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Science and Technology Innovation (IAECST), International Academic Exchange Conference on

作者： Weina Dong Zongbao Jiang Lifeng Chen Wenquan Sun Key Laboratory of Network and Information Security of PAP Engineering University of PAP Xi’an Shaanxi China

Aiming at the problem that the high-capacity steganography model based on encoding-decoding network had weak robustness and could not resist noise attack and channel compression, an improved high-capacity robust image steganography algorithm based on adversarial network was proposed. In the proposed algorithm, encoder, decoder and critic based on densely connected convolutional networks (DenseNet) were designed. The secret information and the carrier image are jointly encoded into a steganographic image by the encoder, then the secret information was extracted by the decoder. The critic was used to discriminate between carrier images and steganographic images. A noise layer was added between encoder and decoder, Dropout, JPEG compression, gaussian blur, gaussian noise and salt and pepper noise were used to simulate a real environment of various kinds of noise attack. The steganography output by encoder was processed with different kinds of noise and decoded by decoder. Through model was trained, the message could be extracted from the noise-processed steganographic image by the decoder, so the ability to resist noise attacks was realized. The experiment results show that the steganographic capacity of the proposed algorithm reaches 0.450.95 bits per pixel (bpp) on $360 \times 360$ pixel images, which are 3.6 times higher than that of the earlier robust steganographic algorithms. The decoding accuracy reaches 0.72-0.97, which are 42% points higher than that of steganography without noise layer. The proposed algorithm not only guarantees high embedding quantity and high coding image quality, but also has stronger anti-noise capability.

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Another Lattice Attack Against ECDSA with the wNAF to Recover More Bits per Signature 1

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18th EAI International Conference on security and Privacy in Communication networks, SecureComm 2022

作者： Ma, Ziqiang Li, Shuaigang Lin, Jingqiang Cai, Quanwei Fan, Shuqin Zhang, Fan Luo, Bo School of Information Engineering Ningxia University Yinchuan China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Science and Technology of China Hefei China State Key Laboratory of Cryptology Beijing China School of Cyber Science and Technology College of Computer Science and Technology Zhejiang University Hangzhou310027 China Key Laboratory of Blockchain and Cyberspace Governance of Zhejiang Province Hangzhou310027 China Department of Electrical Engineering and Computer Science University of Kansas Lawrence United States

ISBN: (数字)9783031255380

ISBN: (纸本)9783031255373

In the resource-constrained environment such as the Internet of Things, the windowed Non-Adjacent-Form (wNAF) representation is usually used to improve the calculation speed of the scalar multiplication of ECDSA. This paper presents a practical cache side channel attack on ECDSA implementations which use wNAF representation. Compared with existing works, our method exploits more information from the cache side channels, which is then efficiently used to construct lattice attacks in the ECDSA private key recovery. First, we additionally monitor the invert function which is related to the sign of the wNAF digits, and obtain a Double-Add-Invert chain through the Flush+Flush cache side channel. Then, we develop effective methods extracting 154.2 bits information of the ephemeral key per signature for 256-bit ECDSA from this chain, much more than the best known result which extracts 105.8 bits per signature. Finally, to efficiently use the extracted information, we convert the problem of recovering the private key to the Hidden Number Problem (HNP) and the Extended Hidden Number Problem (EHNP) respectively, which are solved by lattice reduction algorithms. We applied the attack on ECDSA with the secp256k1 curve in OpenSSL 1.1.0h. The experimental results show that only 3 signatures are enough to recover the private key. To the best of our knowledge, this work exploits the signs of the wNAF representation, along with the Double-Add chain against ECDSA, to recover the private key with the least number of signatures. © 2023, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Side channel attack

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Image Recognition In Complex Environments Based On Improved FCM Algorithm 43

Image Recognition In Complex Environments Based On Improved ...

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43rd Chinese Control Conference, CCC 2024

作者： Pengxin, Zhao Qing, Lv Qiang, Li Jin, Wang Hebei Normal University College of Computer and Cyberspace Security Shijiazhuang050010 China College of Engineering of Hebei Normal University Hebei Normal University Shijiazhuang050010 China Hebei Provincial Key Laboratory of Information Fusion and Intelligent Control China

ISBN: (纸本)9789887581581

In recent years, image recognition has been commonly utilized in the field of computer vision, while the challenge of image recognition in complex environments has become a topical study. The fuzzy C-mean (FCM) is a clustering algorithm based on fuzzy set theory and achieves clustering by assigning affiliation to each data point. However, in complex environments, the FCM algorithm may fall into local optimal solutions and lead to a decrease in recognition accuracy. To solve this problem, this paper proposes an improved approach based on a genetic algorithm and simulated annealing algorithm applied in the FCM algorithm. The genetic algorithm searches and optimizes the clustering centers by simulating the biological evolution process to find more optimal parameters for the experiment. The simulated annealing algorithm performs global optimization. It generates new solutions by adding a small perturbation to avoid the clustering centers from falling into local optima. Finally, a series of image recognition experiments are conducted in complex environments. The experiment results show that the proposed approach has higher recognition accuracy and robustness in complex environments compared with the traditional FCM algorithm. The algorithm can improve the accuracy of image recognition and has good adaptability in complex environments. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Genetic algorithms

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ADACQR: Enhancing Query Reformulation for Conversational Search via Sparse and Dense Retrieval Alignment

arXiv

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arXiv 2024年

作者： Lai, Yilong Wu, Jialong Zhang, Congzhi Sun, Haowen Zhou, Deyu School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China

Conversational Query Reformulation (CQR) has significantly advanced in addressing the challenges of conversational search, particularly those stemming from the latent user intent and the need for historical context. Recent works aimed to boost the performance of CQR through alignment. However, they are designed for one specific retrieval system, which potentially results in sub-optimal generalization. To overcome this limitation, we present a novel framework ADACQR. By aligning reformulation models with both term-based and semantic-based retrieval systems, ADACQR enhances the generalizability of information-seeking queries among diverse retrieval environments through a two-stage training strategy. Moreover, two effective approaches are proposed to obtain superior labels and diverse input candidates, boosting the efficiency and robustness of the framework. Experimental results on the TopiOCQA, QReCC and TREC CAsT datasets demonstrate that ADACQR outperforms the existing methods in a more efficient framework, offering both quantitative and qualitative improvements in conversational query reformulation.1 Copyright © 2024, The Authors. All rights reserved.

关键词： Structured Query Language

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Power amplifier circuit defect detection based on improved Patch SVDD

Power amplifier circuit defect detection based on improved P...

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作者： Xie, Zhonghui Kong, Wa Zhou, Xinyu Zhang, Wence Zhong, Yujie Xia, Jing School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace Jiangsu University Zhenjiang China Department of Electronic Information Engineering Hong Kong Polytechnic University Hong Kong

In the manufacturing process of power amplifier (PA), various defects on the circuit surface will seriously affect the circuit performance and its operation. To solve the above problems, this article proposes a circuit defect detection method based on improved patch-based support vector data description algorithm (Patch SVDD), which uses contrastive learning to enhance the feature extraction ability of neural network. An image calibration algorithm is used for calibration preprocessing to enhance the robustness of the model. The Euclidean distance between a query image patch and its nearest normal patch is defined to be an anomaly score. For verification, three defects in the PA circuit, including components missing, solder contamination and component orientation dislocation, were detected. The experimental results show that, compared with conventional method, the area under receiver operating characteristic (AUROC) of the improved anomaly detection model increased from 90.1% to 95.1%, which improves the detection accuracy effectively. © 2023 John Wiley & Sons Ltd.

关键词： Anomaly detection

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SEED: Accelerating Reasoning Tree Construction via Scheduled Speculative Decoding

arXiv

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arXiv 2024年

作者： Wang, Zhenglin Wu, Jialong Lai, Yilong Zhang, Congzhi Zhou, Deyu School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China

Large Language Models (LLMs) demonstrate remarkable emergent abilities across various tasks, yet fall short of complex reasoning and planning tasks. The tree-search-based reasoning methods address this by encouraging the exploration of intermediate steps, surpassing the capabilities of chain-of-thought prompting. However, significant inference latency is introduced due to the systematic exploration and evaluation of multiple thought paths. This paper introduces SEED, a novel and efficient inference framework to improve both runtime speed and GPU memory management concurrently. Based on a scheduled speculative execution, SEED efficiently handles multiple iterations for thought generation and state evaluation, leveraging a rounds-scheduled strategy to manage draft model dispatching. Extensive experimental evaluations on three reasoning datasets demonstrate the superior speedup performance of SEED1 Copyright © 2024, The Authors. All rights reserved.

关键词： Memory management

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A Method of Firmware Vulnerability Mining and Verification Based on Code Property Graph 8th

A Method of Firmware Vulnerability Mining and Verification B...

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8th International Conference on Artificial Intelligence and security , ICAIS 2022

作者： Xiao, Na Zeng, Jing Yao, Qigui Huang, Xiuli Platform Operation and Security Department Information and Telecommunication Company Beijing100000 China State Grid Key Laboratory of Information and Network Security Global Energy Interconnection Research Institute Co. Ltd. Nanjing210000 China

ISBN: (纸本)9783031067631

With the rapid development of smart power grid, the security of intelligent terminal has been widely concerned. Firmware is the core component of intelligent terminal equipment, and its vulnerability has become one of the main threats to intelligent terminal security. However, the difficulty of obtaining firmware, extracting binary files and analyzing code bring a series of difficulties to firmware vulnerability mining, resulting in low accuracy and high false positive rate of vulnerability mining. Therefore, this paper proposes a firmware vulnerability mining method based on code property graph. First, generate the code property graph of the target program;secondly, abstract syntax tree, control flow graph and data dependency graph are extracted from code property graph. Then the traversal analysis of these three graphs gradually reduces the scope of the vulnerability;Finally, combined with manual analysis and review, the results of vulnerability mining are obtained. In this paper, joern tool is used to verify the DVRF project, mining stack overflow vulnerability, heap overflow vulnerability, command injection vulnerability and heap release vulnerability, and good experimental results are obtained. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Static analysis

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A generalized reliability analysis of 3-ary n-cubes

A generalized reliability analysis of 3-ary n-cubes

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International Conference on Communication Software and networks, ICCSN

作者： Zefang Bai Guijuan Wang Meijie Ma School of Mathematics and Statistics Qilu University of Technology (Shandong Academy of Sciences) Jinan China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (数字)9798331506322

ISBN: (纸本)9798331506339

Evaluating the reliability of interconnection networks is crucial. The edge-connectivity is a parameter used to assess reliability. In this paper, we discuss a conditional edge-connectivity called the h-extra g-component edge-connectivity. It combines the extra edge-connectivity and the component edge-connectivity. First, this paper proved that $c \lambda_{3}^{h}\left(Q_{n}^{3}\right)=4 n h-$ $4 e_{h}\left(Q_{n}^{3}\right)-h$ for $1 \leq h \leq \frac{1}{2} \cdot 3^{\left\lceil\frac{h}{2}\right\rceil}, n \geq 3$. Then, the paper given the upper bound of h-extra g-component edge-connectivity of the 3 -ary n-cubes for $g \in\left\{4,3^{c}+1\right\}, 1 \leq c \leq\left\lceil\frac{n}{2}\right\rceil-1, n \geq 3$.

关键词： Upper bound Multiprocessor interconnection Software Reliability

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An Efficient Authentication and key Agreement Scheme for CAV Internal Applications 19th

An Efficient Authentication and Key Agreement Scheme for C...

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19th EAI International Conference on Collaborative Computing: networking, Applications and Worksharing, CollaborateCom 2023

作者： Li, Yang Zhang, Qingyang Cao, Wenwen Cui, Jie Zhong, Hong Anhui Province Key Laboratory of Cyberspace Security Situation Awareness and Evaluation Hefei230037 China School of Computer Science and Technology Anhui University Hefei230039 China Anhui Engineering Laboratory of IoT Security Technologies Anhui University Hefei230039 China Institute of Physical Science and Information Technology Anhui University Hefei230039 China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei230039 China

ISBN: (纸本)9783031545276

The data of applications in connected and autonomous vehicles are important, which is usually collected by service providers to improve their services, such as object detection model. But, wireless communication is susceptible to various kinds of attacks. Thus, the data of the application module needs to be securely shared to the corresponding service provider. However, current schemes are with limited performance while a service provider collects multiple application data at the same time. By adopting signcryption and chaotic map, an efficient authentication and key agreement scheme is proposed, while batch authentication is achieved for efficient message authentication of multiple applications, and the efficient revocation is realized based on Chinese remainder theorem under the assistance of trusted execution environment supported vehicle computing/communication unit. The formal security proof shows that the scheme is secure under the random oracle model, and the experiment results shows that the scheme is more efficient than related schemes and can meet the requirements of CAV. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Authentication

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Causal Walk: Debiasing Multi-Hop Fact Verification with Front-Door Adjustment

arXiv

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arXiv 2024年

作者： Zhang, Congzhi Zhang, Linhai Zhou, Deyu School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China

Multi-hop fact verification aims to detect the veracity of the given claim by integrating and reasoning over multiple pieces of evidence. Conventional multi-hop fact verification models are prone to rely on spurious correlations from the annotation artifacts, leading to an obvious performance decline on unbiased datasets. Among the various debiasing works, the causal inference-based methods become popular by performing theoretically guaranteed debiasing such as casual intervention or counterfactual reasoning. However, existing causal inference-based debiasing methods, which mainly formulate fact verification as a single-hop reasoning task to tackle shallow bias patterns, cannot deal with the complicated bias patterns hidden in multiple hops of evidence. To address the challenge, we propose Causal Walk, a novel method for debiasing multi-hop fact verification from a causal perspective with front-door adjustment. Specifically, in the structural causal model, the reasoning path between the treatment (the input claim-evidence graph) and the outcome (the veracity label) is introduced as the mediator to block the confounder. With the front-door adjustment, the causal effect between the treatment and the outcome is decomposed into the causal effect between the treatment and the mediator, which is estimated by applying the idea of random walk, and the causal effect between the mediator and the outcome, which is estimated with normalized weighted geometric mean approximation. To investigate the effectiveness of the proposed method, an adversarial multi-hop fact verification dataset and a symmetric multi-hop fact verification dataset are proposed with the help of the large language model. Experimental results show that Causal Walk outperforms some previous debiasing methods on both existing datasets and the newly constructed datasets. Code and data will be released at https://***/zcccccz/CausalWalk. Copyright © 2024, The Authors. All rights reserved.

关键词： Large datasets

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