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DLP:towards active defense against backdoor attacks with decoupled learning process

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Cybersecurity 2024年第1期7卷 122-134页

作者： Zonghao Ying Bin Wu state key laboratory of information security Institute of Information EngineeringChinese Academy of SciencesBeijingChina School of Cyber security University of Chinese Academy of SciencesBeijingChina

Deep learning models are well known to be susceptible to backdoor attack,where the attacker only needs to provide a tampered dataset on which the triggers are *** trained on the dataset will passively implant the backdoor,and triggers on the input can mislead the models during *** study shows that the model shows different learning behaviors in clean and poisoned subsets during *** on this observation,we propose a general training pipeline to defend against backdoor attacks *** models can be trained from the unreli-able dataset by decoupling the learning process into three stages,i.e.,supervised learning,active unlearning,and active semi-supervised *** effectiveness of our approach has been shown in numerous experiments across various backdoor attacks and datasets.

关键词： Deep learning Backdoor attack Active defense

Constructing the Impossible Differential of Type-II GFN with Boolean Function and Its Application to WARP

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Chinese Journal of Electronics 2024年第1期33卷 80-89页

作者： Jiali SHI Guoqiang LIU Chao LI College of Liberal Arts and Sciences National University of Defense Technology Hunan engineering Research Center of Commercial Cryptography Theory and Technology Innovation state key laboratory of information security Institute of Information Engineering

Type-Ⅱ generalized Feist el network(GFN) has attracted a lot of attention for its simplicity and high *** differential attack is one of the powerful cryptanalytic approaches for word-oriented block ciphers such as Feistel-like *** deduce the impossible differential of Type-Ⅱ GFN by analyzing the Boolean function in the middle *** main idea is to investigate the expression with the variable representing the plaintext(ciphertext) difference words for the internal state *** adopting the miss-in-the-middle approach,we can construct the impossible differential of Type-Ⅱ *** an illustration,we apply this approach to WARP,a lightweight 128-bit block cipher with a 128-bit key which was presented by Banik et *** SAC *** structure of WARP is a 32-branch Type-Ⅱ ***,we find two 21-round truncated impossible differentials and implement a 32-round key recovery attack on *** the 32-round key recovery attack on WARP,some observations are used to mount an effective *** the advantage of the early abort technique,the data,time,and memory complexities are 2125.69chosen plaintexts,2126.6832-round encryptions,and 2100-bit,*** the best of our knowledge,this is the best attack on WARP in the single-key scenario.

关键词： Ciphers Boolean functions Parallel processing Complexity theory

Improved lower bound for the complexity of unique shortest vector problem

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Cybersecurity 2024年第3期7卷 102-110页

作者： Baolong Jin Rui Xue state key laboratory of information security Institute of Information EngineeringChinese Academy of SciencesBeijing 100085China School of Cyber security University of Chinese Academy of SciencesBeijing 100049China

Unique shortest vector problem(uSVP)plays an important role in lattice based *** cryptographic schemes based their security on *** the cofidence of those applications,it is essential to clarify the complex-ity of uSVP with different ***,proving the NP-hardness of usVP appears quite *** the state of the art,we are even not able to prove the NP-hardness of usVP with constant *** this work,we gave a lower bound for the hardness of usVP with constant parameters,*** proved that uSVP is at least as hard as gap shortest vector problem(GapSVP)with gap of O(√n/log(n)),which is in NP n *** previous works,our reduction works for paramters in a bigger range,especially when the constant hidden by the big-O in GapsVP is smallerthan1.

关键词： Computational complexity Unique shortest vector problem Bounded distance decoding Complexity reduction

Big Data Access Control Mechanism Based on Two-Layer Permission Decision Structure

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Computers, Materials & Continua 2024年第4期79卷 1705-1726页

作者： Aodi Liu Na Wang Xuehui Du Dibin Shan Xiangyu Wu Wenjuan Wang He’nan Province key laboratory of information security Information Engineering UniversityZhengzhou450000China

Big data resources are characterized by large scale, wide sources, and strong dynamics. Existing access controlmechanisms based on manual policy formulation by security experts suffer from drawbacks such as low policymanagement efficiency and difficulty in accurately describing the access control policy. To overcome theseproblems, this paper proposes a big data access control mechanism based on a two-layer permission decisionstructure. This mechanism extends the attribute-based access control (ABAC) model. Business attributes areintroduced in the ABAC model as business constraints between entities. The proposed mechanism implementsa two-layer permission decision structure composed of the inherent attributes of access control entities and thebusiness attributes, which constitute the general permission decision algorithm based on logical calculation andthe business permission decision algorithm based on a bi-directional long short-term memory (BiLSTM) neuralnetwork, respectively. The general permission decision algorithm is used to implement accurate policy decisions,while the business permission decision algorithm implements fuzzy decisions based on the business *** BiLSTM neural network is used to calculate the similarity of the business attributes to realize intelligent,adaptive, and efficient access control permission decisions. Through the two-layer permission decision structure,the complex and diverse big data access control management requirements can be satisfied by considering thesecurity and availability of resources. Experimental results show that the proposed mechanism is effective andreliable. In summary, it can efficiently support the secure sharing of big data resources.

关键词： Big data access control data security BiLSTM

New Algebraic Attacks on Grendel with the Strategy of Bypassing SPN Steps

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Chinese Journal of Electronics 2024年第3期33卷 635-644页

作者： Wenxiao QIAO Siwei SUN Lei HU state key laboratory of information security Institute of Information Engineering Chinese Academy of Sciences School of Cyber security University of Chinese Academy of Sciences School of Cryptology University of Chinese Academy of Sciences state key laboratory of Cryptology

The rapid development of modern cryptographic applications such as zero-knowledge,secure multiparty computation,fully homomorphic encryption has motivated the design of new so-called arithmetization-oriented symmetric *** designing ciphers in this domain is relatively new and not well-understood,the security of these new ciphers remains to be completely *** this paper,we revisit the security analysis of arithmetizat ionoriented cipher *** uses the Legendre symbol as a component,which is tailored specifically for the use in zero-knowledge and efficiently-varifiable proof *** FSE 2022,the first preimage attack on some original full GrendelHash instances was *** a countermeasure,the designer adds this attack into the security analysis and updates the formula to derive the secure number of *** our work,we present new algebraic attacks on *** the preimage attack,we can reduce the complexity or attack one more round than previous attacks for some *** addition,we present the first collision attack on some round-reduced instances by solving the constrained input/constrained output problem for the underlying permutations.

关键词： Ciphers Symbols Multi-party computation Complexity theory Homomorphic encryption

Efficient privacy-preserving federated learning under dishonest-majority setting

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Science China(information Sciences) 2024年第5期67卷 323-324页

作者： Yinbin MIAO Da KUANG Xinghua LI Tao LENG Ximeng LIU Jianfeng MA School of Cyber engineering Xidian University Intelligent Policing key laboratory of Sichuan Province Sichuan Police College institute of information engineering Chinese Academy of Sciences School of Cyber security University of Chinese Academy of Sciences key laboratory of information security of Network Systems Fuzhou University

Federated learning(FL) is an emerging distributed learning paradigm that solves the problem of isolated data by jointly learning the global model through distributed ***, recent studies have shown that FL may not always guarantee sufficient privacy preservation, this is mainly because the model parameters(e.g., weights or gradients)may leak sensitive information to malicious adversaries.

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CRBFT:A Byzantine Fault-Tolerant Consensus Protocol Based on Collaborative Filtering Recommendation for Blockchains

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Computers, Materials & Continua 2024年第7期80卷 1491-1519页

作者： Xiangyu Wu Xuehui Du Qiantao Yang Aodi Liu Na Wang Wenjuan Wang He’nan Province key laboratory of information security Information Engineering UniversityZhengzhou450000China School of Cyber Science engineering Zhengzhou UniversityZhengzhou450000China

Blockchain has been widely used in finance,the Internet of Things(IoT),supply chains,and other scenarios as a revolutionary *** protocol plays a vital role in blockchain,which helps all participants to maintain the storage state ***,with the improvement of network environment complexity and system scale,blockchain development is limited by the performance,security,and scalability of the consensus *** address this problem,this paper introduces the collaborative filtering mechanism commonly used in the recommendation system into the Practical Byzantine Fault Tolerance(PBFT)and proposes a Byzantine fault-tolerant(BFT)consensus protocol based on collaborative filtering recommendation(CRBFT).Specifically,an improved collaborative filtering recommendation method is designed to use the similarity between a node’s recommendation opinions and those of the recommender as a basis for determining whether to adopt the recommendation *** can amplify the recommendation voice of good nodes,weaken the impact of cunningmalicious nodes on the trust value calculation,andmake the calculated resultsmore *** addition,the nodes are given voting power according to their trust value,and a weight randomelection algorithm is designed and implemented to reduce the risk of *** experimental results show that CRBFT can effectively eliminate various malicious nodes and improve the performance of blockchain systems in complex network environments,and the feasibility of CRBFT is also proven by theoretical analysis.

关键词： Blockchain consensus byzantine fault-tolerant collaborative filtering trust

Robust textile-based spoof plasmonic frequency scanning antenna for on-body IoT applications

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Science China(information Sciences) 2024年第8期67卷 269-284页

作者： Zhao-Min CHEN Jun-Lin ZHAN Hao CHEN Ya LI Hongjun HE Wu YANG Zhen-Guo LIU Wei-Bing LU state key Lab of Millimeter Waves School of Information Science and EngineeringSoutheast University Center for Flexible RF Technology Frontiers Science Center for Mobile Information Communication and SecuritySoutheast University Future Research laboratory China Mobile Research Institute Purple Mountain Laboratories

Securing a comfortable, wearable compact frequency beam scanning antenna(FBSA) with robustness to deformation, low specific absorption rate(SAR), and good coverage of the surrounding environment for Internet of Things(IoT) applications, such as on-body navigation and wireless communication is an emerging challenge. In this work, a robust textile-based spoof plasmonic frequency scanning antenna utilizing higher-order modes is presented, which is also robust to deformation caused by the activities of the human body. The innovative design of the element ensures the high-efficiency transmission of the fundamental mode of spoof surface plasmon polaritons(SSPP) structure, providing the potential of being a multifunctional composite device in the compact on-body network. Besides, an artificial magnetic conductor(AMC) is designed underneath the SSPP structure, obtaining a low SAR value(0.113 W/kg), which ensures the safety of users. As a practical realization of this concept, a textile-based spoof plasmonic antenna was fabricated in the microwave regime and the performed experimental results show the proposed antenna has a single-beam radiation characteristic with a 70° beam scanning angle range when the frequency is 4.7–6.0 GHz with a high average realized gain of 13.15 dBi. And it still maintains a steady performance when faced with structure deformation, which proves its robustness. Wireless communication quality experiments are performed to demonstrate the proposed antenna can measure the angles of targets and realize wireless signal transmission to specific targets as the frequency varies, it may find great potential in the field of on-body IoT applications.

关键词： frequency beam scanning antenna (FBSA) Internet of Things (IoT) on-body communication spoof surface plasmon polaritons (SSPP) textile-based antenna

Efficient Penetration Testing Path Planning Based on Reinforcement Learning with Episodic Memory

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Computer Modeling in engineering & Sciences 2024年第9期140卷 2613-2634页

作者： Ziqiao Zhou Tianyang Zhou Jinghao Xu Junhu Zhu Henan key laboratory of information security National Engineering Technology Research Center of the Digital Switching SystemZhengzhou450000China School of Cryptographic engineering Information Engineering UniversityZhengzhou450000China

Intelligent penetration testing is of great significance for the improvement of the security of information systems,and the critical issue is the planning of penetration test *** view of the difficulty for attackers to obtain complete network information in realistic network scenarios,Reinforcement Learning(RL)is a promising solution to discover the optimal penetration path under incomplete information about the target *** RL-based methods are challenged by the sizeable discrete action space,which leads to difficulties in the ***,most methods still rely on experts’*** address these issues,this paper proposes a penetration path planning method based on reinforcement learning with episodic ***,the penetration testing problem is formally described in terms of reinforcement *** speed up the training process without specific prior knowledge,the proposed algorithm introduces episodic memory to store experienced advantageous strategies for the first ***,the method offers an exploration strategy based on episodic memory to guide the agents in *** design makes full use of historical experience to achieve the purpose of reducing blind exploration and improving planning ***,comparison experiments are carried out with the existing RL-based *** results reveal that the proposed method has better convergence *** running time is reduced by more than 20%.

关键词： Intelligent penetration testing penetration testing path planning reinforcement learning episodic memory exploration strategy