The probe can directly contact the microcontroller in a typical EM side-channel attack (SCA) targeting cryptographic implementations. However, in a more practical setting such as security level 2 of FIPS 140-3 or ISO/IEC 19790 standards, the microcontroller is required to be safeguarded by an opaque anti-tampering cover. This raises an interesting problem: Can we still launch EM attacks against microcontrollers running cryptographic implementations even when equipped with the cover? This paper proposes an improved deep-learning-based profiled attack against NIST KEM standard Kyber. Our key observation is that the distance between the probe and the microcontroller results in attenuation of signal strength. Moreover, the cover restricts the proximity of the probe, thereby limiting the signal-to-noise ratio. We propose an Adaptive Slimmed Pyramid Network (ASPN) model to instantiate a distinguisher in a plaintext-checking oracle-based SCA, which is generic and easy to implement. The proposed ASPN approach significantly enhances the feature extraction process by employing a pyramid network structure, while simultaneously avoiding the inclusion of excessive parameters. Real-world experiments demonstrate that our proposed distinguishers achieve an accuracy above$99\%$with an$18$mm cover and higher than$89\%$accuracy even with a$24$mm cover.

Smart-card based password authentication has been the most widely used two-factor authentication (2FA) mechanism for security-critical applications (e.g., e-Health, smart grid and e-Commerce) in the past decades, and it is likely to hold its status in the foreseeable future. Hundreds of this type of 2FA schemes have been proposed, yet to our knowledge, most of them are built on the intractability of conventional hard problems (e.g., discrete logarithm problems and integer factoring problems) which are no longer hard in the quantum era. With the recent advancements in quantum computing, the design of secure and efficient smart-card based password authentication schemes against quantum attacks is becoming increasingly urgent. However, it is not as simple as it seems,how to design such a quantum-resistant 2FA scheme is challenging due to the demanding security requirements and the resource-constrained nature of mobile devices. In this work, we take the first step towards this issue by proposing Quantum2FA, a practical quantum-resistant smart-card-based password authentication scheme that employs Alkimet al.’s lattice-based key exchange and Wang-Wang’s “fuzzy-verifier + honeywords” technique (IEEE TDSC’18). Particularly, Quantum2FA can thwart the newly revealed key-reuse attack (ACISP’18, CT-RSA’19) against lattice-based key exchange schemes in two aspects: signal leakage attacks and key mismatch attacks. Specifically, it restricts the necessary conditions (i.e., the attacker must be the initiator of the key exchange) for an adversary to analyze the signal; It introduces honeywords to detect the key mismatches between the smart card and the server, and thus smart card loss attack can be thwarted. We formally prove the security of Quantum2FA under the random oracle model and demonstrate its efficiency through experiments on a 32 MHz 8-bit AVR Embedded Processor. Comparison results show that Quantum2FA is not only more secure but also offers better computation efficiency than the state-of-the-art conventional 2FA schemes.

Existing semisupervised learning approaches generally focus on the single-agent (centralized) setting, and hence, there is the risk of privacy leakage during joint data processing. At the same time, using the mean square error criterion in such approaches does not allow one to efficiently deal with problems involving non-Gaussian distribution. Thus, in this article, we present a novel privacy-preserving semisupervised algorithm under the maximum correntropy criterion (MCC). The proposed algorithm allows us to share data among different entities while effectively mitigating the risk of privacy leaks. In addition, under MCC, our proposed approach works well for data with non-Gaussian distribution noise. Our experiments on three different learning tasks demonstrate that our method distinctively outperforms the related algorithms in common regression learning scenarios.

Recently, Zhanget al.proposed a lattice-based data outsourcing scheme with public integrity verification (DOPIV), which enables an original data owner to delegate a proxy to generate the signatures of data and outsource them to the cloud server. They employed a third party auditor (TPA) to check the integrity of the outsourced data and any TPA can verify the data integrity efficiently. DOPIV is claimed to achieve proxy-oriented secure data outsourcing as well as storage correctness guarantee. Unfortunately, we find that there exist vulnerabilities in DOPIV which allow the cloud server to simply delete the received data without being noticed by the TPA. Fortunately, we come up with a simple and efficient solution to thwart the proposed attack. Our improved scheme maintains all the features claimed in DOPIV.

The real-time electricity consumption data can be used in value-added service such as big data analysis, meanwhile the single user's privacy needs to be protected. How to balance the data utility and the privacy preservation is a vital issue, where the privacy-preserving data aggregation could be a feasible solution. Most of the existing data aggregation schemes rely on a trusted third party (TTP). However, this assumption will have negative impact on reliability, because the system can be easily knocked down by the denial of service attack. In this paper, a practical privacy-preserving data aggregation scheme is proposed without TTP, in which the users with some extent trust construct a virtual aggregation area to mask the single user's data, and meanwhile, the aggregation result almost has no effect for the data utility in large scale applications. The computation cost and communication overhead are reduced in order to promote the practicability. Moreover, the security analysis and the performance evaluation show that the proposed scheme is robust and efficient.

Sensitive data stored in laptops or other mobile devices can easily be lost, stolen, misplaced or corrupted, the remote backup storage technique is used to address these issues; however, the backup server could not be fully trusted, the data should be encrypted in advance. Although the key is more easily protected due to the smaller size compared with the backup data, it is still impossible for ordinary human to remember. A user‐centred design data backup scheme is proposed using multi‐factor authentication. The user firstly selects a symmetrical key and divides it into three shares, then destroys the key. The key can easily be reconstructed by combining the shares stored in the user's smart card and the laptop. Even if the smart card or laptop is lost, the key can still be recovered with the password and biometrics. The proposed scheme not only achieves the required security goals but also is more robust and practical.

Recently, based on the homomorphic signatures, the authentication schemes, such as homomorphic subspace signature (HSS) and key predistribution-based tag encoding (KEPTE), have been proposed to resist against pollution attacks in network coding. In this paper, we show that there exists an efficient multi-generation pollution attack on HSS and KEPTE. In particular, we show that using packets and their signatures of different generations, the adversary can create invalid packets and their corresponding signatures that pass the verification of HSS and KEPTE at intermediate the nodes as well as at the destination nodes. After giving a more generic attack, we analyze the cause of the proposed attack. We then propose the improved key distribution schemes for HSS and KEPTE, respectively. Next, we show that the proposed key distribution schemes can combat against the proposed multi-generation pollution attacks. Finally, we analyze the computation and communication costs of the proposed key distribution schemes for HSS and KEPTE, and by implementing experiments, we demonstrate that the proposed schemes add acceptable burden on the system.

Abstract Recently, Liu and Wang proposed a homomorphic signature scheme for network coding, which was claimed to resist against pollution attacks. However, we show that in Liu and Wang's scheme, after several generations, the adversary is able to launch a successful forgery attack with a high probability. Therefore, Liu and Wang's scheme is not secure. After analyzing the cause of the attack, an improved scheme is given, which can combat against the proposed attack in an efficient way. Copyright © 2015 John Wiley & Sons, Ltd.

Recently, the peer-to-peer (P2P) live streaming system has benefited from the advent of network coding. However, it was demonstrated that malicious nodes could significantly reduce the network throughput by launching pollution attacks or entropy attacks. In this paper, we propose an efficient symmetric-key based authentication scheme for P2P live streaming system with network coding, to provide in-network detection against pollution attacks and entropy attacks simultaneously. Since the nature of P2P live streaming requires that the detection scheme has high computation efficiency and small communication overheads, we firstly propose a homomorphic message authentication code (MAC), called as PMAC, which has small key size and low computation overhead. Then, the proposed PMAC and the delayed key disclosure technique are employed to make sure that the peers could not only detect the corrupted blocks, but also upload blocks in accordance with random linear network coding. Furthermore, the performance evaluation demonstrates that the proposed scheme has both low communication and computation overheads.

Recently, homomorphic message authentication code (MAC) schemes have been proposed to resist against pollution attacks in network coding. However, existing methods face a common challenge: the generated MAC t belongs to a small finite field Fq, which means that an adversary could attack by randomly guessing the value of t, and succeed with probability 1/q. Since q is a predetermined system parameter which is typically set as 28, the resulted security 1/256 could be unsatisfactory in practice. In this paper, we propose an efficient homomorphic MAC for authentication in network coding. The proposed method achieves a reliable security parameter 1/qlusing only one key, where l could be chosen according to different security requirements. Compared with previous approaches that using multiple tags, the proposed homomorphic MAC has both low computation and communication overheads.

To achieve secure group communication, one-time session keys need to be shared among group members in a secure and authenticated manner. In this paper, we propose an improved authenticated key transfer protocol based on Shamir's secret sharing. The proposed protocol achieves key confidentiality due to security of Shamir's secret sharing and provides key authentication by broadcasting a single authentication message to all members. Furthermore, the proposed scheme resists against both insider and outsider attacks.

In this letter, we propose a novel scheme to construct a novel class of 2-D binary sequences with zero correlation zone, which is based on perfect arrays and orthogonal sequences. Compared with all existing 2-D binary sequences, the proposed construction can generate more sets of two-dimensional binary sequences with long zero correlation zone. Moreover, the constructed 2-D sequence sets could be applied directly, such as arrays of sound sources, position detection arrays, phased-array antennas, time-frequency coding, and spatial correlation.