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With the widespread prevalence of smart devices, mobile crowdsensing (MCS) becomes a new trend to encourage mobile nodes to participate in cooperative data collection in various Internet of Things (IoT) applications. In location-dependent MCS, location information of mobile nodes is collected and analyzed by service provider to assist in task allocation. If the service provider is not fully trusted, mobile nodes privacy is leaked and accessed by unauthorized parties. How to preserve privacy while maintaining task allocation accuracy and efficiency becomes challenging. To this end, we propose a learning-based mechanism that involves two parts: 1) privacy-preserving task release and task allocation; 2) accurate and efficient task allocation. In the first part, we design a location-based symmetric key generator, which enables two parties to self-generate a symmetric key without depending on fully trusted authorities. By utilizing this key generator and Proxy Re-encryption, we propose a privacy preserving protocol to protect location information in task release and task allocation. In the second part, we design a reinforcement learning based task allocation algorithm to optimize the winners selection, which obtains high accuracy and efficiency. Performance analysis reveals that our proposed mechanism achieves accurate and efficient task allocation while preserving privacy in location-dependent MCS.

With the growth of the Internet of Vehicles (IoV) in Intelligent Autonomous Transport Systems (IATS), a huge volume of data is exchanged between vehicles in these newly developed infrastructures. As a result, the requirements of securing data exchange between vehicles, autonomous or otherwise, have also increased tremendously. Securing data transfer and keeping a record of each transaction becomes a necessity in IoV/IATS. In this paper, we propose some optimized security algorithms using symmetric encryption for secure multimedia data transfer between vehicles. The main feature of these optimized algorithms is that they use a lower amount of data to generate fingerprints. The algorithms convert approximately 3.7 x 10⁵ samples of data into 3600 samples to generate the fingerprint. Fast Fourier Transform (FFT) is used to fetch the highest three peak values of the signal in the frequency domain. A centralized server authenticates the data transfer by comparing the HASH of the fingerprints and also keeps the transaction record. Through experimental analysis, the performance of proposed algorithms is confirmed by achieving reduced size samples to generate fingerprints and their authentication at the server-side.

We study the problem of multi-user dynamic searchable symmetric encryption (DMUSSE) where a data owner stores its encrypted documents on an untrusted remote server and wishes to selectively allow multiple users to access them by issuing keyword search queries. Specifically, we consider the case where some of the users may be corrupted and colluding with the server to extract additional information about the dataset (beyond what they have access to). We provide the first formal security definition for the dynamic setting as well as forward and backward privacy definitions. We then propose SE, the first provably secure DMUSSE scheme and instantiate it in two versions, one based on oblivious data structures and one based on update queues, with different performance trade-offs. Furthermore, we extend SE to support verifiability of results. To achieve this, users need a secure digest initially computed by the data owner and changed after every update. We efficiently accommodate this, without relying on a trusted third party, by adopting a blockchain-based approach for the digests dissemination and deploy our schemes over the permissioned Hyperledger Fabric blockchain. We prototype both versions and experimentally evaluate their practical performance, both as stand-alone systems and running on top of Hyperledger Fabric.

Over the past two decades, the effectiveness of Conflict-Driven Boolean Satisfiability (CDCL SAT) solutions in a range of applications such as verification, monitoring, safety and the AI has improved dramatically in relation to industrial problems. The availability of powerful general-purpose search tools such as the SAT solver have led many scientists to propose satellite methods for cryptanalysis such as havoc collision techniques and symmetric encryption schemes. One feature of all of the above suggested SAT cryptanalysis is that it is a black box in that the problem with encrypted cryptanalysis is encoded as an instance with SAT and a CDCL SAT solver is called upon to solve that instance. A limitation is that the encoding produced may be too large to solve efficiently by any modern solver. Perhaps more importantly, the solver is in no way trained or tailored for solving the particular instance. Finally, very little work has been done in the field of SAT-based cryptanalysis to exploit parallelism.

Searchable Symmetric Encryption (SSE), which enables users to search over encrypted data without decryption, has gained increasing attention from both academic and industrial fields. However, existing SSE schemes either have low search efficiency or cannot support multi-keyword search, dynamic updates, and result verification simultaneously. To solve these problems, we propose a Verifiable and Dynamic Multi-keyword Search (VDMS) scheme over encrypted data by using the bitmap and RSA accumulator, which provides multi-keyword search over encrypted data in an efficient, verifiable and updated way. The bitmap is used as a data structure to build the indexes, which improves the search efficiency and reduces the storage space of the indexes. The RSA accumulator and bitmap are combined to verify the correctness of results. Formal security analysis proves that our VDMS is adaptively secure against Chosen-Keyword Attacks (CKA), and empirical experiments using a real-world dataset demonstrate that our VDMS is efficient and feasible in practical applications.

The development of the Internet of things (IoT) has given birth to new applications and services. Accordingly, because the IoT application system collects a large amount of data containing sensitive information, there are also new challenges in data security and privacy preservation. To locate the medical Internet of things (mIoT), this paper proposes a multi-keyword searchable encryption scheme based on attributes supporting the data privacy preservation and integrity verification of the electronic health files stored on the IoT cloud platform on the basis of ensuring the application business functions of the mIoT. (1) To ensure data confidentiality and fine-grained search authorization, the attribute-based encryption mechanism is introduced to encrypt the symmetric key. Moreover, anonymous key generation tampers semi-Trusted Centre Authority's (CA) decryption of all ciphertexts of users and access policy is hidden to prevent access policy from leaking. (2) Convergence key is adopted to encrypt electronic health records (EHRs), thereby providing double verification of the correctness of the search results and partial decryption results. (3) A time division mechanism is also established to provide the access validity of shared EHRs. (4) Fixed length ciphertext and outsourcing decryption mechanisms are used to reduce the calculation on the user side, in which the majority of the decryption calculations are done by the cloud server. Formal proofs and performance evaluation show that the proposed scheme can achieve data security, keyword security, integrity verification, hidden policy and collusion resistance, and has high computational efficiency and search efficiency.

Searchable Symmetric Encryption (SSE) is a key tool for secure data processing. To date, most of the SSEs were studied alone, while an SSE supporting update operations over encrypted data remained a challenging problem due to various statistical attacks and multi-user environments. In this paper, we propose SeUpdate, the first SSE scheme that simultaneously achieves keyword search and controlled update over encrypted data, with flexible read (search) and write (update) access control policies among multiple users. In SeUpdate, users do not need to share secret keys and a single query enables one to efficiently search all his authorized data. We formally define a security model, and prove our scheme have both forward and backward security. We note that the write permission of an SSE is realized for the first time. We further extend the basic scheme with dynamic access policy update and support of a large number of files. We also implement SeUpdate and some related work. The theoretical and experimental analyses demonstrate our scheme and its extension are practical and efficient.

To ensure the security of images outsourced to the malicious cloud without affecting searchability on such outsourced (typically encrypted) images, one could use privacy-preserving Content-Based Image Retrieval (CBIR) primitive. However, conventional privacy-preserving CBIR schemes based on Searchable Symmetric Encryption (SSE) are not capable of supporting efficient fine-grained access control and result verification simultaneously. Therefore, in this paper, we propose a Verifiable Fine-grained encrypted Image Retrieval scheme in the Multi-owner multi-user settings (VFIRM). VFIRM first utilizes a novel polynomial-based access strategy to provide efficient fine-grained access control. Then, it employs the dual secure k-nearest neighbor technique to distribute distinct keys to different data owners and data users, and finally implements an adapted homomorphic MAC technique to check the correctness of search results. Our formal security analysis shows that VFIRM is non-adaptive semantic secure if the clients search key is generated randomly and keeps in secret. Our empirical experiments using two real-world datasets (i.e., Caltech101 and Corel5k) demonstrate the practicality of VFIRM.

As a useful cryptographic primitive, searchable symmetric encryption (SSE) has been intensively studied to achieve the secure and efficient retrieval of encrypted data. In order to process update operations, dynamic SSE schemes have been proposed. But recently, file-injection attack has threatened the security of traditional dynamic SSE protocols. Therefore, designing dynamic SSE schemes with forward privacy becomes a new demand to resist the above attack. Meanwhile, multi-client setting is another requirement in SSE techniques where multiple clients can be delegated and have access to the database. However, most of previous forward private schemes were constructed for single-client setting and cannot directly extended to multi-client environment efficiently. To solve the problem, we propose a forward private SSE scheme with support for multi-client in cloud computing. The proposed scheme is based on XOR-homomorphic function and involves two new data structures as private link and public search tree. Security proof demonstrates the proposed scheme can meet the desired secure features. We then conduct experimental evaluation of the proposed scheme and make comparison with related schemes. The result shows that the proposed scheme tends to have high efficiency.

Internet of Things (IoT) sensing capabilities are now available as a public service. This new model , called sensing as a service (S2aaS) , a llows data owners to sell and/or exchange data with consumers interested in large open markets. However, t he openness of the service industry makes the IoT-based S2aaS model more susceptible to malicious attacks. In this article, we propose a simple, efficient , a nd secure key agreement scheme for IoT-based S2aaS model. Users in the proposed system can securely and quickly access public services through a simple website r ather than a traditional smart card. To simulate a real S2aaS environment, the cloud is treated as an untrusted node in the proposed method, and not all channels are secure. The fuzzy extractor and elliptic-curve diffie–hellman algorithms are used in conjunction with symmetric encryption and hash functions to establish a secure key agreement and data exchange session. In critical and frequent intervals, heavy processes are avoided. The proposed scheme's security has been informally analyzed and formally proven using the Automated Validation of Internet Security Protocols and Applications tool. The results show that our scheme satisfies the security requirements.

Searchable symmetric encryption (SSE) enables a user to outsource a private dataset to a cloud server in encrypted form while retaining the ability to search over the encrypted outsourced data. The existing SSE schemes improve the search and safety performances from different perspectives. However, almost none of the existing SSE schemes considers the data distribution issues. We find that when the dataset is not distributed uniformly, the search quality based on the conventional methods decreases. Therefore, the existing SSE schemes cannot guarantee high search quality when faced with non-uniform datasets. In addition, most existing SSE solutions cannot hide the distribution of the query set. In this paper, we design a Secure similarity search over Encrypted Non-uniform and high-dimensional Datasets (SEND) with a novel way to enhance security. The basic idea is to combine SSE with locality-sensitive hashing (LSH). Unlike earlier schemes, SEND uses selective hashing, which has better performance for non-uniform datasets. Also, we present a novel approach to hide the distribution of the query set, which makes SEND more secure. Our experimental results indicate SEND achieves a high search quality of recall and precision, and it is proven secure against adaptively chosen query attacks in the standard model.

Forward privacy in existing searchable symmetric encryption approaches generally supports only keyword searches, rather than range searches. In addition, existing approaches that support range search over encrypted datasets have limitations associated with efficiency, accuracy, and security. Seeking to address these limitations, we formally propose the definition of the forward privacy for secure range searches. Also, we demonstrate how three widely-used cryptographic tools— order-preserving encryption (OPE), pseudorandom function, and one-time pad–can be leveraged to design an efficient, accurate, and forward secure (EAFS) searchable encryption scheme supporting range search in encrypted numerical databases. In the proposed EAFS scheme, a trapdoor only matches the last data record that satisfies the search range, and the other results are found iteratively using the previous result. The chain-like search and the embedded ciphertexts of OPE simultaneously guarantee its efficiency, forward privacy, and accuracy. We also use the simulation-based method to demonstrate that our scheme is secure. Then, we implement EAFS in Microsoft Azure and evaluate its performance. The evaluation findings demonstrate that our proposed scheme supports secure range search practically and efficiently.

The Industrial Internet of Things (IIoT), a typical Internet of Things (IoT) application, integrates the global industrial system with other advanced computing, analysis, and sensing technologies through Internet connectivity. Due to the limited storage and computing capacity of edge and IIoT devices, data sensed and collected by these devices are usually stored in the cloud. Encryption is commonly used to ensure privacy and confidentiality of IIoT data. However, the key used for data encryption and decryption is usually directly stored and managed by users or third-party organizations, which has security and privacy implications. To address this potential security and privacy risk, we propose a Shamir threshold cryptography scheme for IIoT data protection using blockchain: STCChain. Specifically, in our solution the edge gateway uses a symmetric key to encrypt the data uploaded by the IoT device and stores it in the cloud. The symmetric key is protected by a private key generated by the edge gateway. To prevent the loss of the private key and privacy leakage, we use a Shamir secret sharing algorithm to divide the private key, encrypt it, and publish it on the blockchain. We implement a prototype of STCChain using Xuperchain, and the results show that STCChain can effectively prevent attackers from stealing data as well as ensuring the security of the encryption key.

To achieve efficiently search and update on outsourced encrypted data, dynamic searchable symmetric encryption~(DSSE) was proposed by just leaking some well-defined leakages. Though small, many recent works show that an attacker can exploit these leakages to undermine the security of existing DSSE schemes. In particular, an attacker can exploit even seemingly harmless size pattern to perform severe attacks. Many exiting schemes resort to oblivious RAM~(ORAM) to hide search/access pattern; however, even such powerful cryptographic primitive cannot protect size pattern leakage. In this paper, we first show that size pattern can lead to more information leakages, which is not well studied or protected by existing schemes. We then extend the existing privacy notion for DSSE to capture the size pattern leakage, achieving a strong forward and backward privacy definition. Following the definition, we propose a new DSSE scheme Eurus. Eurus can eliminate search/access pattern by relying on a multi-server ORAM scheme, meanwhile reducing size pattern with reasonable efficiency. We show that Eurus can reduce leakage significantly with better efficiency, compared with state-of-the-art leakage reduction schemes.

Cloud storage becomes the priority for storing and sharing data for enterprise users. Encrypting prior to uploading data to the cloud is the best way to protect business secrets, however, it hinders the convenient operations on plaintexts, such as searching over the cloud data. In addition, employees in an enterprise have multiple layer structures and a higher layer employee should have the privilege to monitor the lower layer employees' data to check if these users violate the regulation without letting the employees be aware of. Public key encryption with keyword search (PEKS) is a well-known cryptographic primitive suitable for secure cloud storage, which supports keyword search without decryption in public key encryption settings. Unfortunately, there is no existing PEKS scheme supporting the monitoring function without authorization from the sender. To address this issue, we propose a variant of PEKS named Hierarchical Public Key Encryption with Keyword Search (HPEKS) and provide a semi-generic construction utilizing a public key tree (PKTree) and a PEKS scheme. To better suit for the enterprise secret data sharing, we build an advanced HPEKS scheme, named designated-tester decryptable hierarchical public key encryption with keyword search, which enjoys stronger security and integrates the public key and symmetric key.

Searchable symmetric encryption enables a cloud server to answer queries directly over encrypted data. Two key requirements are a strong security guarantee and a sub-linear search performance. The bucketization approach in the literature addresses these requirements at the expense of downloading false positives and requiring the local search at the client side. In this work, we propose a novel approach to meet these requirements while minimizing the client's work and communication cost. First, a relaxed notion of ciphertext indistinguishability on partitioned data is formalized, called class indistinguishability, which provides a level of ciphertext indistinguishability similar to that of bucketization but allows the server to perform search of relevant data and filter false positives. We present a construction for achieving these goals through a two-phase search algorithm. The first phase finds a candidate set through a sub-linear search. The second phase finds the exact query result using a linear search applied to the candidate set. The experiment results on large real-world data-sets show that our approach outperforms the state-of-the-art. This work focuses on the class of equality conjunction search, but it applies to the general class of Boolean queries of equalities because the latter can be reduced to several equality conjunction queries.

Smart grid depends on an advanced communication network to collect information from the power grid, and to disseminate control commands to the control devices. To safeguard the power grid, it is crucial to ensure information confidentiality in the communication networks. Quantum key distribution (QKD) protocols help in generating, and distributing secret keys between communication parties, and such secret keys are required in symmetric cryptography. The combination of QKD protocols, and symmetric cryptography are known to be unconditionally secure, which means information confidentiality can be guaranteed even against an eavesdropper, who has unlimited resources. This article provides a concise review of existing works on QKD protocols, and their applications in smart grid communications. Deploying QKD protocols in smart grid is challenging because distance between the control center, and control devices can be larger than the limits of existing protocols. Also, QKD protocols require an expensive quantum channel between each pair of sender, and receiver nodes, and there is large number of control devices with diverse capabilities in smart grid. We have classified existing works based on the challenges they have dealt with. Compared to the rich literature on QKD protocols in general, there are significantly fewer works in the specific context of smart grid. This can be an indication for opportunity to make a significant contribution. We have also identified a few research challenges that can be potential future works.

In this paper, a Phase Congruency based digital color image watermarking algorithm is proposed which provides a higher degree of robustness against attacks and excellent imperceptibility. Here, Phase Congruency has been used to detect the local feature regions of the host image and then the watermark has been infused into it using a new technique called ‘Adaptive α-β Blending’. An accurate Human Visual System modeling has been incorporated via Lifting Wavelet Transform to take the full advantage of perceptual watermarking. The coefficients of the α-β blending are selected adaptively based on the Phase Congruency feature map of the host image. Furthermore, the watermark is secured with a cryptographic algorithm called Arnold’s Cat Map to prohibit further eavesdropping. From rigorous testing, results indicate that our approach is robust against various geometric, non-geometric and combined attacks while maintaining a sublime imperceptibility.

A matching in a bipartite graph with parts X and Y is called envy-free if no unmatched vertex in X is a adjacent to a matched vertex in Y. Every perfect matching is envy-free, but envy-free matchings exist even when perfect matchings do not. We prove that every bipartite graph has a unique partition such that all envy-free matchings are contained in one of the partition sets. Using this structural theorem, we provide a polynomial-time algorithm for finding an envy-free matching of maximum cardinality. For edge-weighted bipartite graphs, we provide a polynomial-time algorithm for finding a maximum-cardinality envy-free matching of minimum total weight. We show how envy-free matchings can be used in various fair division problems with either continuous resources ("cakes") or discrete ones. In particular, we propose a symmetric algorithm for proportional cake-cutting, an algorithm for 1-out-of-(2n-2) maximin-share allocation of discrete goods, and an algorithm for 1-out-of-floor(2n/3) maximin-share allocation of discrete bads among n agents., Comment: Appeared in Information Sciences, 587:164--187. But during the production, the main theorem text was deleted. The arXiv version is the correct one

Dynamic searchable symmetric encryption (DSSE) allows a client to query or update an outsourced encrypted database. Range queries are commonly needed. Previous range-searchable schemes either do not support updates natively (SIGMOD’16) or use file indexes of many long bit-vectors for distinct keywords, which only support toggling updates via homomorphically flipping the presence bit. (ESORICS’18). We propose a generic upgrade of any (inverted-index) DSSE to support range queries (a.k.a. range DSSE), without homomorphic encryption, and a specific instantiation with a new trade-off reducing client-side storage. Our schemes achieve forward security, an important property that mitigates file injection attacks. Moreover, we identify a variant of injection attacks against the first somewhat dynamic scheme (ESORICS’18). We also extend the definition of backward security to range DSSE and show that our schemes are compatible with a generic upgrade of backward security (CCS’17). We comprehensively analyze the computation and communication overheads, including implementation details of client-side index-related operations omitted by prior schemes. We show high empirical efficiency for million-scale databases over a million-scale keyword space.

International audience; In this paper, we propose an instantiation, called \textsf{Stanislas}, of a dedicated Self-Synchronizing Stream Cipher (SSSC) involving an automaton with finite input memory using non-triangular state transition functions. Previous existing SSSC are based on automata with shifts or triangular functions (T-functions) as state transition functions. Our algorithm Stanislas admits a matrix representation deduced from a general and systematic methodology called Linear Parameter Varying (LPV). This particular representation comes from the automatic theory and from a special property of dynamical systems called flatness.

Cloud computing facilitates the storage and management of huge volumes of data. It offers flexibility for retrieving the data anytime and anywhere. In recent years, storing data onto the cloud achieved fame among corporations as well as private users. Although, the cloud is drawing a lot of attention still there are data security, privacy, reliability and interoperability concerns that need to be taken care. To deal with these issues, cloud data encryption comes to the rescue. Encrypting the data before uploading it onto the cloud prevents unauthorized users from accessing the data. A lot of encryption algorithms have been developed to secure data stored on the cloud. In this paper, a novel cryptographic technique has been presented that uses client-side data encryption for encrypting the data before uploading it onto the cloud. It is a multifold symmetric-key cryptography technique which is based upon DNA cryptography. Besides presenting the detailed design of our approach, we have compared it with the existing symmetric-key algorithms (DNA, AES, DES and Blowfish). The experimental results illustrate that our proposed algorithm outperforms these traditional algorithms in terms of ciphertext size, encryption time and throughput. Hence, the newly proposed technique is more efficient and offers better performance.

Due to the high demands of searchability over encrypted data, searchable encryption (SE) has recently received considerable attention and been widely suggested in encrypted cloud storage. Typically, the cloud server is assumed to be honestbut- curious in most SE-based cloud storage systems, i.e., the cloud server should follow the protocol to return valid and complete search results to users. However, this trust assumption is not always true due to some unanticipated situations, such as misconfigurations and malfunctions. Therefore, the function of verifiability of search results becomes crucial for the success of SE-based cloud storage systems. For this reason, many verifiable SE schemes have been proposed; however, they either fail to support query operators "OR", "AND", "*" and "?" simultaneously, or require many time-consuming operations. Aiming at addressing this problem, in this paper, we propose a new verifiable SE scheme for encrypted cloud storage. The proposed scheme is characterized by integrating various techniques, i.e., bitmap index, radix tree, format preserving encryption, keyedhash message authentication code and symmetric key encryption, for achieving efficient and verifiable conjunctive and fuzzy queries over encrypted data in the cloud. Detailed security analysis shows that our proposed scheme holds the confidentiality of data and verifiability of search results at the same time. In addition, extensive experiments are conducted, and the results demonstrate our proposed scheme is efficient and suitable for users to retrieve their data from the cloud to their mobile devices.

Traditional encryption is based on secrecy provided by secret-key. But this leads to generation of same cipher text when the encryption scheme is applied to same plaintext with same key. Thus, replay of messages can be effortlessly identified by an adversary which can be a weak link in any communication. Probabilistic encryption is an approach to overcome this weakness where different cipher texts are generated each time same plaintext is encrypted using the same key. Extending the probabilistic approach, which is generally employed in asymmetric encryption, this paper proposes a new chaos-based probabilistic symmetric encryption scheme with customizable block-size suitable for image encryption. It employs a Random Bits Insertion phase followed by four rounds of two-staged diffusion involving simple XOR (exclusive-OR) operation making it computationally efficient. Random Bits Insertion makes the scheme probabilistic. This phase also helps in increasing entropy and making intensity distribution more uniform in cipher. The generated cipher text is twice the size of plain text. An increase in cipher text space is inevitable for probabilistic encryption and it provides an advantage as the apparent message space for the attacker is increased. The observations show that the scheme offers high strength to resist statistical and cryptanalytic attacks.

Cloud computing as a promising computing paradigm is increasingly utilized as potential hosts for users' massive dataset. Since the cloud service provider (CSP) is outside the users' trusted domain, existing research suggests encrypting sensitive data before outsourcing and adopting Searchable Symmetric Encryption (SSE) to facilitate keyword-based searches over the ciphertexts. However, it remains a challenging task to design an effective SSE scheme that simultaneously supports sublinear search time, efficient update and verification, and on-demand information retrieval. To address this, we propose a Verifiable Dynamic Encryption with Ranked Search (VDERS) scheme that allows a user to perform top-K searches on a dynamic document collection and verify the correctness of the search results in a secure and efficient way. Specifically, we first provide a basic construction, VDERS0, where a ranked inverted index and a verifiable matrix are constructed to enable verifiable document insertion in top-K searches. Then, an advanced construction, VDERS*, is devised to further support document deletion with a reduced communication cost. Extensive experiments on real datasets demonstrate the efficiency and effectiveness of our VDERS scheme.

Due to its capabilities of searches and updates over the encrypted database, the dynamic searchable symmetric encryption (DSSE) has received considerable attention recently. To resist leakage abuse attacks, a secure DSSE scheme usually requires forward and backward privacy. However, the existing forward and backward private DSSE schemes either only support single keyword queries or require more interactions between the client and the server. In this paper, we first give a new leakage function for range queries, which is more complicated than the one for single keyword queries. Furthermore, we propose a concrete forward and backward private DSSE scheme by using a refined binary tree data structure. Finally, the detailed security analysis and extensive experiments demonstrate that our proposal is secure and efficient, respectively.

Health related information of an individual is very sensitive and demands a high level of security and privacy. Healthcare providers have the responsibility to ensure that patient information is secure and accessible only to authorized users. Healthcare systems are using biometrics since long for authentication and/or access control purposes. Biometrics can also be used for healthcare data security and privacy. This paper proposes an iris based cancelable biometric cryptosystem to securely store the healthcare data of patients on the smart card. It employs symmetric key cryptography to encrypt the healthcare data and store it on the smart card in encrypted form. We use the fuzzy commitment scheme to bind the secret encryption key with the cancelable iris template of the patient. Our proposed scheme provides user authentication as well as the decryption of healthcare data when needed by using the iris template of the owner of the healthcare smart card. The implementation results show that our proposed scheme provides better performance as compared to other schemes. It can generate an encryption key of a maximum of 252 bits from the input iris template with a false acceptance rate (FAR) of 0 and a false rejection rate (FRR) of 0.07. The generated key can be used for encrypting the health care data of patients using a symmetric encryption algorithm, e.g. Advance Encryption Standard (AES), International Data Encryption Algorithm (IDEA), Blowfish, etc. As compared to a conventional encryption system where the security of the system depends on keeping the key secret, our proposed scheme binds the encryption key with the iris - template of the patient impeccably without the need to store it securely. The security analysis demonstrates that it is not possible for an attacker to retrieve the secret key or healthcare data of the patient from the stolen healthcare card.

In cloud-based health monitoring services, support vector machine (SVM) classification techniques are often utilized by medical institutes to build medical decision models, which can be outsourced to a cloud server for producing medical decisions based on medical features from remote clients. In this article, we propose a verifiable and secure SVM classification scheme ( $\mathsf {VSSVMC}$ ) for cloud-based health monitoring services in a malicious setting, where the cloud server may return invalid decisions. By constructing verifiable indices, $\mathsf {VSSVMC}$ ensures the verifiability of medical decisions, which enables clients to detect whether the cloud server returns incorrect or incomplete medical decisions. Symmetric key encryption is leveraged to ensure the confidentiality of the medical decision model and medical data with computational efficiency. We give security and verifiability definitions and provide formal security and verifiability proofs for $\mathsf {VSSVMC}$ . Performance analyses show that $\mathsf {VSSVMC}$ is extremely efficient in terms of computation, communication, and storage. Experimental evaluations demonstrate that $\mathsf {VSSVMC}$ achieves microsecond-level execution time with kilobyte-level communication and storage overheads on the tested data set.

In order to improve the security of image information in the information age, we propose an image encryption scheme in this paper, which is achieved by using finite-time cluster synchronization of two-layer complex dynamic networks. Considering the cluster characteristics of nodes in complex networks and the time convergence of synchronization, the method of finite-time cluster synchronization, which plays an important role in information encryption/decryption, is investigated and the influence of stochastic disturbance is taken into consideration as well. A two-layer encryption system is proposed, in which the drive layer is used for encryption, and the response layer is used for decryption. The encryption process can be mainly divided into three steps: scrambling preprocessing, encryption function operation, and diffusion. The encryption scheme uses a symmetric encryption method, and both the encryption keys and the decryption keys are disposable and dynamic, which can increase the complexity and security of the keys. A detailed theoretical analysis for the capability of encryption scheme, which has the advantages of great cipher set, fast encryption and decryption speed, good encryption effect, is provided and the time for information encryption/decryption is controllable and predictable. The availability and practicability of the encryption scheme are verified by simulation results.

Blockchain was at the top of the 2016 Gartner hype cycle and has been integrated into business profiles by numerous start-ups. Since the emergence of blockchain through Bitcoin, studies have been conducted to increase blockchain applications for nonfinancial uses. A supply chain is a sector where blockchain is anticipated to have crucial applications. In a traditional supply chain, maintaining traceability and ownership remains a serious issue. In the supply chain, blockchain can increase trust, improve traceability, and eliminate the middle man. It makes the supply chain more transparent though, raising the privacy issue. In this paper, a new approach for transaction privacy is proposed by considering ownership and traceability. The proposed system retains the advantages of blockchain and centralised database server. Its novelty lies in achieving privacy by generating symmetric keys, employing product codes and current timestamps, and it uses asymmetric key elliptic curve cryptography for transaction validation and user identification. The proposed system allows product owners to trace the product and enables its transfer. It protects the supply chain from counterfeit products. The Hyperledger Sawtooth blockchain was used for experiments. Security and privacy analysis show that the proposed system can afford privacy without impinging on traceability and ownership. The results estimate that privacy incorporation introduces an overhead of 4.4%. In the experiment, the performance of the proposed system bettered the results of the existing techniques such as POMS and b_verify.

Symmetric cryptography is expected to be quantum safe when long‐term security is needed. Kuwakado and Morii gave a 3‐round quantum distinguisher of the Feistel cipher based on Simon's algorithm. However, the quantum distinguisher without considering the specific structure of the round function is not accurate enough. A new quantum cryptanalysis method for Feistel structure is studied here. It can make full use of the specific structure of the round function. The properties of Camellia round function and its linear transformation P are taken into account, and a 5‐round quantum distinguisher is proposed. Then, the authors follow a key‐recovery attack framework by Leander and May, that is, Grover‐meet‐Simon algorithm, and give a quantum key‐recovery attack on 7‐round Camellia in Q2 model with the time complexity of 224. It is the very first time that the specific structure of the round function is used to improve quantum attack on Camellia.

Quantum computing is a serious threat for contemporary cryptography and, in order to address this threat, key sizes used for symmetric cryptography should be doubled, most typically from 128 to 256 bits. The third-generation partnership project (3GPP), the standards organization for mobile communications, is currently in the process of adding support for 256-bit keys into future mobile standards for the purpose of confidentiality and integrity protection. The current standard defines three ciphers with 128-bit keys: AES, SNOW 3G, and ZUC. There are two competing stream ciphers for the replacement of the 128-bit SNOW 3G: a 256-bit variant of SNOW 3G and a new design SNOW-V. SNOW-V has superior performance in software platforms. In this article, we investigate the implementations of these ciphers on field-programmable gate arrays (FPGAs) for both confidentiality and integrity protection. We develop optimized architectures and introduce a new parallelization technique that applies to both ciphers and offers significant throughput improvements in particular when the ciphers are used in the integrity protection modes. Our results show that SNOW-V has a significant performance advantage over the 256-bit SNOW 3G also on FPGAs.

Searchable encryption has received a significant attention from the research community with various constructions being proposed, each achieving asymptotically optimal complexity for specific metrics (e.g., search, update). Despite their elegance, the recent attacks and deployment efforts have shown that the optimal asymptotic complexity might not always imply practical performance, especially if the application demands a high privacy. In this article, we introduce a novel Dynamic Searchable Symmetric Encryption (DSSE) framework called Incidence Matrix (IM)-DSSE, which achieves a high level of privacy, efficient search/update, and low client storage with actual deployments on real cloud settings. We harness an incidence matrix along with two hash tables to create an encrypted index, on which both search and update operations can be performed effectively with minimal information leakage. This simple set of data structures surprisingly offers a high level of DSSE security while achieving practical performance. Specifically, IM-DSSE achieves forward-privacy, backward-privacy and size-obliviousness simultaneously. We also create several DSSE variants, each offering different trade-offs that are suitable for different cloud applications and infrastructures. We fully implemented our framework and evaluated its performance on a real cloud system (Amazon EC2). We have released IM-DSSE as an open-source library for wide development and adaptation.

With the rapid development of the genomic sequencing technology, the cost of obtaining personal genomic data and analyzing it effectively has been gradually reduced, and the analysis and utilization of genomic data has gradually entered the public view, while the leakage of genomic data privacy has aroused the attention of researchers. The security of genomic data is not only related to the protection of personal privacy, but also related to the biological information security of the country. However, there is still no effective genomic data privacy protection scheme using Shangyong Mima(SM) algorithms. In this paper, we analyze the widely used genomic data file formats and design a large genomic data files encryption scheme based on the SM algorithms. Firstly, we design a key agreement protocol based on the SM2 asymmetric cryptography and use the SM3 hash function to guarantee the correctness of the key. Secondly, we used the SM4 symmetric cryptography to encrypt the genomic data by optimizing the packet processing of files, and improve the usability by assisting the computing platform with key management. Software implementation demonstrates that the scheme can be applied to securely transmit the genomic data in the network environment and provide an encryption method based on SM algorithms for protecting the privacy of genomic data.

Security in quantum dot cellular automata (SQCA) is an emerging trend in the arena of nanotechnology. Its features are high computing speed, smaller size and low power depletion in comparison to transistor oriented technology. This article proposes a nanoscale Crypto-Codec circuit which produces cipher texts in order to obtain security during nanocommunication. Single layer crossing is used to design the Crypto-Codec circuit to minimize the fabrication difficulty. In this article higher attention is given to obtain high level of security by providing two layers of security using two different keys at two levels. Cryptographic communication architecture is proposed employing Crypto-Codecs and 2 × 2 Crossbar switch for authentic information sharing. The result resembles with the theoretical values, which endorse the precision of the proposed circuit. Circuit density of the design is calculated to prove that QCA circuits possess higher devise density in comparison to CMOS circuit. Stuck-at-fault analysis is performed to obtain faultless design. The proposed circuit is designed using QCA designer tool.

Image encryption is an efficient technique to protect the contents of an image. However, many existing image encryption algorithms have low efficiency and are weak to resist many commonly used security attacks such as the chosen-plaintext attack. To address these issues, in this paper, we propose a new image encryption scheme using value-differencing transformation (VDT) and modified ZigZag transformation. First, we propose a new transform called VDT. It can split a plain image into four subbands based on value-differencing and this can greatly help to diffuse the image pixels. Second, we develop a modified ZigZag transformation that can separate the image pixels with a much higher efficiency. Besides, to improve the ability to defense the chosen-plaintext attack, we extract part information of plain image as parameters to encrypt the image. Notice that these information don’t need when decrypting the image so that the proposed image encryption scheme is a symmetric key encryption algorithm. Simulation results and security analysis show that the proposed image encryption scheme can encrypt different kinds of plain images into unrecognized cipher images with a high security level, and it can outperform several existing image encryption schemes.

In case of global roaming services, user authentication plays an important role in order to prevent any unauthorized user from accessing services. Preserving anonymity and unlinkability are also crucial to ensure user untraceability over public channel. However, achieving user authenticity and untraceability are not sufficient to guarantee a secure communication. Several active and passive attacks may breach the system security as the mode of communication is considered to be wireless. Hence, requiring a well-designed protocol to resist these vulnerabilities. In this article, we put forward a secure and efficient authentication protocol with user untraceability for global roaming services. The proposed protocol utilizes low-cost cryptographic primitives such as symmetric key encryption/decryption and one-way hash function. We use dynamic keys (rather than long-term keys) to ensure forward/backward secrecy of the session key. The use of dynamic pseudonym ensures user anonymity and unlinkability over public channel. In addition, there is no need to re-synchronize the peers in case of desynchronization attack. The security validation of the proposed protocol is done both formally and informally to ensure robustness of the protocol under various active and passive attacks. Finally, we compare our protocol with some recently proposed approaches in terms of various security and design parameters to ensure its efficiency for low-power applications of global roaming services.

Use of Internet-of-Things (IoT)-based wireless applications has been exponentially increased nowadays and likely to accelerate in near future. Thus, a large volume of traffic needs to be managed at the application server. In such scenario, the traditional single-server architecture shows serious performance bottleneck and needs to be replaced by multiple servers. In addition, several security and design vulnerabilities may arise while accessing application data through various resource-constraint mobile devices. Thus, ensuring entity authentication, application data confidentiality and energy-efficient computations are essential. In this article, we introduce a group key-based lightweight Mutual Authentication and Key Agreement (MAKA) protocol for multi-server environment. The proposed protocol is designed using low-cost cryptographic primitives (such as hash function and symmetric key encryption/decryption) to address energy-efficiency requirements of the resource-constraint mobile devices. It reduces computational burden of the registration center by distributing the traffic load into a group of servers. Additionally, registration center needs not to maintain one-to-one communication with its users whenever a new server is added to the system. The protocol achieves various security and design properties which are verified both formally and informally. Finally, we compare our protocol with others to show its applicability in real-life implementations.

This article discusses one of the ways to generate a common cryptographic key using synchronized artificial neural networks. This option is based on a combined method of forming a cryptographic key [1]. The proposed combined formation consists of two stages: the formation of partially coinciding binary sequences using synchronized artificial neural networks and the elimination of mismatched bits by open comparison of the parities of bit pairs. The purpose of this article is to increase the cryptographic strength of this method in relation to a cryptanalyst. In this regard, it is proposed to prematurely interrupt the synchronization process at the first stage of the combined method and make changes to the resulting binary sequence by randomly inverting a certain number of bits. To confirm the quality of this method, possible attacks are considered and the scale of enumeration of possible values is illustrated. The results obtained showed that the combined method of forming a cryptographic key with a secret modification of the synchronization results of artificial neural networks, proposed in this article, provides its high cryptographic strength, commensurate with the cryptographic strength of modern symmetric encryption algorithms, with a relatively simple implementation.

Dynamic Searchable Symmetric Encryption (DSSE) has gained increasing popularity as it enables users to perform both file updates and ciphertext retrieval over encrypted data . However, existing DSSE schemes still lead to privacy leakage ( e.g., forward and backward privacy) in the dynamic setting. Some forward and backward secure DSSE schemes have been proposed, but still cannot support the keyword shielding flexibly. To solve this challenging issue, we propose a Forward and Backward Authorized Keyword Search (FB-AKS) scheme with recoverable keyword shielding by using trapdoor permutations and puncturable encryption in this paper. Compared with existing forward and backward private schemes, FB-AKS achieves keyword authorization flexibly ( e.g., keyword shielding, keyword un-shielding). The formal security analysis proves that FB-AKS achieves forward and backward security. And extensive experiments demonstrate that FB-AKS has less computation and storage overheads .

Wireless sensor networks (WSN) allow to exchange information and to take immediate and remote actions in natural, industrial, military or domestic environment systems. These networks are vulnerable to cyber-attacks, hence, they are vulnerable to being intercepted, interrupted or modified. However, for the last twenty years, the amount of information exchanged through communication networks around the world has considerably increased and thus its vulnerability. As a result, encryption algorithms are fundamental to protect information. In this context, security, performance and energy consumption become a paramount design factor for an engineer when designing and implementing WSNs. It is not an easy task to reach an optimal balance between these factors. In this paper, we evaluate three well-known symmetric encryption algorithms in an embedded development platform: the ARDUINO MEGA 2560. Our experiment measures the algorithms encryption average execution time and energy consumption. Additionally, we measure the impact of the channels of a small wireless sensor network with two nodes. The evaluation demonstrates the feasibility of implementing cryptographic algorithms in devices with limited resources such as memory, computing power and life span (energy consumption). Furthermore, the low impact on the network channels when comparing unencrypted communication vs encrypted communication evidence the potential of symmetric encryption algorithms.

As more data from Industrial Internet of Things (IIoT) devices are been outsourced to the cloud, the need to ensure/achieve data privacy will be increasingly pressing. Searchable public-key encryption is a promising tool to achieve data privacy without sacrificing data usability. However, most existing searchable public-key encryption schemes are either inefficient (e.g., expensive in terms of encryption and searching keywords) or lack the required (security) features such as forward privacy. To address these limitations, we propose a lightweight searchable public-key encryption with forward privacy. Specifically, the scheme allows us to achieve forward privacy in a public-key cryptography (i.e., asymmetric) setting, and has the same search performance as a number of practical searchable symmetric encryption schemes. The formal security analysis shows that the proposed scheme is chosen-keyword attack resilient and achieves forward privacy. Finally, the experimental results on a real-world dataset demonstrate that the proposed scheme is highly efficient and scalable in IIoT applications.

In 2020 E. Sakalauskas with coauthors published a paper defining perfectly secure Shannon cipher based on matrix power function, proposing effective parallelization, and ensuring no need for multiple rounds encrypting one data block [1]. In this paper we present computational results with the avalanche effect and bit independence criterion (BIC). These criteria are important when describing the rate of confusion of bits in the ciphertext. It was observed that increasing matrix order and group size enhance BIC and avalanche effect results converging to the desired values. Based on the outputs it is possible to pick appropriate parameters satisfying security needs and available memory in a device where appropriate keys are going to be stored.

This paper presents a GPU-accelerated implementation of an image encryption algorithm. The algorithm uses the concepts of a modified XOR cipher to encrypt and decrypt the images, with an encryption pad, generated using the shared secret key and some initialization vectors. It uses a genetically optimized pseudo-random generator that outputs a stream of random bytes of the specified length. The proposed algorithm is subjected to a number of theoretical, experimental, and mathematical analyses, to examine its performance and security against a number of possible attacks, using the following metrics - histogram analysis, correlation analysis, information entropy analysis, NPCR and UACI. The performance analysis carried out shows an average speedup-ratio of 3.489 for encryption, and 4.055 for decryption operation, between the serial and parallel implementations using GPU. The algorithm aims to provide better performance benchmarks, which can significantly improve the experience in the relevant use-cases, like real-time media applications.

The International Electrotechnical Commission (IEC) 62351-6 standard prescribes provisions to secure IEC 61850-8-1 generic object-oriented substation events (GOOSE) communications from cyber threats. The GOOSE authentication schemes recommended by IEC 62351-6 have shortcomings, such as long authentication-value computation times, large signature lengths, the usage of symmetric keys, and susceptibility to quantum computer attacks. To overcome these, this paper proposes the usage of the rainbow signature scheme (RSS), a quantum cryptographic method to secure GOOSE messages. The RSS offers fast signature generation and verification using asymmetric keys, making it very attractive to meet the time-latency and security requirements of the GOOSE protocol. The adaptation of the RSS cryptography method for its application to the GOOSE protocol is presented in this paper. The algorithms for key generation, signature computation and message verification are discussed in detail. A first-of-its-kind C library that incorporates security features within the GOOSE protocol in compliance with the IEC 62351-6–stipulated format, is developed. The superior features of the RSS in comparison with the other IEC 62351-6 security schemes are demonstrated.

The smart grid emerges as a new era of the electronic power grid. It integrates advanced sensing technologies, communications, and controlling methods that tell how electricity travels from different generation points to consumers. In order to fulfill customers’ satisfaction and two way communications, a huge number of smart meters are deployed in different countries for real-time consumption and presentation of the rigorous energy usage. The privacy of industrial ecosystems may require greater attention while considering minimum network load, lower computational resources, better energy efficiency, and accuracy of data. Different research works have been done to tackle customers’ privacy, but at the cost of using more computational resources, communication overhead, and hiring of a trusting third party. In this article, we have proposed a symmetric encryption scheme for industrial ecosystems in the Internet of Thing (IoT) environment. The performance evaluation and security analysis demonstrate successful user privacy and integrity with lower computational resources and communication overhead.