT FROM AUTHOR]

In the realm of smart communication systems, where the ubiquity of 5G/6G networks and IoT applications demands robust data confidentiality, the cryptographic integrity of block and stream cipher mechanisms plays a pivotal role. This paper focuses on the enhancement of cryptographic strength in these systems through an innovative approach to generating substitution boxes (S-boxes), which are integral in achieving confusion and diffusion properties in substitution–permutation networks. These properties are critical in thwarting statistical, differential, linear, and other forms of cryptanalysis, and are equally vital in pseudorandom number generation and cryptographic hashing algorithms. The paper addresses the challenge of rapidly producing random S-boxes with desired cryptographic attributes, a task notably arduous given the complexity of existing generation algorithms. We delve into the hill climbing algorithm, exploring various cost functions and their impact on computational complexity for generating S-boxes with a target nonlinearity of 104. Our contribution lies in proposing a new cost function that markedly reduces the generation complexity, bringing down the iteration count to under 50,000 for achieving the desired S-box. This advancement is particularly significant in the context of smart communication environments, where the balance between security and performance is paramount. [ABSTRACT FROM AUTHOR]

Various organizations store data online rather than on physical servers. As the number of user's data stored in cloud servers increases, the attack rate to access data from cloud servers also increases. Different researchers worked on different algorithms to protect cloud data from replay attacks. None of the papers used a technique that simultaneously detects a full-message and partial-message replay attack. This study presents the development of a TKN (Text, Key and Name) cryptographic algorithm aimed at protecting data from replay attacks. The program employs distinct ways to encrypt plain text [P], a user-defined Key [K], and a Secret Code [N]. The novelty of the TKN cryptographic algorithm is that the bit value of each text is linked to another value with the help of the proposed algorithm, and the length of the cipher text obtained is twice the length of the original text. In the scenario that an attacker executes a replay attack on the cloud server, engages in cryptanalysis, or manipulates any data, it will result in automated modification of all associated values inside the backend. This mechanism has the benefit of enhancing the detectability of replay attacks. Nevertheless, the attacker cannot access data not included in any of the papers, regardless of how effective the attack strategy is. At the end of paper, the proposed algorithm's novelty will be compared with different algorithms, and it will be discussed how far the proposed algorithm is better than all other algorithms. [ABSTRACT FROM AUTHOR]

Polynomial multiplication is the most computationally expensive part of the lattice-based cryptography algorithm. However, the existing acceleration schemes have problems, such as low performance and high hardware resource overhead. Based on the polynomial multiplication of number theoretic transformation (NTT), this paper proposed a simple element of Montgomery module reduction with pipeline structure to realize fast module multiplication. In order to improve the throughput of the NTT module, the block storage technology is used in the NTT hardware module to enable the computing unit to read and write data alternately. Based on the NTT hardware module, a precalculated parameter storage and real-time calculation method suitable for the hardware architecture of this paper is also proposed. Finally, the hardware of polynomial multiplier based on NTT module is implemented, and its function simulation and performance evaluation are carried out. The results show that the proposed hardware accelerator can have excellent computing performance while using fewer hardware resources, thus meeting the requirements of lattice cipher algorithms in security chips. Compared with the existing studies, the computing performance of the polynomial multiplier designed in this paper is improved by approximately 1 to 3 times, and the slice resources and storage resources used are reduced by approximately 60% and 17%, respectively. [ABSTRACT FROM AUTHOR]

Many symmetric and asymmetric encryption algorithms have been developed in cloud computing to transmit data in a secure form. Cloud cryptography is a data encryption mechanism that consists of different steps and prevents the attacker from misusing the data. This paper has developed an efficient algorithm to protect the data from invaders and secure the data from misuse. If this algorithm is applied to the cloud network, the attacker will not be able to access the data. To encrypt the data, the values of the bytes have been obtained by converting the plain text to ASCII. A key has been generated using the Non-Deterministic Bit Generator (NRBG) mechanism, and the key is XNORed with plain text bits, and then Bit toggling has been implemented. After that, an efficient matrix cipher encryption algorithm has been developed, and this algorithm has been applied to this text. The capability of this algorithm is that with its help, a key has been obtained from the plain text, and only by using this key can the data be decrypted in the first steps. A plain text key will never be used for another plain text. The data has been secured by implementing different mechanisms in both stages, and after that, a ciphertext has been obtained. At the end of the article, the latest technique will be compared with different techniques. There will be a discussion on how the present technique is better than all the other techniques; then, the conclusion will be drawn based on comparative analysis. [ABSTRACT FROM AUTHOR]

Communication security has become particularly crucial with the rapid development of the Internet of Things (IoT). Frequency hopping spread spectrum (FHSS) technology, a prevalent method in wireless communication, has a wide range of applications in the Internet of Things. Enhancing the security of frequency hopping sequences is an essential means to improve the security of frequency hopping communication in the Internet of Things, as the performance of frequency hopping sequences plays a crucial role in frequency hopping systems. This paper proposes constructing secure adaptive frequency hopping sequence sets based on the advanced encryption standard (AES) algorithm. As a block cipher algorithm with superior security, the AES algorithm can provide a fundamental guarantee for the security of the proposed frequency hopping sequences. The mapping methods from ciphertext sequences to frequency hopping sequences proposed in this paper can achieve the construction of frequency hopping sequences of any frequency set size to meet the requirements of adaptive frequency hopping. In addition, we also model and analyse the problem of overlapping spectrum band of the IoT groups in the industrial, scientific, and medical (ISM) band, aiming to achieve better packet transmission performance by adjusting the frequency set size. [ABSTRACT FROM AUTHOR]

With the development of artificial intelligence (AI), deep learning is widely used in various industries. At CRYPTO 2019, researchers used deep learning to analyze the block cipher for the first time and constructed a differential neural network distinguisher to meet a certain accuracy. In this paper, a mixture differential neural network distinguisher using ResNet is proposed to further improve the accuracy by exploring the mixture differential properties. Experiments are conducted on SIMON32/64, and the accuracy of the 8-round mixture differential neural network distinguisher is improved from 74.7% to 92.3%, compared with that of the previous differential neural network distinguisher. The prediction accuracy of the differential neural network distinguisher is susceptible to the choice of the specified input differentials, whereas the mixture differential neural network distinguisher is less affected by the input difference and has greater robustness. Furthermore, by combining the probabilistic expansion of rounds and the neutral bit, the obtained mixture differential neural network distinguisher is extended to 11 rounds, which can realize the 12-round actual key recovery attack on SIMON32/64. With an appropriate increase in the time complexity and data complexity, the key recovery accuracy of the mixture differential neural network distinguisher can be improved to 55% as compared to 52% of the differential neural network distinguisher. The mixture differential neural network distinguisher proposed in this paper can also be applied to other lightweight block ciphers. [ABSTRACT FROM AUTHOR]

In this paper, we present some new observations on the branch number and study concrete differential analysis of SPEEDY. It is a new low-latency block cipher proposed at TCHES 2021. It employs SPS-type round function and consists of only 5/6/7 rounds. Since the iteration rounds are rather small so as to achieve ultra low-latency in encryption speed, it will be crucially important to analyze its security margin accurately. In this paper, we first propose a new notation of partition branch number which can describe the minimum number of active S-boxes for 2-round SPEEDY more accurately. An efficient algorithm to compute the value of partition branch number is also given. Then by extending the notation to higher-order partition branch number, we can obtain more accurate results of the minimum number of active S-boxes for 3–7 rounds. As a result, the maximum expected differential probabilities are significantly higher than the results estimated by designers. Based on this, we search for optimal differential characteristics of SPEEDY while considering the difference distribution table of S-box. We present examples of differential characteristics for 2–7 rounds. Furthermore, by utilizing the simple bit-permutation key schedule of SPEEDY, we can extend the differential trail search method and construct an efficient 6-round related-key differential trail with probability 2 - 179.2 . Based on it, we can present related-key differential attack on full round SPEEDY-7-192 with data complexity of 2 186.2 chosen-plaintexts and time complexity of 2 160.13 encryptions. [ABSTRACT FROM AUTHOR]

With the widespread adoption of applications and IoT devices, modern society has come to rely on them in various aspects of daily life. These applications and devices cover a range of needs, including home appliances and even medical devices for body monitoring. Because a significant amount of data generated by IoT devices and applications must be transmitted over networks, particularly the Internet, there is an increased risk of cyber-attacks on this transmitted data. This data can be text, images, sound, or other forms, and it is critical to ensure its protection, especially if it contains valuable information. Extensive research has been conducted on various encryption algorithms to ensure the security of transmitted data, whether through block ciphers or stream ciphers. In addition, efforts have been made to increase encryption efficiency by securing the transmission channels. The question of this research is “what is the state of the art in the lightweight encryption in terms of strength and speed up the process?”. This paper provides a comprehensive survey of research related to two main categories of lightweight encryption, and work focused on secure authentication between entities. The paper includes an analysis of the techniques used in each surveyed paper and highlights their main results. [ABSTRACT FROM AUTHOR]

Nowadays, it is important to deliver information in a safe and confidential manner to specific individuals or entities. As the best way for the defense is to attack, therefore, cryptanalysis study is important to highlight any weakness of any security algorithm. Usually, attackers or any third-party tries to intercept to do any malicious actions that might cause problems. Bluefish encryption is one of the main methods of protection, which is a 64-bit Feistel network process. The objective of this review paper is to find out in the literature the possible cryptanalysis methods that applied to bluefish encryption. Where, the analyst tries to analyze the ciphers of a particular encryption algorithm by using many traditional methods. Thus, in this paper, review will be dedicated for try to analyze the ciphers using artificial intelligence on symmetric encryption algorithms, such as Blowfish. This approach to cryptanalysis may be more efficient than traditional methods in terms of accuracy, speed, and memory usage. [ABSTRACT FROM AUTHOR]

Cloud cryptography is the art of converting plain text into an unreadable format, which protects data and prevents the data from being misused by the attacker. Different researchers designed various Caesar cipher algorithms for data security. With the help of these algorithms, the data can be converted into a nonreadable format, but the data cannot be completely secured. In this paper, data security is provided in different phases. Firstly, data are secured through a bit-reversing mechanism in which those replace the actual values with no relation to the original data. Then the four-bit values are added at the beginning and end of bits using a salting mechanism to interlink the salting and existing bit-values and hide the original data. A Caesar cipher value is obtained by applying the Caesar cipher algorithm to the resulting bits. The Caesar cipher algorithm is used to implement number-of-shifting on the obtained values. An efficient cipher matrix algorithm is then developed in which different rules are designed to encrypt the data. Afterward, a secure cipher value is obtained by implementing Cipher XORation rules on the result obtained and the user-defined key. In the end, the proposed algorithm is compared with various papers. It identifies how much better the proposed algorithm performs than all the previous algorithms and how much the attack rate can be reduced if this algorithm is used for data security. [ABSTRACT FROM AUTHOR]

SKINNY-64-64 is a lightweight block cipher with a 64-bit block length and key length, and it is mainly used on the Internet of Things (IoT). Currently, faults can be injected into cryptographic devices by attackers in a variety of ways, but it is still difficult to achieve a precisely located fault attacks at a low cost, whereas a Hardware Trojan (HT) can realize this. Temperature, as a physical quantity incidental to the operation of a cryptographic device, is easily overlooked. In this paper, a temperature-triggered HT (THT) is designed, which, when activated, causes a specific bit of the intermediate state of the SKINNY-64-64 to be flipped. Further, in this paper, a THT-based algebraic fault analysis (THT-AFA) method is proposed. To demonstrate the effectiveness of the method, experiments on algebraic fault analysis (AFA) and THT-AFA have been carried out on SKINNY-64-64. In the THT-AFA for SKINNY-64-64, it is only required to activate the THT 3 times to obtain the master key with a 100% success rate, and the average time for the attack is 64.57 s. However, when performing AFA on this cipher, we provide a relationship between the number of different faults and the residual entropy of the key. In comparison, our proposed THT-AFA method has better performance in terms of attack efficiency. To the best of our knowledge, this is the first HT attack on SKINNY-64-64. [ABSTRACT FROM AUTHOR]

Public key Cryptography which is associated with pair of public and private keys is an important requirement for electronic commence in the history of cryptography. Since public key is shared it should be digitally stored in the software in the form of public key Infrastructure (PKI) certificates Elliptic Curve Cryptography plays major role in cloud computing due to the exceptional property of smaller key size. ECC has wide range of applications in Secure Socket Layers (SSL) of cloud computing. The main disadvantage of ECC is the cipher space is two times the message. The present paper explains an innovative elliptic curve cryptosystem that reduces the cipher space, equal to the original message. [ABSTRACT FROM AUTHOR]

In this paper, we perform neural cryptanalysis on five block ciphers: Data Encryption Standard (DES), Simplified DES (SDES), Advanced Encryption Standard (AES), Simplified AES (SAES), and SPECK. The block ciphers are investigated on three different deep learning-based attacks, Encryption Emulation (EE), Plaintext Recovery (PR), Key Recovery (KR), and Ciphertext Classification (CC) attacks. The attacks attempt to break the block ciphers in various cases, such as different types of plaintexts (i.e., block-sized bit arrays and texts), different numbers of round functions and quantity of training data, different text encryption methods (i.e., Word-based Text Encryption (WTE) and Sentence-based Text Encryption (STE)), and different deep learning model architectures. As a result, the block ciphers can be vulnerable to EE and PR attacks using a large amount of training data, and STE can improve the strength of the block ciphers, unlike WTE, which shows almost the same classification accuracy as the plaintexts, especially in a CC attack. Moreover, especially in the KR attack, the Recurrent Neural Network (RNN)-based deep learning model shows higher average Bit Accuracy Probability than the fully connected-based deep learning model. Furthermore, the RNN-based deep learning model is more suitable than the transformer-based deep learning model in the CC attack. Besides, when the keys are the same as the plaintexts, the KR attack can perfectly break the block ciphers, even if the plaintexts are randomly generated. Additionally, we identify that DES and SPECK32/64 applying two round functions are more vulnerable than those applying the single round function by performing the KR attack with randomly generated keys and randomly generated single plaintext. [ABSTRACT FROM AUTHOR]

Block cipher is a cryptographic field that is now widely applied in various domains. Besides its security, deployment issues, implementation costs, and flexibility across different platforms are also crucial in practice. From an efficiency perspective, the linear layer is often the slowest transformation and requires significant implementation costs in block ciphers. Many current works employ lookup table techniques for linear layers, but they are quite costly and do not save memory storage space for the lookup tables. In this paper, we propose a novel lookup table technique to reduce memory storage when executing software. This technique is applied to the linear layer of block ciphers with recursive Maximum Distance Separable (MDS) matrices, Hadamard MDS matrices, and circulant MDS matrices of considerable sizes (e.g. sizes of 16, 32, 64, and so on). The proposed lookup table technique leverages the recursive property of linear matrices and the similarity in elements of Hadamard or circulant MDS matrices, allowing the construction of a lookup table for a submatrix instead of the entire linear matrix. The proposed lookup table technique enables the execution of the diffusion layer with unchanged computational complexity (number of XOR operations and memory accesses) compared to conventional lookup table implementations but allows a substantial reduction in memory storage for the pre-computed tables, potentially reducing the storage needed by 4 or 8 times or more. The memory storage will be reduced even more as the size of the MDS matrix increases. For instance, analysis shows that when the matrix size is 64, the memory storage ratio with the proposed lookup table technique decreases by 87.5% compared to the conventional lookup table technique. This method also allows for more flexible software implementations of large-sized linear layers across different environments. [ABSTRACT FROM AUTHOR]

Summary: The widespread use of Internet of Things devices has increased the demand for lower cost and more efficient lightweight ciphers. However, there is a difficult trade‐off between cost and efficiency for lightweight block ciphers. The optimizations of area and throughput are important for some constrained environments. This paper proposes two novel hardware architectures for the LILLIPUT cipher. In the novel low area structure, a new permutation layer is provided for LILLIPUT. The relationship between encryption algorithm and key scheduling algorithm is utilized to achieve optimal sharing among components, which significantly reduces hardware area. The experimental results show that the number of XOR gates and S‐boxes required for low area optimization is reduced by 52 and 8, respectively. The total area is reduced by about 18%. For high throughput structure, this paper provides 2‐round, 5‐round, and 15‐round loop unrolling designs for LILLIPUT to improve throughput. The experimental results show that the throughput of the 5‐round loop unrolling structure reaches a good level, which is relatively the most cost‐effective. In practical application, ciphers can be unrolled implementations according to the needs of devices to improve the execution speed, which can greatly reduce the execution time and complexity of the algorithm. [ABSTRACT FROM AUTHOR]

Lightweight cryptographic algorithms like Speck, which are a family of block ciphers developed by the US National Security Agency (NSA), have become popular because of their efficient performance and small operational size. This paper introduces the execution on a parallel multi-core processor of the optimized version of the Speck cipher. However, this proposition fulfils the increased demand for developing quick and ultra-lightweight ciphers. In this work, this is addressed by optimizing the speck128/128 cipher by reducing its number of rounds to five. The optimization is accomplished by adding the dynamic substitution layer to increase the randomness of the cipher, which allows us to reduce the speck rounds. We conducted tests such as statistical, randomness, and cryptanalysis tests for linear and differential attacks on the optimized speck. The security results show that the optimized speck overcomes the original speck security level. The conducted experiments show that the new version of the speck runs faster than the original one in terms of execution time and throughput. The parallel execution over a multicore processor is applied, and its speedup ratio is equal to 2.64 when it's compared to the parallel execution of the original speck. Different message sizes and thread configurations are used in this work. The sequential execution of both speck ciphers is computed in terms of execution time and throughput, and the acceleration ratio of the optimized speck in this case is equal to 2.63. [ABSTRACT FROM AUTHOR]

This paper delves into the realm of cryptographic analysis by employing mixed-integer linear programming (MILP), a powerful tool for automated cryptanalysis. Building on this foundation, we apply the division property method alongside MILP to conduct a comprehensive cryptanalysis of the IIoTBC (industrial Internet of Things block cipher) algorithm, a critical cipher in the security landscape of industrial IoT systems. Our investigation into IIoTBC System A has led to identifying a 14-round integral distinguisher, further extended to a 22-round key recovery. This significant finding underscores the cipher's susceptibility to sophisticated cryptanalytic attacks and demonstrates the profound impact of combining the division property method with MILP in revealing hidden cipher weaknesses. In the case of IIoTBC System B, our innovative approach has uncovered a full-round distinguisher. We provide theoretical validation for this distinguisher and uncover a pivotal structural issue in the System B algorithm, specifically the non-diffusion of its third branch. This discovery sheds light on inherent security challenges within System B and points to areas for potential enhancement in its design. Our research, through its methodical examination and analysis of the IIoTBC algorithm, contributes substantially to the field of cryptographic security, especially concerning industrial IoT applications. By uncovering and analyzing the vulnerabilities within IIoTBC, we enhance the understanding of cipher robustness and pave the way for advancements in securing industrial IoT communications. [ABSTRACT FROM AUTHOR]

Nowadays the number of embedded devices communicating over a network is increasing. Thus, the need for security appeared. Considering various constraints for the limited resources devices is very important. These constraints include power, memory, area and latency. A perfect environment for satisfying requirements of security in limited resources devices is lightweight cryptography. A recent lightweight algorithm that has a low area and high throughput which is the ANU-II block cipher. Many technologies like the internet of things (IoT) needed lightweight hardware architectures to provide security for it. In IoT issues like the size of memory, power consumption and smaller gate counts need to take care of by using lightweight cryptography. This paper presents hardware lightweight data path implementation for the ANU-II algorithm using field programmable gate array (FPGA). This paper presents a hardware implementation of a 64-bit ANU-II block cipher. Also, this research presents comparisons based on various design metrics among our data path for the ANU-II cipher and other existing data path designs. The result of the proposed design shows a high throughput of 1502.31, 1951.86, and 2696.47 Mbps. Also, it shows the high efficiency of 7.0201, 31.9977, and 10.6579 Mbps/slice as compared to other ciphers in this paper. [ABSTRACT FROM AUTHOR]

Security of medical images over an unsecured channel is a challenging task, and for this, several methods have been designed recently. The present paper is also in the same direction, and is an attempt to improve the security of the existing methods. In this paper, a cryptosystem is proposed, which performs encryption and decryption in the CBC (Cipher Block Chaining) mode of operation, and attains the confusion-diffusion properties using the PSN (Permutation-Substitution Network) of cryptography. The permutation is performed by a composite operation, consisting of rotation (via special orthogonal group), reflection, flipping, and pixel-wise shuffling, while substitution is performed by a composite operation of multiplication and multiplicative inverse over Galois field. The Archimedes' constant is utilized for constructing Initialization Vector (IV) to be used in the CBC mode of encryption (and decryption). The proposed approach is able to encrypt monochrome (8-bit, 10-bit, 12-bit, and 16-bit), palette color, and 24-bit color medical images, simultaneously into noisy-like images from the human visual as well as the statistical point of view. The designed approach is empirically assessed via several statistical and security evaluation metrics, such as key sensitivity, chi-squared test, number of pixel change rate, avalanche effect, poker test, peak signal-to-noise ratio, etc. The results of these metrics support the objectives of our proposed approach. Moreover, a thorough comparison is also made with the recent state-of-the-art existing methods. [ABSTRACT FROM AUTHOR]

In cryptography, a mode of operation is the way of processing plaintext and encrypted text blocks within a block cipher algorithm, or it is the presentation of a method of chaining blocks in a block cipher. Several models exist with their strengths, some are more vulnerable than others, and some combine authentication and security concepts. In this paper, a new mode of operation is proposed, inspired by the braid of long hair which we call mode CBLCH (Cipher Braided Long Hair Chaining). The HILL cipher will be used to validate it and to compare it with ECB (Electronic Code-Book: code dictionary) and CBC mode (Cipher Block Chaining: sequence of blocks) by the influence of a pixel change on the plaint-image and the encrypted image. [ABSTRACT FROM AUTHOR]

With the rapid evolvement of cryptanalysis, attacks with multiple distinguishers have emerged gradually. Many new cryptanalytic methods such as multiple differential cryptanalysis, multiple linear cryptanalysis, multiple impossible differential cryptanalysis, multidimensional zero correlation linear cryptanalysis have been proposed, which have greatly enhanced the efficiency of corresponding attacks. During these attacks, discovering more distinguishers has always been a trivial and manual work. Many cryptographers use their expertise and experience to achieve this goal. However, in most cases, either the length of the attack or the number of distinguishers is underestimated. This paper proposes a generic method to discover more different distinguishers based on a new property called "weak rotational property". Block ciphers with this property can easily discover more distinguishers such as truncated differential distinguishers, impossible differential distinguishers and zero correlation linear distinguishers in a theoretical approach. Then the number of equivalent distinguishers is proved in a mathematical form. As an application, this paper focuses on SIMON family ciphers to illustrate how this property improves cryptanalysis. For the section of application, first of all, SIMON family ciphers are proved to have weak rotational property. Thus the number of corresponding discovered distinguishers can be increased for SIMON. Then, some earlier observations on SIMON are extended accordingly to this new property. Finally, based on the idea of weak rotational property and equivalent-subkey technique, an improved impossible differential cryptanalysis on SIMON is proposed. For SIMON32(64)/SIMON128(128)/SIMON128(192), the rounds attacked are all extended by one round. For other variants of SIMON, current best non full codebook impossible differential attacks are derived. The successful application of weak rotational property indicates its potential in cryptanalysis. [ABSTRACT FROM AUTHOR]

As the current society is increasingly facing major challenges from extremism and terrorism, protecting key urban public facilities and important targets from destruction is an important challenge facing the security departments of all countries. Based on real scene, this paper conducts researches on anti-terrorism security game algorithms and emergency response models in response to the three key links of before, during and after terrorist attacks. First of all, this paper constructs a multi-round joint attack game and emergency response model based on cooperation, establishes the optimization problem of solving the defender's optimal strategy in mathematical form, and then obtains the optimal defense strategy. Secondly, in response to the fact that terrorists are not completely rational, a new hybrid model is constructed to propose an efficient allocation and scheduling algorithm for safe resources in response to terrorist attacks. Thirdly, a model of crowd evacuation strategy after a terrorist attack is built based on the problem of crowd evacuation in multiple rounds of premeditated cooperative attacks. Finally, taking the area of the first ring of a certain city as a real scene, a complete game system of the whole process is constructed, and the game effectiveness evaluation of the existing security resource allocation scheme in the first ring area is carried out. Through the research of this thesis, the author puts forward some new technical ideas for the current society's anti-terrorism governance, and hopes to provide some technical references for the decision-making of security agencies. [ABSTRACT FROM AUTHOR]

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In symmetric cryptography, block ciphers, stream ciphers and permutations often make use of a round function and many round functions consist of a linear and a non-linear layer. One that is often used is based on the cellular automaton that is denoted by χ as a Boolean map on bi-infinite sequences, F 2 Z . It is defined by σ ↦ ν where each ν i = σ i + (σ i + 1 + 1) σ i + 2 . A map χ n is a map that operates on n-bit arrays with periodic boundary conditions. This corresponds with χ restricted to periodic infinite sequences with period that divides n. This map χ n is used in various permutations, e.g., Keccak-f (the permutation in SHA-3), ASCON (the NIST standard for lightweight cryptography), Xoodoo, Rasta and Subterranean (2.0). In this paper, we characterize the graph of χ on periodic sequences. It turns out that χ is surjective on the set of all periodic sequences. We will show what sequences will give collisions after one application of χ . We prove that, for odd n, the order of χ n (in the group of bijective maps on F 2 n ) is 2 ⌈ lg (n + 1 2) ⌉ . A given periodic sequence lies on a cycle in the graph of χ , or it can be represented as a polynomial. By regarding the divisors of such a polynomial one can see whether it lies in a cycle, or after how many iterations of χ it will. Furthermore, we can see, for a given σ , the length of the cycle in its component in the state diagram. Finally, we extend the surjectivity of χ to F 2 Z , thus to include non-periodic sequences. [ABSTRACT FROM AUTHOR]

Permutation codes are studied due to their numerous applications in various applications, such as power line communications, block ciphers, and coding for storage. In this paper, we study perfect permutation codes in S n , the set of all permutations on n elements, under the ℓ ∞ -metric. We present some nonexistence results on perfect t-error-correcting permutation codes in S n under the ℓ ∞ -metric for some t and n. More precisely, we prove that there does not exist a perfect t-error-correcting code in S n under the ℓ ∞ -metric for t and n satisfying 1 ≤ t ≤ 3 , 2 t + 1 ≤ n or for t and n satisfying R 2 t + 1 (n) = 0 , 1 , 2 t , where 0 ≤ R d (n) < d is the residue when dividing the positive integer n by the positive integer d. [ABSTRACT FROM AUTHOR]

Security vulnerabilities in the symmetric-key primitives of a cipher can undermine the overall security claims of the cipher. With the rapid advancement of quantum computing in recent years, there is an increasing effort to evaluate the security of symmetric-key cryptography against potential quantum attacks. This paper focuses on analyzing the quantum attack resistance of AIM, a symmetric-key primitive used in the AIMer digital signature scheme. We present the first quantum circuit implementation of AIM and estimate its complexity (such as qubit count, gate count, and circuit depth) with respect to Grover's search algorithm. For Grover's key search, the most important optimization metric is depth, especially when considering parallel search. Our implementation gathers multiple methods for a low-depth quantum circuit of AIM in order to reduce the Toffoli depth and full depth (such as the Karatsuba multiplication and optimization of inner modules;  Mer ,  LinearLayer). [ABSTRACT FROM AUTHOR]

Meet-in-the-middle (MitM) attack method has led to the best currently published cryptanalytic results on the AES block cipher in the single-key attack scenario, except biclique attack. Particularly, for AES with a 256-bit key (AES-256), Li and Jin published a MitM attack on 10-round AES-256 in 2016, which has a data complexity of 2 111 chosen plaintexts, a memory complexity of 2 215.2 bytes and a time complexity of 2 253 10-round AES-256 encryptions under so-called weak-key approach. In this paper, we observe that the memory complexity of Li and Jin's attack should be 2 217.4 bytes, then we show that three other byte key relations can be used to further reduce the memory complexity in Li and Jin's attack by decomposing Li and Jin's big precomputational table into two smaller ones and using MixColumns' property to connect the two smaller tables in online key-recovery phase, which produces a 10-round AES-256 attack with a memory complexity of 2 189 bytes and a time complexity of 2 255 10-round AES encryptions, and finally we exploit a different 6-round MitM distinguisher to mount a 10-round AES-256 attack with a data complexity of 2 105 chosen plaintexts, a memory complexity of 2 189 bytes and a time complexity of 2 253.2 10-round AES encryptions. Our final attack has a much smaller data and memory complexity and a marginally larger time complexity than Li and Jin's attack. [ABSTRACT FROM AUTHOR]

In modern information technology, research on block cipher security is imperative. Concerning the ultra lightweight block cipher PICO, there has been only one study focused on recovering its complete master key, with a large search space of 2 64 , and no fault analysis yet. This paper proposes a new fault analysis approach, combining differential fault and algebraic equation techniques. It achieved the recovery of PICO's entire master key with 40 faults in an average time of 0.57 h. S-box decomposition was utilized to optimize our approach, reducing the time by a remarkable 75.83% under the identical 40-fault condition. Furthermore, PICO's complete master key could be recovered with 28 faults in an average time of 0.78 h, indicating a significant 2 37 reduction in its search space compared to the previous study. This marks the first fault analysis on PICO. Compared to conventional fault analysis methods DFA (differential fault analysis) and AFA (algebraic fault analysis), our approach outperforms in recovering PICO's entire master key, highlighting the cruciality of key expansion complexity in block cipher security. Therefore, our approach could serve to recover master keys of block ciphers with comparably complicated key expansions, and production of more secure block ciphers could result. [ABSTRACT FROM AUTHOR]

The SAND algorithm is a family of lightweight AND-RX block ciphers released by DCC in 2022. Our research focuses on assessing the security of SAND with a quantum computation model. This paper presents the first quantum implementation of SAND (including two versions of SAND, SAND-64 and SAND-128). Considering the depth-times-width metric, the quantum circuit implementation of the SAND algorithm demonstrates a relatively lower consumption of quantum resources than that of the quantum implementations of existing lightweight algorithms. A generalized Grover-based brute-force attack framework was implemented and employed to perform attacks on two versions of the SAND algorithm. This framework utilized the g-database algorithm, which considered different plaintext–ciphertext pairs in a unified manner, reducing quantum resource consumption. Our findings indicate that the SAND-128 algorithm achieved the NIST security level I, while the SAND-64 algorithm fell short of meeting the requirements of security level I. [ABSTRACT FROM AUTHOR]

This paper presents a study aimed at effectively implementing a deterministic random bit generator (DRBG) IP in verilog language, based on the standard encryption algorithm. By controlling the existing round generation and key generation blocks, the internal modules of the counter mode deterministic random bit generator (CTR-DRBG) were successfully implemented and operated, ensuring the secure and efficient generation of random bit sequences. The research focused on parallel operation of modules and optimized module placement to achieve improved clock frequencies. By concurrently operating two modules in the derivation and internal update modules of CTR-DRBG, the processing speed was enhanced compared to the conventional algorithm. Additionally, integrating the reseeding and initialization modules of CTR-DRBG into a single module successfully reduced size. Furthermore, this IP supports the special function register (SFR) interface. The safety of the CTR-DRBG was validated through known answer test (KAT) verification utilizing test vectors from certification. Future research should explore additional studies on CTR-DRBG operating on real FPGA or ASIC, not only using normal algorithm but also employing other block cipher algorithms. [ABSTRACT FROM AUTHOR]

Cryptographic devices' complexity necessitates fast security simulation environments against fault attacks. SystemC, a promising candidate in Electronic System Levels (ESLs), can achieve higher simulation speeds while maintaining accuracy and reliability, and its modular and hierarchical design allows for efficient modeling of complex cryptographic algorithms and protocols. However, code modification is required for fault injection and detection. Aspect-Oriented Programming (AOP) can test cryptographic models' robustness without modifications, potentially replacing real cryptanalysis schemes and reducing the time and effort required for fault injection and detection. Through the utilization of a fault injection/detection environment, this paper presents a novel approach to simulating the security fault attacks of ASCON cryptographic systems at the ESL. The purpose of this methodology is to evaluate the resistance of ASCON SystemC models against fault attacks. The proposed methodology leverages the advantages of AOP to enhance the fault injection and detection process. By applying AOP techniques, we inject faults into the SystemC models without making any changes to the main codebase. This approach not only improves the efficiency of testing cryptographic systems but also ensures that the main functionality remains intact during the fault injection process. The methodology was validated using three scenarios and SystemC ASCON as a case study. The first simulation involved evaluating fault detection capabilities, the second focused on the impact of AOP on executable file size and simulation time, and the third focused on the ESL impact on the ASCON design process. Simulation results show that this methodology can perfectly evaluate the robustness of the ASCON design against fault injection attacks with no significant impact on simulation time and file executable size. Additionally, the simulation results prove that the ASCON development life cycle at the ESL reduces the amount of time devoted to the design procedure by 83.34%, and the ASCON security attack simulations at the ESL decrease the simulation time by 40% compared to the register transfer level (RTL). [ABSTRACT FROM AUTHOR]

To obtain reliable results from conflicting data in mobile crowdsensing, numerous truth discovery protocols have been proposed in the past decade. However, most of them do not consider the data privacy of entities involved (e.g., workers and servers), and several existing privacy-preserving truth discovery protocols either provide limited privacy protection or have heavy computation and communication overheads due to iterative computation and transmission over large ciphertexts. In this paper, we aim to propose privacy-preserving and lightweight truth discovery protocols to tackle the above problems. Specifically, we carefully design an anonymization protocol named AnonymTD to delink workers from their data, where workers’ data are computed and transmitted without complicated encryption. To further reduce each worker's overheads in the scenarios where workers are willing to share their weights, we resort to the perturbation technology to propose a more lightweight truth discovery protocol named PerturbTD. Based on workers’ perturbed data, two cloud servers in PerturbTD complete most of the workload of truth discovery together, which avoids the frequent involvement of workers. The theoretical analysis and the comparative experiments in this paper demonstrate that our two protocols can achieve our security goals with low computation and communication overheads. [ABSTRACT FROM AUTHOR]

This paper presents a novel encryption method based on individual block ciphering using Catalan random walks. This paper aims to offer some new possibilities of multimedia data protection to realize the rights of participants in the multimedia distribution chain (image, text, video, sound). Also, the emphasis is on advanced analysis of Catalan numbers and their combinatorial representations in multimedia security. The proposed method consists of five phases: conversion, division, selection, encryption, and generation. We presented the application of our method in ensuring the security of multimedia content. The proposed method was implemented in Java. In the experimental testing, we provide the time and space complexity of Catalan keys generation and Maurer's universal statistical test for the proposed method. Also, we state security analysis using machine learning methods and comparative analysis with existing methods of encrypting data into a blockchain. [ABSTRACT FROM AUTHOR]

A tweakable enciphering scheme (TES) is a length preserving (tweakable) encryption scheme that provides (tweakable) strong pseudorandom permutation security on arbitrarily long messages. TES is traditionally built using block ciphers and the security of the mode depends on the strong pseudorandom permutation security of the underlying block cipher. In this paper, we construct TESs using public random permutations. Public random permutations are being considered as a replacement of block cipher in several cryptographic schemes including AEs, MACs, etc. However, to our knowledge, a systematic study of constructing TES using public random permutations is missing. In this paper, we give a generic construction of a TES which uses a public random permutation, a length expanding public permutation based PRF and a hash function which is both almost xor universal and almost regular. Further, we propose a concrete length expanding public permutation based PRF construction. We also propose a single keyed TES using a public random permutation and an AXU and almost regular hash function. [ABSTRACT FROM AUTHOR]

The latest version of ZigBee offers improvements in various aspects, including its low power consumption, flexibility, and cost-effective deployment. However, the challenges persist, as the upgraded protocol continues to suffer from a wide range of security weaknesses. Constrained wireless sensor network devices cannot use standard security protocols such as asymmetric cryptography mechanisms, which are resource-intensive and unsuitable for wireless sensor networks. ZigBee uses the Advanced Encryption Standard (AES), which is the best recommended symmetric key block cipher for securing data of sensitive networks and applications. However, AES is expected to be vulnerable to some attacks in the near future. Moreover, symmetric cryptosystems have key management and authentication issues. To address these concerns in wireless sensor networks, particularly in ZigBee communications, in this paper, we propose a mutual authentication scheme that can dynamically update the secret key value of device-to-trust center (D2TC) and device-to-device (D2D) communications. In addition, the suggested solution improves the cryptographic strength of ZigBee communications by improving the encryption process of a regular AES without the need for asymmetric cryptography. To achieve that, we use a secure one-way hash function operation when D2TC and D2D mutually authenticate each other, along with bitwise exclusive OR operations to enhance cryptography. Once authentication is accomplished, the ZigBee-based participants can mutually agree upon a shared session key and exchange a secure value. This secure value is then integrated with the sensed data from the devices and utilized as input for regular AES encryption. By adopting this technique, the encrypted data gains robust protection against potential cryptanalysis attacks. Finally, a comparative analysis is conducted to illustrate how the proposed scheme effectively maintains efficiency in comparison to eight competitive schemes. This analysis evaluates the scheme's performance across various factors, including security features, communication, and computational cost. [ABSTRACT FROM AUTHOR]

As IoT technology develops, many sensor devices are being used in our life. To protect such sensor data, lightweight block cipher techniques such as SPECK-32 are applied. However, attack techniques for these lightweight ciphers are also being studied. Block ciphers have differential characteristics, which are probabilistically predictable, so deep learning has been utilized to solve this problem. Since Gohr's work at Crypto2019, many studies on deep-learning-based distinguishers have been conducted. Currently, as quantum computers are developed, quantum neural network technology is developing. Quantum neural networks can also learn and make predictions on data, just like classical neural networks. However, current quantum computers are constrained by many factors (e.g., the scale and execution time of available quantum computers), making it difficult for quantum neural networks to outperform classical neural networks. Quantum computers have higher performance and computational speed than classical computers, but this cannot be achieved in the current quantum computing environment. Nevertheless, it is very important to find areas where quantum neural networks work for technology development in the future. In this paper, we propose the first quantum neural network based distinguisher for the block cipher SPECK-32 in an NISQ. Our quantum neural distinguisher successfully operated for up to 5 rounds even under constrained conditions. As a result of our experiment, the classical neural distinguisher achieved an accuracy of 0.93, but our quantum neural distinguisher achieved an accuracy of 0.53 due to limitations in data, time, and parameters. Due to the constrained environment, it cannot exceed the performance of classical neural networks, but it can operate as a distinguisher because it has obtained an accuracy of 0.51 or higher. In addition, we performed an in-depth analysis of the quantum neural network's various factors that affect the performance of the quantum neural distinguisher. As a result, it was confirmed that the embedding method, the number of the qubit, and quantum layers, etc., have an effect. It turns out that if a high-capacity network is needed, we have to properly tune properly to take into account the connectivity and complexity of the circuit, not just by adding quantum resources. In the future, if more quantum resources, data, and time become available, it is expected that an approach to achieve better performance can be designed by considering the various factors presented in this paper. [ABSTRACT FROM AUTHOR]

Cryptographic algorithm identification is aimed to analyze the potential feature information in ciphertext data when the ciphertext is known, which belongs to the category of cryptanalysis. This paper takes block cipher algorithm as the research object, and proposes a block cipher algorithm identification scheme based on hybrid random forest and logistic regression (HRFLR) model with the idea of ensemble learning. Based on the NIST randomness test feature extraction method, five block ciphers, AES, 3DES, Blowfish, CAST and RC2, are selected as the research object of cryptographic algorithm identification to carry out the ciphertext classification tasks. The experimental results show that, compared with the existing methods, the cryptographic algorithm identification scheme based on HRFLR proposed in this paper has higher accuracy and stability on binary classification and multi-class classification tasks. In the binary classification tasks of AES and 3DES, the identification accuracy of our proposed cryptographic algorithm identification scheme based on HRFLR can reach up to 74%, and the highest identification accuracy of the five classification tasks is 38%. Compared with the 54% and 28.8% accuracies of random forest-based identification scheme, the accuracy is increased by 37.04% and 18.06%, respectively. This result is significantly better than the 50% and 20% accuracies of random guessing scheme. [ABSTRACT FROM AUTHOR]

Chaos has been one of the most effective cryptographic sources since it was first used in image-encryption algorithms. This paper closely examines the development process of chaos-based image-encryption algorithms from various angles, including symmetric and asymmetric algorithms, block ciphers and stream ciphers, and integration with other technologies. The unique attributes of chaos, such as sensitivity to initial conditions, topological transitivity, and pseudo-randomness, are conducive to cross-referencing with other disciplines and improving image-encryption methods. Additionally, this paper covers practical application scenarios and current challenges of chaotic image encryption, thereby encouraging researchers to continue developing and complementing existing situations, and may also serve as a basis of future development prospects for chaos-based image encryption. [ABSTRACT FROM AUTHOR]

Lightweight block ciphers are normally used in low-power resource-constrained environments, while providing reliable and sufficient security. Therefore, it is important to study the security and reliability of lightweight block ciphers. SKINNY is a new lightweight tweakable block cipher. In this paper, we present an efficient attack scheme for SKINNY-64 based on algebraic fault analysis. The optimal fault injection location is given by analyzing the diffusion of a single-bit fault at different locations during the encryption process. At the same time, by combining the algebraic fault analysis method based on S-box decomposition, the master key can be recovered in an average time of 9 s using one fault. To the best of our knowledge, our proposed attack scheme requires fewer faults, is faster to solve, and has a higher success rate than other existing attack methods. [ABSTRACT FROM AUTHOR]

Security is the study of encryption and decryption, data hiding, potential attacks, and performance evaluation. Many algorithms perform this purpose. Blowfish is a symmetric block cipher that uses the Feistel network. Although several works employed the Blowfish algorithm for the security of the cloud, there is still no article that lists previous studies. Cloud computing is the transmission of computer services such as servers, storage, databases, networking, software, analytics, and intelligence through the Internet ("the cloud") in order to provide faster innovation, more flexible resources, and cost savings. The most common issue with cloud computing is information security, privacy, confidentiality, and how the cloud provider ensures these services. This paper includes a survey of most previous works that were concerned with using the Blowfish algorithm in achieving cloud security [ABSTRACT FROM AUTHOR]