IET Information Security最新文献

GEA-1, a proprietary stream cipher, was initially designed and used to protect against eavesdropping general packet radio service (GPRS) between the phone and the base station. Now, a variety of current mobile phones still support this standard cipher. In this paper, a structural weakness of the GEA-1 stream cipher that has not been found in previous works is discovered and analyzed. That is the probability that two different inputs of GEA-1 generate the identical keystream can be up to 2^−7.30, which is quite high compared with an ideal stream cipher that generates random sequences. Based on this newfound weakness, a new practical distinguishing attack on GEA-1 is proposed, which shows that the keystreams generated by GEA-1 are far from random and can be easily distinguished with a practical time cost. After then, a new practical key recovery attack on GEA-1 is presented. It has a time complexity of 2^21.02 GEA-1 encryptions and requires only seven related keys, which is much less than the existing related key attack on GEA-1. The experimental results show that GEA-1 can be broken within about 41.75 s on a common PC in the related key setting. These cryptanalytic results show that GEA-1 cannot provide enough security and should be immediately prohibited to be supported in the massive GPRS devices.

Two-party private set intersection (PSI) plays a pivotal role in secure two-party computation protocols. The communication cost in a PSI protocol is normally influenced by the sizes of the participating parties. However, for parties with unbalanced sets, the communication costs of existing protocols mainly depend on the size of the larger set, leading to high communication cost. In this paper, we propose a low communication-cost PSI protocol designed specifically for unbalanced two-party private sets, aiming to enhance the efficiency of communication. For each item in the smaller set, the receiver queries whether it belongs to the larger set, such that the communication cost depends solely on the smaller set. The queries are implemented by private information retrieval which is constructed with trapdoor hash function. Our investigation indicates that in each instance of invoking the trapdoor hash function, the receiver is required to transmit both a hash key and an encoding key to the sender, thus incurring significant communication cost. In order to address this concern, we propose the utilization of a seed hash key, a seed encoding key, and a Latin square. By employing these components, the sender can autonomously generate all the necessary hash keys and encoding keys, obviating the multiple transmissions of such keys. The proposed protocol is provably secure against a semihonest adversary under the Decisional Diffie–Hellman assumption. Through implementation demonstration, we showcase that when the sizes of the two sets are 2⁸ and 2¹⁴, the communication cost of our protocol is only 3.3% of the state-of-the-art protocol and under 100 Kbps bandwidth, we achieve 1.46x speedup compared to the state-of-the-art protocol. Our source code is available on GitHub: https://github.com/TAN-OpenLab/Unbanlanced-PSI.

The continuous malicious attacks on Internet of Things devices pose a potential threat to the economic and private information security of end-users, especially on the dominant Android devices. Combining static analysis methods with deep Learning is a promising approach to defend against that. This kind of method has two limitations: the first is that the current single-permission mechanism is not insufficient to regulate interapplication resource acquisition; another problem is that current work on feature learning is dedicated to modifying a single network structure, which may result in a suboptimal solution. In this study, to solve the abovementioned problems, we propose a novel malware detection framework MFEMDroid, which combines multitype features analysis and ensemble modeling. The Provider feature, facilitating information requests between applications (apps) and serving as an indispensable data storage method, plays a vital role in characterizing app behavior. Hence, we extract permissions and Provider features to comprehensively characterize app behavior and probe potentially dangerous combinations between or within these features. To address oversparse datasets and reduce feature learning overhead, we employ an auto-encoder for feature dimensionality reduction. Furthermore, we design an ensemble network based on SENet, ResNet, and the evolutionary convolutional neural network Squeeze Excitation Residual Network (SEResNet) to explore the hidden associations between different types of features from multiple perspectives. We performed extensive experiments to evaluate its method performance on real-world samples. The evaluation results demonstrate that the proposed framework can detect malware with an accuracy of 95.38%, which is much better than state-of-the-art solutions. These promising experimental results show that MFEMDroid is an effective approach to detect Android malware.

Universal composability (UC) is a primary security flavor for designing oblivious transfer (OT) due to its advantage of arbitrary composition. However, the study of UC-secure OT over lattices is still far behind compared with constructions over prequantum assumptions. Relying on the learning with errors (LWE) assumption, Quach proposes a dual-mode encryption scheme (SCN’20) for deriving a two-round OT whose security is provably UC-secure in the common reference string (CRS) model. Due to its use of a randomized rounding function proposed by Benhamouda et al. (PKC’18), this OT can only be limited to transmitting single-bit messages. Therefore, conducting trivial repetitions of Quach’s OT when transmitting multibit strings would be very costly. In this work, we put forward a modified dual-mode encryption cryptosystem under the decisional LWE assumption, from which we can derive a UC-secure string OT with both full-fledged dual-mode security and better efficiency on transmitting strings. The key technique we adopt is a key reconciliation scheme proposed by Jiang et al. (PKC’20), which is utilized to extend the single-bit symmetric encryption key (produced by the aforementioned rounding function) to a multibit case. Through a comprehensive performance analysis, we demonstrate that our proposal can indeed strike a balance between security and efficiency.

Blockchain is commonly employed in access control to provide safe medical data exchange because of the characteristics of decentralization, nontamperability, and traceability. Patients share personal health data by granting access rights to users or medical institutions. The major purpose of the existing access control techniques is to identify users who are permitted to access medical data. They hardly ever recognize internal assailants from legitimate entities. Medical data will involve multilayer access within the authorized organizations. Considering the cost of permissions management and the problem of insider malicious node attacks, users hope to implement authorization constraints within the authorized institutions. It can prevent their data from being maliciously disclosed by end-users from different authorized healthcare domains. For the purpose to achieve the fine-grained permissions propagation control of medical data in sharing institutions, a trust-based authorization access control mechanism is suggested in this study. Trust thresholds are assigned to different privileges based on their sensitivity and used to generate zero-knowledge proof to be broadcasted among blockchain nodes. This method evaluates the trust of each user through the dynamic trust calculation model. And meanwhile, smart contract is employed to verify whether the user’s trust can activate some permissions and ensure the privacy of the user’s trust in the process of authorization verification. In addition, the authorization transaction between users and institutions is recorded on the blockchain for patient traceability and accountability. The feasibility and effectiveness of the scheme are demonstrated through comprehensive comparisons and extensive experiments.

Lattice-based encryption schemes are significant cryptographic primitives to defend information security against quantum menace, and the decryption failure rate is related to both theoretical and realistic security. We quantitatively analyze how the floating-point arithmetic and neglecting small probabilities impact the precision, and propose a new effective and efficient test of the failure probability. Therein explicit criteria are given to select the floating-point datatype and to decide which small probabilities should be abandoned. Furthermore, the outcome is theoretically ensured to meet a given precision. Moreover, by combining the heuristic estimate and the precise simulation, this test is more efficient than previously neglecting small probabilities in a practical way.

At Eurocrypt 2020, Coron et al. proposed a masking technique allowing the use of random numbers from pseudo-random generators (PRGs) to largely reduce the use of expansive true-random generators (TRNGs). For security against d probes, they describe a construction using 2d PRGs, each of which is fed with at most 2d random variables in a finite field, resulting in a randomness requirement of $$. In this paper, we improve the technique on multiple frontiers. On the theoretical level, we push the limits of the randomness requirement by providing an improved masking multiplication using only d PRGs, each of which is fed with d random variables, saving more than half random bits. On the practical level, considering that the masking of arithmetic addition usually requires more randomness (than multiplication), we apply the technique to the algorithm proposed at FSE 2015 that is a very efficient scheme performing arithmetic addition modulo 2^w. It significantly reduces the randomness cost of masked arithmetic addition, and further advocates the advantage of masking with PRGs. Furthermore, we apply our masking scheme to the Speck, XTEA, and Sparkle, and provide the first (to the best of our knowledge) higher order masked implementations for the ciphers using ARX structure.

Differential-linear (DL) cryptanalysis is an important cryptanalytic method in cryptography and has received extensive attention from the cryptography community since its proposal by Langford and Hellman in 1994. At CT-RSA 2023, Bellini et al. introduced continuous difference propagations of XOR, rotation, and modulo-addition operations and proposed a fully automatic method using Mixed-Integer Linear Programing (MILP) and Mixed-Integer Quadratic Constraint Programing (MIQCP) techniques to search for DL distinguishers of Addition-Rotation-XOR (ARX) ciphers. In this paper, we propose continuous difference propagation of AND operation and construct an MILP/MIQCP-based fully automatic model of searching for DL distinguishers of SIMON-like ciphers. We apply the fully automatic model to all versions of SIMON and SIMECK. As a result, for SIMON, we find 13 and 14-round DL distinguishers of SIMON32, 15, 16, and 17-round DL distinguishers of SIMON48, 20-round DL distinguishers of SIMON64, 25 and 26-round DL distinguishers of SIMON96, 31 and 32-round DL distinguishers of SIMON128. For SIMECK, we find 14-round DL distinguishers of SIMECK32, 17 and 18-round DL distinguishers of SIMECK48, 22, 23, 24, and 25-round DL distinguishers of SIMECK64. As far as we know, our results are currently the best.

Anonymous data exchange is in great demand in many situations, especially in remote control systems, in which a stable, secure, and secret data channel must be established between the controlling and controlled parties to distribute control commands and return data. In the previous work, we built a two-level Virtual-Space anonymous communication scheme based on the Crowds System for performing secret data exchange in remote control systems. However, as an essential part of security and anonymity, participating nodes’ identity declaration and session key agreement phases were not well designed. In this paper, we redesign the identity agreement and declaration process and design an identity-based Virtual-Space agreement method using the extended Chebyshev Chaotic Maps. In this approach, we transform the identity declaration process into a multilevel Virtual-Space agreement problem, where a series of security-progressive Virtual-Space addresses are negotiated between the controller and the controlled nodes. The protocol can handle the case where there are multiple controllers in the system, and the negotiated Virtual-Space depends on the identity of the controller and the controlled node, so different controllers do not affect each other. The designed protocol is verified on Freenet, and we conclude this paper with a detailed security analysis of the method to prove that the method satisfies forward security.

This paper focuses on similarity properties and extension of the classical slide property of block ciphers. Taking FESH, an award-winning block cipher of the National Cryptographic Algorithm Design Competition 2019, as an example, similarity properties of the encryption and key transformation are found, owing to the similar structures that the encryption and key transformation adopted, and the constants generation. Based on the similarity properties, extended slide properties can be constructed for FESH. Slide attacks of FESH are then proposed. The similarity properties and extended slide property are immune to the increasing of iterated rounds, i.e., it cannot be avoided by increasing the round number of FESH. Furthermore, extended slide property helps relaxing the strict requirements of the subkeys in slide attacks. Taking Feistel and SPN structures as examples, frameworks of slide attacks based on the extended slide properties are presented. Slide attack of FESH is exactly a concrete example of SPN structure.