Cross-chain interaction plays a crucial role in enhancing asset circulation and data sharing across diverse blockchain systems. Cross-chain identity authentication is the primary pre-requisite of cross-chain security interaction. However, existing cross-chain identity authentication protocol generally has issues such as insufficient decentralization, poor universality, and low authentication efficiency. These issues compromise the reliability of cross-chain interactions. Based on group signature and zero-knowledge proof, this paper proposes a cross-chain identity authentication protocol to address these concerns. The protocol employs Decentralized Identifiers(DIDs) as the global identity identifier of users, utilizes zero-knowledge proof to provide privacy for the verification of users' identities when joining the group, and then constructs the users' transaction signatures through group signatures to hide the users' identities. This approach not only reduces the risk of users' privacy leakage but also facilitates mutual recognition of identities among cross-chain systems. Finally, the security analysis and experimental analysis shows the correctness and efficiency of the proposed scheme.

In Wireless Medical Sensor Networks (WMSNs) wearable or implantable sensors are used to collect vital body parameters, allowing remote monitoring and advanced predictive and preventive healthcare. This involves transmitting patients’ physiological data, which are sensitive and should be confidential, over the network. Thus, ensuring the security and privacy of these data is one of the most important prerequisites for the successful development of healthcare systems based on WMSN. In this regard, reliable authentication protocols designed for this specific scenario are needed. In this paper, we propose the most efficient attacks to date on the widely referenced lightweight authentication protocols for WMSNs - Wang et al.’s protocol (IEEE Internet of Things Journal, 9(11), 2022, doi: 10.1109/JIOT.2021.3117762). This protocol relies on blockchain and smart contracts to address the issue of centralization, and on Physically Unclonable Functions (PUFs) to ensure advanced physical layer security. Our attacks exploit the protocol’s vulnerabilities that stem from an inadequate use of the underlying blockchain component, unlike the previous attacks which require challenging conditions to meet, i.e. physical access to users’ mobile devices and specialized power analysis techniques. We introduce new attack scenarios and prove that Wang et al.’s protocol is vulnerable to impersonation, tracing, message replay and session key disclosure. We validate these vulnerabilities using the ProVerif tool, thereby confirming the feasibility of the attack scenarios and refuting Wang et al.’s claims regarding the protocol’s security properties. In addition, we identify and discuss other design weaknesses in Wang et al.’s proposal that further undermine its overall security and practical applicability. Finally, we revisit the feasibility of previously published attacks on Wang et al.’s protocol.

Secure neural network inference provides privacy guarantees for both the client and the server, and is an integral approach in Machine Learning as a Service Setting (MLaaS). However, the multilayer structure in the neural network introduces frequent activation function calculations, which causes large overhead. Most of the prior secure inference systems focused on designing cryptographic protocols to improve computational efficiency, but high computing and communication overhead are still bottlenecks in practicality. In this work, we refocus on the potential of shallow neural networks and propose a model with only one trainable layer to reduce the required computation. Our main contributions are in three-fold: 1) introduce training-free weights and formally prove their contribution in the model expressivity; 2) design the Self Enhanced Module that is more suitable for shallow models as an alternative for the activation function; and 3) propose a linear layer with multiscale and normalization property, named Nested & Norm Conv. We conduct extensive experiments on visual datasets and the results demonstrate the proposed single-layer trainable model holds promise as a viable platform for secure inference in practical applications.

With the development of the Industrial Internet of Things (IIoT), data sharing provides an important driving force for the innovative development of industry. By analysis and mining of massive data, enterprises can find new market opportunities and develop more competitive products and services. At the same time, frequent data breaches show that data faces serious security challenges in IIoT. Therefore, the security and privacy of data in IIoT must be ensured by means of identity authentication and access control technology. Traditional identity authentication methods usually only consider one-way authentication and have inherent security deficiencies that are insufficient to meet the needs of current IIoT systems. This paper proposes a blockchain-based mutual authentication scheme that replaces the traditional third-party intermediary with blockchain technology, to enhance the transparency and credibility of the identity authentication process. Moreover, the scheme combines attribute-based encryption with linkable ring signature to achieve both the protection of user identity privacy and identity tracking. Experimental results indicate that the proposed scheme demonstrates good scalability and usability.

This study considers a class of randomised encryption techniques, where the encrypted data suffers from noise through transmission over a communication channel. It focuses on the encoding–encryption framework, where the data is first encoded using error correction coding for reliability, then encrypted with a stream cipher. A dedicated homophonic encoder is added to enhance the protection of the stream cipher key, on which relies the security of all the system transmissions. This study presents a security evaluation of such systems in a chosen plaintext attack scenario, which shows that the computational complexity security is lower bounded by the related LPN (learning from parity with noise) complexity in both the average and worst cases. This gives guidelines to construct a dedicated homophonic encoder which maximises the complexity of the underlying LPN problem for a given encoding overhead. A generic homophonic coding strategy that fulfils the proposed design criteria is then given, which thus both enhances security while minimising the induced overhead. Finally, a comparison of encryption schemes based on the LPN problem with and without homophonic coding is considered.

This paper proposes an improvement of certain encryption approaches designed based on hardness of the learning from parity with noise (LPN) problem. The proposal employs a dedicated homophonic coding and randomness resulting in a harder underlying LPN problem in comparison with the related source schemes without homophonic coding. It is pointed out that the proposed scheme provides a high security, and consideration of the implementation complexity shows that it is low (regarding the both: time and space), assuming that the appropriate efficient linear block codes are employed. The proposed encryption is compared with the related recently reported ones and it is pointed out that the novel scheme can provide an enhanced security or reduced implementation complexity and communications overhead.

A novel technique for cryptanalysis of the stream cipher Grain-v1 is given. In a particular setting, the algorithms proposed in this study provide recovery of an internal state of Grain-v1 with the expected time complexity of only 254 table look-up operations employing a memory of dimension ∼270, assuming availability of 234 keystream sequences each of length 238 generated for different initial values, and the pre-processing time complexity of ∼288. These figures appear as significantly better in comparison with the previously reported ones. The proposed approach for cryptanalysis primarily depends on the order of normality of the employed Boolean function in Grain-v1. Accordingly, in addition to the security evaluation insights of Grain-v1, the results of this study are also an evidence of the cryptographic significance of the normality criteria of Boolean functions.

A Boolean function is k-normal if it is constant on a k-dimensional flat of its domain. This paper demonstrates that k-normality of a Boolean function can be exploited to mount a dedicated algebraic attack on a stream cipher of the nonlinear filter generator type, which employs a k-normal Boolean function as its filter function. The cryptanalysis is based on the possibility for pre-computing a table of the state-key stream pairs via solving certain system of algebraic equations as a consequence of the employed k-normal Boolean function. This pre-computed table is the main origin for mounting the cryptanalysis and it is independent of a the sample for cryptanalysis and the secret key employed for generating the sample.

An authentication protocol is proposed which originates from the elements of the authentication protocols belonging to the HB-family and the protocols based on employment of pseudorandom number generators. Desired features of the proposed protocol have been achieved via combining the pseudorandomnes generated by a compact keystream generator, randomness and dedicated homophonic and error-correction coding. It is shown that implementation complexity of the protocol is low. Security of the proposed protocol is considered from an information-theoretic and a computational-complexity points of view assuming the passive attacking The performed security evaluation yields an indication for a conjecture on the security within certain active attacking scenarios as well.

Following some of the recently reported results, an approach for design of stream ciphers has been considered which is based on joint employment of pseudorandomness, randomness and dedicated wire-tap channel and error correction coding. The wire-tap channel coding controlled by the randomness, provides that an attacker faces not only the traditional problems of cryptanalysis but also the problem of decoding without the secret key which appears as complex as the exhaustive search over the possible secret keys. Security evaluation has been performed based on the algebraic representation of the proposed stream cipher. The given security evaluation has addressed hardness of the algebraic recovering of the secret key in the CPA scenario. It is shown that the secret key recovery is as hard as the LPNϵproblem where ϵ = (1-(1-2p)(m-ℓ)/2)/2 and m, ℓ and p are the stream cipher parameters.

In this paper, the gains achievable by proper decimation (or puncturing) of the received sample for fast correlation attack are investigated. In particular, the instances in which such an approach is interesting are clearly identified.

In this paper, a general framework which enables to compare previously proposed block decoding approaches for the fast correlation attack is developed. All attacks are based on decoding using a set of parity check sums of an underlying linear code. The purpose of this paper is twofold:to provide a simple close form estimate about the number of check sums of a particular structure necessary for the corresponding attack to succeed;

The problem of minimizing the amount of secret information (secret bits) required for certain key management schemes related to data access control techniques is addressed. Particularly note that the importance of the secret storage minimization originates from the fact that this storage should be read-proof and tamper-proof one. This paper points out to a novel approach for minimization of the secret storage dimension and compare this approach with a straightforward one based on establishing a virtual secret storage employing data encryption. The novel approach yields: (i) provable security; (ii) it is not based on storing the encrypted data into a public storage, and (iii) it requires lower processing complexity. The proposed approach yields the secret storage minimization via exchange of a secret storage to a public one based on the efficient one-way mapping of the secret bits yielding significant additional flexibility and reduction of the secret storage overhead at the user's side as an appropriate trade-off with the required public storage and processing complexity. The overheads of the proposed technique are compared with the related previously reported ones, and advantages of the novel approach are pointed out.

In this paper, a general framework which enables to compare previously proposed approaches for the fast correlation attacks is developed. All attacks are based on decoding using a set of parity check sums of an underlying linear code. The purpose of this paper is two-fold: (a) to provide a simple close form estimate about the number of check sums of a particular structure necessary for the corresponding attack to succeed; (b) to illustrate how such estimates are useful in minimizing the computational complexity of each attack considered, and consequently, in establishing a unified framework for comparison

In order to obtain an appropriate, high level of security, a number of architectural elements for secure downloading of software to a software defined radio (SDR) terminal have been pointed out. They include four different cryptographic techniques and employment of tamper resistant hardware. The cryptographic techniques employed are: (a) a secret key encryption technique; (b) a public key encryption technique; (c) a technique for cryptographic hashing and (d) a technique for digital signature. Particularly, a protocol for exchanging cryptographic components in an automatic manner without any assistance from the user, is proposed. Implementation characteristics of certain cryptographic components are also discussed.

Some arguments more are presented to illustrate a need for careful security evaluation of the encryption algorithms for possible use in the wireless networks. Particularly, the security evaluation of a previously proposed fast encryption for multimedia FEA-M is presented. It is shown that the effective secret key size is much smaller than its nominal one, which is a very undesirable and potentially dangerous characteristic.

A novel analytical approach to performance evaluation of soft-decoding algorithms for binary linear block codes based on probabilistic iterative error correction is presented. A convergence condition establishing the critical noise rate below which the expected bit-error probability tends to zero is theoretically derived. It explains the capability of iterative probabilistic decoding of binary linear block codes with sparse parity-check matrices to correct, with probability close to one, error patterns with the number of errors (far) beyond half the code minimum distance. Systematic experiments conducted on truncated simplex codes seem to agree well with the convergence condition. The method may also be interesting for the theoretical analysis of the so-called turbo codes.

Two simplified versions of the belief propagation algorithm for fast iterative decoding of low-density parity check codes on the additive white Gaussian noise channel are proposed. Both versions are implemented with real additions only, which greatly simplifies the decoding complexity of belief propagation in which products of probabilities have to be computed. Also, these two algorithms do not require any knowledge about the channel characteristics. Both algorithms yield a good performance-complexity trade-off and can be efficiently implemented in software as well as in hardware, with possibly quantized received values.

Starting from a memory-based nonlinear generator due to P.R. Geffe (1973), a binary sequence generator (MEM-BSG), consisting of three linear feedback shift registers and a variable memory, is defined and analyzed. The MEM-BSG is shown to be convenient for generating fast binary sequences of large period and linear complexity, which may be useful in spread-spectrum and cryptographic applications.>