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International Conference on Computer and communications (ICCC)

作者： Zhiping Lu Ruxin Zhi Weiguo Ma School of Information and Communication Engineering Beijing University of Posts and Telecommunications State Key Laboratory of Wireless Mobile Communications China Academy of Telecommunications Technology (CATT) Beijing China Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

Low earth orbit satellite communication systems are attractive for provisioning global, high-speed and low latency Internet access services. In order to achieve global continuous multiple coverage, the number of satellites is tremendous. But Low earth orbit satellite networks are prone to instability due to unpredictable link failures and frequent topology changes. Therefore, in this paper, a novel routing schemes with quick response to link failures is first proposed. Based on Dijkstra algorithm, a scalable routing algorithm is proposed to minimize the end-to-end transmission delay. It takes advantage of the predictable constellation trajectory, and changes dynamically according to the changes of network topology. It provides the shortest routing path and an alternative path simultaneously. When a link failure is detected by one satellite, notification packets will be sent to its neighbors for adjustment to the alternative routing path. Notification packets also will be sent to the head node for the recalculation of routing table. Finally, extensive simulations have been conducted, and the results show that the proposed scheme is able to produce desired performance.

关键词： Satellites Network topology Heuristic algorithms Dynamics Low earth orbit satellites Packet loss Routing

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Privacy Preserving OpenPGP Public Key Distribution with Spamming Resistance 17th

Privacy Preserving OpenPGP Public Key Distribution with Spam...

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17th International Conference on information security and Cryptology, Inscrypt 2021

作者： Li, Wenyuan Wang, Wei Lin, Jingqiang Wang, Qiongxiao Wang, Wenjie State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100089 China School of Cyber Security University of Chinese Academy of Sciences Beijing100089 China Data Assurance and Communication Security Research Center CAS Beijing100089 China School of Cyber Security University of Science and Technology of China Anhui Hefei230027 China

ISBN: (纸本)9783030883225

OpenPGP public key distribution via Synchronizing KeyServers (SKS) is facing the challenges of user privacy leakage caused by keyword search behaviors and service unavailability of OpenPGP software caused by OpenPGP certificate spamming attack (CVE-2019-13050). Most existing solutions to the problem dispense with the necessary features and functions of SKS or Web of Trust (WoT) for attack mitigation. In this paper, we put forward a solution which is privacy-preserving and spamming-resistant, while maintaining the functionalities of SKS and WoT. Considering the characteristics of our scenario, we protect user privacy by introducing a third-party server, and propose a specific third party-based private set intersection protocol to improve usability of OpenPGP software. Our protocol helps users filter out the required key data by intersection computation between unbalanced sets of keywords. We also propose an enhanced scheme for multi-key query and further privacy protection. We evaluate the usability and privacy of our schemes. Experimental results show that our scheme can largely reduce unnecessary data download with appropriate filter parameters. The proposed solution relies on the security of Elliptic Curve Diffie–Hellman, HMAC-based Key Derivation Function, Bloom filter and symmetric cryptographic encryption to defend against semi-honest adversaries. © 2021, Springer Nature Switzerland AG.

关键词： Search engines

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Cognitive Method Discussion on communication Jamming Intelligent Decision 2020

Cognitive Method Discussion on Communication Jamming Intelli...

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2020 International Conference on Aviation Safety and information technology, ICASIT 2020

作者： Jin, Hu Shen, Weiguo Zhao, Fan Science and Technology on Communication Information Security Control Laboratory Research Institute Jiaxing China Electronic Countermeasure Institute National University of Defense Technology Hefei China

ISBN: (纸本)9781450375764

The application of reconfigurable, programmable and cognitive radio technologies in communication systems has put forward new requirements for communication jamming decision. In this paper, the overall scheme of cognition-based jamming communication jamming decision methods is presented first. Then the method of intelligent communication jamming decision based on reinforcement learning is discussed under the condition of a large number of data samples of the communication signal, and how to build the element library of jamming strategy and how to describe the behavior of communication signal are described in detail. Moreover, the real-time dynamic jamming effect evaluation method based on target communication signal behavior learning is also discussed. As a result, an online, self-learning and self-optimizing cognitive jamming closed-loop is realized. © 2020 ACM.

关键词： Reinforcement learning

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BADROBOT: JAILBREAKING EMBODIED LLMS IN THE PHYSICAL WORLD

arXiv

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arXiv 2024年

作者： Zhang, Hangtao Zhu, Chenyu Wang, Xianlong Zhou, Ziqi Yin, Changgan Li, Minghui Xue, Lulu Wang, Yichen Hu, Shengshan Liu, Aishan Guo, Peijin Zhang, Leo Yu National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China Beihang University China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia

Embodied AI represents systems where AI is integrated into physical entities. Large Language Model (LLM), which exhibits powerful language understanding abilities, has been extensively employed in embodied AI by facilitating sophisticated task planning. However, a critical safety issue remains overlooked: could these embodied LLMs perpetrate harmful behaviors? In response, we introduce BADROBOT, a novel attack paradigm aiming to make embodied LLMs violate safety and ethical constraints through typical voice-based user-system interactions. Specifically, three vulnerabilities are exploited to achieve this type of attack: (i) manipulation of LLMs within robotic systems, (ii) misalignment between linguistic outputs and physical actions, and (iii) unintentional hazardous behaviors caused by world knowledge’s flaws. Furthermore, we construct a benchmark of various malicious physical action queries to evaluate BADROBOT’s attack performance. Based on this benchmark, extensive experiments against existing prominent embodied LLM frameworks (e.g., Voxposer, Code as Policies, and ProgPrompt) demonstrate the effectiveness of our BADROBOT. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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Integrating Parafac and Pso Fitting Model: A New View into Fluorescence Spectroscopic Analysis for Adulterant Quantification of Lubricant Oil

SSRN

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SSRN 2024年

作者： Zhang, Lujun Cai, Nuo Wang, Yan Fan, Xinmin Gao, Juanjuan Gao, Jin Li, Sensen Lan, Christopher Q. Xiaodong, Huang Wang, Chunyan Department of Physics and Electronic Information Weifang University Weifang261061 China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin300308 China Department of Chemical & Biological Engineering University of Ottawa OttawaONK1N 6N5 Canada

The adulteration of high-quality engine lubricants with inferior, dubious alternatives or reclaimed oils presents a significant challenge, necessitating the development of precise and rapid detection methodologies. This study introduces a novel analytical approach of excitation-emission matrix fluorescence (EEMF) spectroscopy paired with parallel factor analysis (PARAFAC) for the quantification of adulterants within adulterated lubricant samples. A fitting model is introduced to establish a correlation between the PARAFAC component scores of pure adulterants and those of adulterated samples. Furthermore, particle swarm optimization (PSO) is employed to refine the fitting parameters within this model, enabling the determination of individual adulterant' relative quantities in adulterated samples. This methodology not only broadens the application of EEMF combined with PARAFAC for adulteration quantification but also shows potential as a universal quantitative analysis tool for diverse complex fluorophobic mixtures. © 2024, The Authors. All rights reserved.

关键词： Fluorescence

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On Characterization of Transparency Order for (n, m)-functions 17th

On Characterization of Transparency Order for (n, m)-functi...

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17th International Conference on information security and Cryptology, Inscrypt 2021

作者： Zhou, Yu Wei, Yongzhuang Zhang, Hailong Li, Luyang Pasalic, Enes Wu, Wenling Science and Technology on Communication Security Laboratory Chengdu610041 China Guilin University of Electronic Technology Guilin541004 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China National Engineering Laboratory for Wireless Security Xi’an University of Post and Telecommunications Xi’an710061 China University of Primorska FAMNIT & IAM Koper Slovenia TCA Laboratory SKLCS Institute of Software Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9783030883225

The transparency order (denoted by TO ) is a useful measure of the robustness of (n, m)-functions (cryptographic S-boxes as mappings from GF(2 )n to GF(2 )m ) to multi-bits Differential Power Analysis (DPA). An improved version of transparency order (denoted by RTO ), based on the use of cross-correlation coefficients, was also introduced recently. For the first time, we resolve this open problem which (n, m)-functions reach the upper bound on TO for odd n (m is a power of 2). We also investigate the tightness of upper and lower bounds related to RTO and derive its relationship to main cryptographic characterizations of (n, m)-functions (such as nonlinearity, the sum-of-square indicator and algebraic immunity). Finally, concerning S-boxes of size 4 × 4, the distributions of RTO for all 302 balanced S-boxes (up to affine equivalence) and 16 equivalence classes of optimal S-boxes are given. © 2021, Springer Nature Switzerland AG.

关键词： Equivalence classes

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Rapid Prediction of EM Scattering from Finite Periodic Structures Using CBFM with ANNs

Rapid Prediction of EM Scattering from Finite Periodic Struc...

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Mingxin Wang Xinlei Chen Fan Gao Hao Meng Wu Yang Weibing Lu College of Electronic and Information Engineering Key Laboratory of Radar Imaging and Microwave Photonics Key Laboratory of Inlet and Exhaust System Technology Nanjing University of Aeronautics and Astronautics Nanjing China State Key Laboratory of Millimeter Waves Southeast University Nanjing China State Key Laboratory of Millimeter Waves School of Information Science and Engineering Southeast University Nanjing China Center for Flexible RF Technology and MOE Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing China Purple Mountain Laboratories Nanjing China

ISBN: (数字)9798350351019

ISBN: (纸本)9798350351026

In this article, the artificial neural networks (ANNs) are combined with the characteristic basis function method (CBFM) to fast predict the electromagnetic scattering from finite periodic structures. The amplitude and the phase of the expansion coefficients of the characteristic basis functions (CBFs) are predicted by two different ANNs. Then, the predicted expansion coefficients are used to calculated the radar cross sections (RCSs) of the finite periodic structures. Numerical results are given to show the performance of the ANN-assisted CBFM.

关键词： Radar cross-sections Electromagnetic scattering Artificial neural networks Antennas and propagation Artificial intelligence Periodic structures

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Semantic and Emotional Dual Channel for Emotion Recognition in Conversation

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IEEE Transactions on Affective Computing 2025年

作者： Yang, Zhenyu Zhang, Zhibo Cheng, Yuhu Zhang, Tong Wang, Xuesong Jinan250353 China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250353 China China University of Mining and Technology Engineering Research Center of Intelligent Control for Underground Space Ministry of Education Xuzhou Key Laboratory of Artificial Intelligence and Big Data School of Information and Control Engineering Xuzhou221116 China South China University of Technology Guangdong Provincial Key Laboratory of Computational Intelligence and Cyberspace Information School of Computer Science and Engineering Guangzhou510006 China Pazhou Lab Guangzhou510335 China Engineering Research Center Ministry of Education on Health Intelligent Perception and Paralleled Digital-Human Guangzhou China

Emotion recognition in conversation (ERC) aims at accurately identifying emotional states expressed in conversational content. Existing ERC methods, although relying on semantic understanding, often encounter challenges when confronted with incomplete or misleading semantic information. In addition, when dealing with the interaction between emotional and semantic information, existing methods are often difficult to effectively distinguish the complex relationship between the two, which affects the accuracy of emotion recognition. To address the problems of semantic misdirection and emotional cross-talk encountered by traditional models when confronted with complex conversational data, we propose a semantic and emotional dual channel (SEDC) strategy for emotion recognition in conversations to process emotional and semantic information independently. Under this strategy, emotion information provides an auxiliary recognition function when the semantics are unclear or lacking, enhancing the accuracy of the model. Our model consists of two modules: the emotion processing module accurately captures the emotional features of each utterance through contrastive learning, and then constructs a dialogue emotion propagation map to simulate the emotional information conveyed in the dialogue;the semantic processing module combines an external knowledge base to enhance the semantic expression of the dialogue through knowledge enhancement strategies. This divide-and-conquer approach allows us to more deeply analyze the emotional and semantic dimensions of complex dialogues. Experimental results on the IEMOCAP, EmoryNLP, MELD, and DailyDialog datasets show that our approach significantly outperforms existing techniques and effectively improves the accuracy of dialogue emotion recognition. Our code is available at https://***/r/SEDC-FCF1. © 2010-2012 IEEE.

关键词： Contrastive Learning

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SAR Image Processing and Target Detection Based on 2D Singularity Power Spectrum in Time-frequency Domain 5

SAR Image Processing and Target Detection Based on 2D Singul...

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5th IEEE International Conference on Signal and Image Processing, ICSIP 2020

作者： Li, Junye Xiong, Gang Huang, Baigang Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China

ISBN: (纸本)9781728168968

A method for SAR image processing and target detection based on two-dimensional singularity power spectrum (2D-SPS) in time-frequency domain is proposed in this paper. Firstly, the two-dimensional pseudo Wigner-Ville distribution (2D-PWVD) is carried out on the SAR image. Then, the two-dimensional singularity power spectrum estimation is performed on the local delay components of 2D-PWVD to obtain the three-dimensional singularity power spectral SAR (SPS-SAR) functions. Furthermore, a novel SAR target detection method based on SPS-SAR is introduced. The proposed methodology is tested on SAR images, both with and without weak targets, from the OpenSAR dataset. Experiment results show that the proposed method performs better than traditional method based on fractal theory, and can achieve higher detection probability in the complex scene with low SNR. It can provide more details for SAR image analysis and offer a new idea for SAR target detection. © 2020 IEEE.

关键词： Power spectrum

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Efficient Wi-Fi AP Localization through Channel Feature Fusion and Anomaly Detection

Efficient Wi-Fi AP Localization through Channel Feature Fusi...

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IEEE Conference on Wireless communications and Networking

作者： Yan Li Jie Yang Shang-Ling Shih Wan-Ting Shih Chao-Kai Wen Shi Jin National Mobile Communications Research Laboratory Southeast University Nanjing China Frontiers Science Center for Mobile Information Communication and Security Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung Taiwan

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

Wi-Fi access point (AP) and IoT device localization are essential for smart home functionalities, including indoor localization and privacy protection. Yet, complex multipath channels in indoor settings often hinder precise localization. To overcome this, we introduce an Artificial Intelligence (AI) technique that amalgamates channel state information from proximate trajectory points, thus elevating the accuracy of line of sight (LoS) angle of arrival (AoA) estimation. Our methodology initiates with an AI-based anomaly detection system to eliminate questionable measurements. Thereafter, our AI-optimized LoS-AoA network proficiently identifies the primary LoS path from the several multipaths detected by the multipath estimation process and autonomously fine-tunes the LoS-AoA estimation. Using simulations in an indoor office environment with Wireless Insite, our results reveal that our approach considerably improves LoS-AoA estimations, even under challenging indoor scenarios. Notably, our technique enhanced AP positioning accuracy in 68% of instances, reducing a 2-meter error to 0.6 meters, and in 95% of instances, cutting down a 10-meter error to 2 meters when measured against top benchmarks.

关键词： Location awareness Meters Wireless communication Accuracy Estimation Smart homes Trajectory

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