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Outsourcing medical data to healthcare cloud has become a popular trend. Since medical data of patients contain sensitive personal information, they should be encrypted before outsourcing. However, information retrieval methods based on plaintext cannot be directly applied to encrypted data. In this paper, we present a new cryptographic primitive named conjunctive keyword search with secure channel free and autonomous path delegation function (AP-SCF-PECKS), which can be applied in scenarios where patients want to search for and autonomous delegate their private medical information without revealing their private key. Particularly, the proposed solution allows patients to set up multi-hop delegation path with their preferences, and the delegated doctors in the path can search for and access the patient's private medical information with priority from high to low. Patients can ensure that authorized doctors are always trustworthy, and unauthorized users cannot obtain the private medical information of patients. Moreover, the scheme supports the conjunctive keyword search, secure channel free, and is secure against chosen keyword attack, chosen ciphertext attack, and keyword guessing attack. The security of proposed scheme has been formally proved in the standard model. Finally, the performance evaluations demonstrate that the overhead of proposed scheme are modest for healthcare cloud scenarios.

Recently, Ivanov et al. proposed a new approach to construct code-based cryptosystems, namely the \begin{document}$ {\sf IKKR} $\end{document} public-key encryptions (PKE) in the International Workshop on Code-Based Cryptography (CBCrypto 2020) [ 9 ]. Unlike the usual construction in code-based encryption schemes which has restrictions on the Hamming weight of the error introduced into the ciphertext, the \begin{document}$ {\sf IKKR} $\end{document} approach allows error vectors of arbitrary weight being introduced into the ciphertext. Using this new approach, Ivanov et al. constructed two cryptosystems, namely the modified and the upgraded \begin{document}$ {\sf IKKR} $\end{document} -PKE. This paper aims to discuss the practical security of the \begin{document}$ {\sf IKKR} $\end{document} -PKE. In particular, we describe the weaknesses in the design of the public key used in the \begin{document}$ {\sf IKKR} $\end{document} -PKE. We exploit such weaknesses and propose two attacks to recover the plaintext in the \begin{document}$ {\sf IKKR} $\end{document} -PKE. The approach of our first attack is similar to the LCKN attack [ 12 ], whilst our second attack is more efficient than the LCKN attack. Our experimental results show that we can recover the plaintext from a given ciphertext in less than 176 milliseconds for schemes based on random Goppa codes and BCH codes.

The cloud server stores its unique DE-duplicate data replication cloud storage system as outsourced only data copies. Deduplication cloud storage audits can verify the integrity of data stored in the cloud, while the cloud calculates the need to maintain only one copy of the copied file. The existing de-duplication auditing solutions for cloud storage are vulnerable to brute-force dictionary attacks, which is a disclosure leakage of user privacy and more time consumption to find a duplicate files in cloud. Users must check the integrity of lightweight cloud computing data to create data authentication and retrieve files in the cloud. The proposed system uses a secure Array Preserving Triple Data Encryption (AP3DE) algorithm to verify with confidence the expertise of aggregate technology. In this method to analysis the user upload document before store on cloud. The aggregator to provide an authentication access the data access role to cloud user. Cloud protects the privacy, confidentiality, and integrity of data stored in the cloud by generating the code of the authentication file and the encryption key of the file through the proposed system test. The Index-level Boundary Pattern Convergent Encryption (IBPCE) algorithm integrates dynamic data handling and data exclusion capabilities for secure cloud storage privacy security public audits. The cloud data security using a Convergent international data encryption algorithm used to encrypted data. It is a 64 bit plaintext and cipher text blocks is controlled by 128 bit key. Analysis of safety and efficiency shows that the proposed mechanism is highly efficient and safe. In this proposed IBPCE method to manage and reduce the cloud storage compare to other existing method.

Encryption and compression are two critical techniques to ensure data confidentiality and efficiency for a cloud-based data storage system, respectively. However, directly combing encryption and compression incurs substantial performance degradation. We propose TinyEnc, an encrypted data storage system for cloud-based key-value store. TinyEnc supports encryption and compression simultaneously with rich query support.To reconcile encryption and compression without compromising performance, we propose a new encrypted compression data structure to enable fine-grained access to compressed and encrypted key-value data. We then propose two new transforming mechanisms, namely orthogonal data dividing and hierarchical data padding, to transform a plaintext key-value table into the encrypted compression data structure in a privacy-preserving way. Finally, we craft order-revealing encryption (ORE) and symmetric searchable encryption (SSE) to design a new encrypted search index over the encrypted compression data structure to support rich types of data queries. We implement a prototype of TinyEnc on top of Cassandra. Our evaluation shows that TinyEnc increases the throughput by up to 7 times and compression ratio by up to 1.3 times with respect to previous works.

Its size and complexity, cloud externalization is considered for enhancing security in API. Nonetheless, cloud storage API has two key problems that allows user usability to be effectively functioning and that securely update cipher text in cloud through a new access policy for data owner. This paper recommends an effective secure access update algorithm based on an optimum cryptographic algorithm for API in cloud. Proposed method uses an optimal homomorphic Encryption (OHE) algorithm for secure storage. With Adaptive Salp Swarm Optimizations (ASSO), key values for the OHE algorithm are optimally selected. The proposed project also allows cloud server to efficiently update cipher text and monitor updates against cloud misbehaviors when a new access policy has been mentioned by data owner. It enables data proprietor and skilled users to effectively monitor legitimacy user data access and allow the user to verify that information provided by others is correctly recovered in plaintext. For that, the suggested method utilizes the attribute based access control model. Its analysis reveals how the policy reform program is formulated accurately, completely, safely and efficiently. The performance of the method proposed is measured by differentiating data and the cluster size due to its memory and execution times. Unlike the existing systems with a secure update in the access policies, this approach consumes minimum memory and time. The proposed process is introduced in cloud handset to Hadoop Map Reduction Framework.

Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is one of the potent encryption paradigms in protecting data confidentiality in the cloud data sharing scenario. However, the access policy of the traditional CP-ABE is in plaintext form that reveals significant sensitive information of data owners and data visitors. To mitigate this problem, two approaches have been proposed in the literature. One is partially hidden, where the attributes in the access policy are divided into two parts: the plaintext attribute names and the hidden attribute values. The other approach fully hides the attributes in the access policy which, unfortunately, hinders efficient and correct decryption as well as dynamic policy-updating. In this paper, we design a security-enhanced Attribute Cuckoo Filter (se-ACF) to hide the access policy and propose a new CP-ABE system, called Privacy-Preserving Policy Updating ABE (3PU-ABE), which effectively integrates policy hiding and policy updating. We conduct rigorous security analysis and performance evaluation of 3PU-ABE. The results indicate that 3PU-ABE completely hides the access policy without affecting the decryption, and entails better policy-updating efficiency than similar works.

Cloud-assisted Internet of Things (IoT) is increasingly prevalent used in various fields, such as the healthcare system. While in such a scenario, sensitive data (e.g., personal electronic medical records) can be easily revealed, which incurs potential security challenges. Thus, Symmetric Searchable Encryption (SSE) has been extensively studied due to its capability of supporting efficient search on encrypted data. However, most SSE schemes require the data owner to share the complete key with query users and take malicious cloud servers out of consideration. Seeking to address these limitations, in this paper we propose a Verifiable Privacy-preserving data Search scheme with Limited key-disclosure (VPSL) for cloud-assisted Internet of Things. VPSL first designs a trapdoor generation protocol for obtaining a trapdoor with disclosing limited key information and without revealing plaintext query points to others. Then, VPSL provides an efficient result verification and search processing by employing the Merkle hash tree structure and k-means clustering technique, respectively. VPSL is secure against the level-2 attack. Finally, an enhanced VPSL (called VPSL+) resisting the level-3 attack is constructed by introducing the random splitting technique. Empirical experiments demonstrate the accuracy and efficiency of VPSL or VPSL+ using real-world datasets.

In cryptography,encryptionis the process of encoding information. This process converts the original representation of the information, known as plaintext, into an alternative form known as cipher text. Ideally, only authorized parties can decipher a cipher text back to plaintext and access the original information. Encryption does not itself prevent interference but denies the intelligible content to a would-be interceptor. AES is based on a design principle known as asubstitution–permutation network, and is efficient in both software and hardware.Unlike its predecessor DES, AES does not use aFeistel network. AES is a variant of Rijndael, with a fixedblock sizeof 128bits, and akey sizeof 128, 192, or 256 bits. By contrast, Rijndaelper seis specified with block and key sizes that may be any multiple of 32 bits, with a minimum of 128 and a maximum of 256 bits. In this research, a method has been suggested using the encryption algorithm multiple and serially since it was used4) -AES(implemented serially.The proposed algorithm is faster because it encrypts 64 bytes together. It encrypts all kinds of data and the number of files that are encrypted (2048) file and in one as it is possible to encrypt several files or one file at the same time. The performance of this technique has been done by computer using mathlab package.

Cloud computing enables enterprises and individu-1 als to outsource and share their data. This way, cloud computing 2 eliminates the heavy workload of local information infrastruc-3 ture. Attribute-based encryption has become a promising solution 4 for encrypted data access control in clouds due to the ability 5 to achieve one-to-many encrypted data sharing. Revocation is a 6 critical requirement for encrypted data access control systems. 7 After outsourcing the encrypted attribute-based ciphertext to the 8 cloud, the data owner may want to revoke some recipients that 9 were authorized previously, which means that the outsourced 10 attribute-based ciphertext needs to be updated to a new one 11 that is under the revoked policy. The integrity issue arises when 12 the revocation is executed. When a new ciphertext with the 13 revoked access policy is generated by the cloud server, the data 14 recipient cannot be sure that the newly generated ciphertext 15 guarantees to be decrypted to the same plaintext as the originally 16 encrypted data, since the cloud server is provided by a third 17 party, which is not fully trusted. In this paper, we consider 18 a new security requirement for the revocable attribute-based 19 encryption schemes: integrity. We introduce a formal definition 20 and security model for the revocable attribute-based encryption 21 with data integrity protection (RABE-DI). Then, we propose 22 a concrete RABE-DI scheme and prove its confidentiality and 23 integrity under the defined security model. Finally, we present 24 an implementation result and provide performance evaluation 25 which shows that our scheme is efficient and practical. 26

A previously unknown form of compromising emanations has been discovered. LED status indicators on data communication equipment, under certain conditions, are shown to carry a modulated optical signal that is significantly correlated with information being processed by the device. Physical access is not required; the attacker gains access to all data going through the device, including plaintext in the case of data encryption systems. Experiments show that it is possible to intercept data under realistic conditions at a considerable distance. Many different sorts of devices, including modems and Internet Protocol routers, were found to be vulnerable. A taxonomy of compromising optical emanations is developed, and design changes are described that will successfully block this kind of "Optical TEMPEST" attack., 26 pages, 11 figures

The signcryption protocols supporting the equality test are only for a single system rather than a flexible heterogeneous environment of wireless body area networks (WBANs). In this article, this problem is efficiently addressed through a proposed heterogeneous signcryption scheme from identity-based cryptosystem (IBC) to public key infrastructure (PKI) with an equality test (HSCIP-ET) for WBANs. Our scheme allows the sensors planted or worn by a user in the IBC system to signcrypt sensitive data using the public key of the management center in the PKI system, and then uploading it to the cloud server. Subsequently, the equality test can be executed by the cloud server on diverse ciphertexts to determine whether they contain the identical plaintext and return the corresponding result after receiving a request from an application provider. Furthermore, a rigorous analysis and an experimental comparison demonstrate the security and efficiency of the HSCIP-ET approach, respectively.

Medical time series data analytics based on dynamic time warping (DTW) greatly benefits modern medical research. Driven by the distributed nature of medical data, the collaboration of multiple healthcare institutions is usually necessary for a sound medical conclusion. Among others, a typical use case is disease screening for public health, where multiple healthcare institutions wish to collaboratively detect over their joint datasets the patients whose medical records have similar features to the given query samples. However, sharing the medical data faces critical privacy obstacles with the increasingly strict legal regulations on data privacy. In this paper, we present the design of a novel system enabling privacy-preserving DTW-based analytics on distributed medical time series datasets. Our system is built from a delicate synergy of techniques from both cryptography and data mining domains, where the key idea is to leverage observations on the advancements in plaintext DTW analytics (e.g., clustering and pruning) to facilitate the scalable computation in the ciphertext domain, through our tailored security design. Extensive experiments over real medical time series datasets demonstrate the promising performance of our system, e.g., our system is able to process a secure DTW query computation over 15K time series sequences in 34 minutes.