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IEEE Open Journal of the Communications Society 2024年 5卷 3568-3580页

作者： Zahoor, Amina Mahmood, Khalid Saleem, Muhammad Asad Badar, Hafiz Muhammad Sanaullah Le, Tuan-Vinh Das, Ashok Kumar Department of Computer Science Sahiwal57000 Pakistan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Emerson University Multan Department of Emerging Computing Technologies Multan61000 Pakistan Fu Jen Catholic University Bachelor's Program of Artificial Intelligence and Information Security New Taipei City24206 Taiwan International Institute of Information Technology Hyderabad Center for Security Theory and Algorithmic Research Hyderabad500032 India

The Smart Power Grid (SPG) is pivotal in orchestrating and managing demand response in contemporary smart cities, leveraging the prowess of information and Communication Technologies (ICTs). Within the immersive SPG environment, the ubiquitous deployment of smart meters stands as a testament to their paramount importance in the realm of vigilant monitoring and oversight. These smart meters are installed on high-tension electricity lines and transmit information about electricity outages and other issues to the utility center. To access services from utility centers, smart meters need to communicate securely over a public channel, even though the network itself is insecure. However, potential attacks from adversaries ( Ad) can exploit this communication. Therefore, protecting this communication is of utmost importance. Several privacy-preserving authentication protocols designed for SPG have been introduced in the literature. Nevertheless, a significant number of these protocols exhibit vulnerabilities to diverse security attacks. This article introduces a lightweight and anonymous authentication protocol specifically designed to address these concerns in the SPG environment. Our protocol ensures both security and efficiency, surpassing other comparable protocols in terms of its lightweight nature. By employing both formal and informal analysis, we showcase the robustness of our protocol against significant attacks while remaining lightweight. The proposed protocol provides added security features and incurs 23.8879% lower computation cost than related protocols. Consequently, our protocol is highly suitable for implementation in the SPG system. © 2020 IEEE.

关键词： Hash functions

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DeepRisk:A deep learning approach for genome-wide assessment of common disease risk

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Fundamental Research 2024年第4期4卷 752-760页

作者： Jiajie Peng Zhijie Bao Jingyi Lia Ruijiang Han Yuxian Wang Lu Han Jinghao Peng Tao Wang Jianye Hao Zhongyu Wei Xuequn Shang AI for Science Interdisciplinary Research Center Schoolof Computer ScienceNorthwestern Polyechnical UniversityXi'an 129China Key Laboratoryof Bg Data Sorage and Management Northwestern Polytechnical UniversityMinisty of Industy and Information TechnologyX'an 129Chin College of Intelligence and Computing Tianjin UniversityTianjin 300072China School of Data Science Fudan UniversityShanghai 200433China Research and Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen 518000China

The potential for being able to identify individuals at high disease risk solely based on genotype data has garnered significant *** widely applied,traditional polygenic risk scoring methods fall short,as they are built on additive models that fail to capture the intricate associations among single nucleotide polymorphisms(SNPs).This presents a limitation,as genetic diseases often arise from complex interactions between multiple *** address this challenge,we developed DeepRisk,a biological knowledge-driven deep learning method for modeling these complex,nonlinear associations among SNPs,to provide a more effective method for scoring the risk of common diseases with genome-wide genotype *** demonstrated that DeepRisk outperforms existing PRs-based methods in identifying individuals at high risk for four common diseases:Alzheimer's disease,inflammatory bowel disease,type 2diabetes,and breast cancer.

关键词： Disease risk prediction Deep learning Polygenic risk score Common disease risk Disease prevention

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CroPrompt: Cross-task Interactive Prompting for Zero-shot Spoken Language Understanding

CroPrompt: Cross-task Interactive Prompting for Zero-shot Sp...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Qin, Libo Wei, Fuxuan Chen, Qiguang Zhou, Jingxuan Huang, Shijue Si, Jiasheng Lu, Wenpeng Che, Wanxiang School of Computer Science and Engineering Central South University China Key Laboratory of Data Intelligence and Advanced Computing in Provincial Universities Soochow University China Research Center for Social Computing and Information Retrieval Harbin Institute of Technology China Harbin Institute of Technology Shenzhen China Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology Shandong Academy of Sciences China

ISBN: (纸本)9798350368741

Slot filling and intent detection are two highly correlated tasks in spoken language understanding (SLU). Recent SLU research attempts to explore zero-shot prompting techniques in large language models to alleviate the data scarcity problem. Nevertheless, the existing prompting work ignores the cross-task interaction information for SLU, which leads to sub-optimal performance. To solve this problem, we present the pioneering work of Cross-task Interactive Prompting (CroPrompt) for SLU, which enables the model to interactively leverage the information exchange across the correlated tasks in SLU. Additionally, we further introduce a multi-task self-consistency mechanism to mitigate the error propagation caused by the intent information injection. We conduct extensive experiments on the standard SLU benchmark and the results reveal that CroPrompt consistently outperforms the existing prompting approaches. In addition, the multi-task self-consistency mechanism can effectively ease the error propagation issue, thereby enhancing the performance. We hope this work can inspire more research on cross-task prompting for SLU. © 2025 IEEE.

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Defending Against Vishing Attacks: A Comprehensive Review for Prevention and Mitigation Techniques

Defending Against Vishing Attacks: A Comprehensive Review fo...

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International Conference on Recent Developments in Cyber Security, ReDCySec 2023

作者： Ashfaq, Shaikh Chandre, Pankaj Pathan, Shafi Mande, Uday Nimbalkar, Madhukar Mahalle, Parikshit Information Technology Department M H Saboo Siddik College of Engineering Mumbai India Computer Science and Engineering Department MIT School of Computing MIT Art Design and Technology University Loni Kalbhor Pune India Artificial Intelligence and Data Science Department Vishwakarma Institute of Information Technology Kondhwa Pune India

ISBN: (纸本)9789819998104

Vishing attacks, or voice phishing attacks, are a type of social engineering attack in which attackers use voice communication channels, such as phone calls, to trick victims into divulging sensitive information or performing actions that compromise their security. Vishing attacks have become increasingly common in recent years and can have severe consequences for individuals, businesses, and organizations. In this review, we examine various prevention and mitigation techniques that can be used to defend against vishing attacks. We start by discussing the common tactics used by attackers and how they exploit vulnerabilities in human behaviour to achieve their goals. We then present an overview of different prevention and mitigation techniques, including education and awareness campaigns, technical solutions such as authentication mechanisms and policy-based approaches. We also evaluate the effectiveness of different techniques, highlighting their strengths and weaknesses, and provide guidance on how to implement a comprehensive vishing defence strategy. Finally, we discuss emerging trends and challenges in vishing attacks and defence, such as the use of artificial intelligence and deepfake technology, and suggest directions for future research and development. Overall, this review provides a comprehensive and up-to-date overview of the current state of vishing attacks and defence, and should be of interest to researchers, practitioners, and individuals who want to enhance their knowledge and understanding of this important topic. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Artificial intelligence

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Integrating Artificial Intelligence and Multiple Intelligences for Advanced Educational Models

Integrating Artificial Intelligence and Multiple Intelligenc...

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2024 International Conference on Electrical, Electronics and computing Technologies, ICEECT 2024

作者： Palarimath, Suresh Maran, Pyingkodi Venkateswaran, R. Wilfred Blessing, N.R. Shiny, K.V. Renuga, S. University of Technology and Applied Sciences College of Computing and Information Sciences Salalah Oman Kongu Engineering College Department of Computer Applications Erode India University of Technology and Applied Sciences College of Computing and Information Sciences Ibri Oman Bharath Institute of Higher Education and Research Department of Computer Science and Engineering Chennai India Panimalar Engineering College Department of Artificial Intelligence and Data Science Chennai India

ISBN: (纸本)9798350378092

The aim of educational innovation is to foster students' creative and problem-solving skills via the integration of several disciplines, including science, technology, engineering, art, and mathematics. Efficiently identifying and fostering the various abilities of pupils continues to be a crucial obstacle. This research presents a sophisticated educational approach that combines the notion of multiple intelligences with artificial intelligence (AI) technology to tackle this problem. This concept improves the teaching environment by including intelligent auxiliary services for instructors and students via the use of smart speech and picture interaction. Artificial intelligence (AI) integrated into the multiple intelligence's framework enables the ability to observe, analyze, and implement personalized teaching tactics in real-time using machine learning. The suggested AI-assisted education paradigm aims to enhance teacher-student interactions and facilitate personalized instruction. The study provides evidence that this technique successfully facilitates personalized and captivating learning experiences, promoting students' diverse talents and augmenting their creativity and problem-solving capabilities. This approach seeks to fundamentally transform conventional educational techniques by addressing the disparity between existing educational practices and the future requirements of the workforce. © 2024 IEEE.

关键词： Adversarial machine learning

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Gradient-Based Differential kWTA Network With Application to Competitive Coordination of Multiple Robots

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IEEE/CAA Journal of Automatica Sinica 2022年第8期9卷 1452-1463页

作者： Mei Liu Xiaoyan Zhang Mingsheng Shang Long Jin School of Information Science and Engineering Lanzhou UniversityLanzhou 730000 State Key Laboratory of Tibetan Intelligent Information Processing and Application Xining 810016China Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing 400714China Shenzhen Research Institute Lanzhou UniversityShenzhen 518063China

Aiming at the k-winners-take-all(kWTA)operation,this paper proposes a gradient-based differential kWTA(GDk WTA)*** obtaining the network,theorems and related proofs are provided to guarantee the exponential convergence and noise resistance of the proposed GD-kWTA ***,numerical simulations are conducted to substantiate the preferable performance of the proposed network as compared with the traditional ***,the GD-k WTA network,backed with a consensus filter,is utilized as a robust control scheme for modeling the competition behavior in the multi-robot coordination,thereby further demonstrating its effectiveness and feasibility.

关键词： Consensus filter k-winners-take-all(kWTA) multirobot coordination noise resistance

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Joint Design of Trajectory and Near-Field Beamforming for STAR-RIS-Enabled ISAC 16

Joint Design of Trajectory and Near-Field Beamforming for ST...

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16th International Conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Huang, Qiulei Song, Zhaohui Xiong, Zehui Xu, Guanjun Zhao, Nan Niyato, Dusit School of Information and Communication Engineering Dalian University of Technology Dalian116024 China Space Information Research Institute Hangzhou Dianzi University Hangzhou310018 China Singapore University of Technology and Design 487372 Singapore College of Computing and Data Science Nanyang Technological University 639798 Singapore

ISBN: (纸本)9798350390643

Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) can be assembled in the air-ground integrated sensing and communication (ISAC) to further enhance the performance. However, the near-field effect should be further considered with higher carrier frequency and increasing number of STAR-RIS elements. In this paper, we propose a STAR-RIS enabled air-ground near-field ISAC scheme, where the unmanned aerial vehicle (UAV) is deployed as a mobile base station and the semi-passive architecture is adopted to alleviate the severe path loss. We maximize the weighted sum rate to guarantee both the communication and sensing by modifying the beamforming vectors, the reflection/transmission matrices and the hovering location of UAV to match the near-field effect. To address this challenge, we first divide it into three subproblems, which are recast into convex ones by the semidefinite relaxation and successive convex approximation. Finally, we develop an alternate algorithm to iteratively solve them. Simulation results are shown to demonstrate the superiority and validity of the proposed scheme. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Beamforming and Trajectory Design for Active IRS-Assisted UAV Relaying Systems 35

Beamforming and Trajectory Design for Active IRS-Assisted UA...

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Huang, Qiulei Song, Zhaohui Xiong, Zehui Xu, Guanjun Zhao, Nan Niyato, Dusit Dalian University of Technology School of Information and Communication Engineering Dalian116024 China Space Information Research Institute Hangzhou Dianzi University Hangzhou310018 China Singapore University of Technology and Design 487372 Singapore Nanyang Technological University College of Computing and Data Science 639798 Singapore

ISBN: (纸本)9798350362244

Intelligent reflecting surface (IRS) can reconfigure the channel conditions, while the passive beamforming gain is limited by the severe double path-loss effect. Fortunately, active IRS (AIRS) is emerging to tackle obstacles by simultaneously adjusting the phases and amplitudes. In this paper, we propose an AIRS-assisted unmanned aerial vehicle (UAV)-relaying scheme, where the AIRS is equipped on the UAV to reflect the signal from the ground base station (GBS) to users via non-orthogonal multiple access. We jointly adjust transmit beamforming, reflection matrix and UAV trajectory to maximize the average sum rate, which is non-convex. Thus, the problem is decomposed into three subproblems via block coordinate descent. The beamforming optimization is solved through semidefinite relaxation. Then, the reflection matrix of AIRS and UAV trajectory are jointly optimized via successive convex approximation. Finally, we design an iterative algorithm to effectively tackle the original problem. Simulation results are shown to verify the performance of the designed scheme. © 2024 IEEE.

关键词： Beamforming

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Evolving Effective Drug Therapies with Multi-objective Genetic Algorithm 16th

Evolving Effective Drug Therapies with Multi-objective Genet...

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16th International Conference on Genetic and Evolutionary computing, ICGEC 2024

作者： Zhang, Tiancong Weng, Shaowei Chu, Shu-Chuan Nguyen, Trong-The Dao, Thi-Kien School of Computing and Information Science Fuzhou Institute of Technology Fuzhou350506 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China College of Computer Science and Engineering Shandong University of Science and Technology Qing-dao266590 China University of Information Technology Ho Chi Minh City700000 Viet Nam

ISBN: (纸本)9789819615346

The development of effective drug therapies is a complex and multifaceted problem involving various biological, chemical, and computational challenges. Traditional drug development methods are often time-consuming and costly, necessitating innovative approaches. Multi-objective genetic algorithms (MOGAs) have emerged as a powerful tool for optimizing drug design by simultaneously considering multiple conflicting objectives, such as efficacy, safety, and cost. This paper reviews the application of MOGAs in drug discovery, highlighting their principles, advantages, and case studies, and discussing future directions in the field. Enhancing MOGAs in drug discovery are also outlined, emphasizing the integration with machine learning, advancements in computational infrastructure, and the potential for personalized medicine. The paper concludes by affirming the significant promise of MOGAs in accelerating the development of safe and effective drug therapies, thereby addressing critical needs in modern pharmacology. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Drug discovery

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Analysis of Schema Formation in Genetic Algorithms: A Review 16th

Analysis of Schema Formation in Genetic Algorithms: A Review

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16th International Conference on Genetic and Evolutionary computing, ICGEC 2024

作者： Zhang, Tiancong Chu, Shu-Chuan Weng, Shaowei Dao, Thi-Kien Nguyen, Trong-The School of Computing and Information Science Fuzhou Institute of Technology Fuzhou350506 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350118 China College of Computer Science and Engineering Shandong University of Science and Technology Qing-Dao266590 China University of Information Technology Ho Chi Minh City700000 Viet Nam

ISBN: (纸本)9789819615346

Genetic algorithms (GAs) are a powerful class of optimization techniques inspired by the principles of natural selection and genetics. One of the theoretical cornerstones of GAs is schema theory, which provides a framework for understanding how building blocks of solutions, known as schemas, are propagated and combined through generations. This review paper aims to provide a comprehensive theoretical analysis of schema formation in genetic algorithms. It delves into the foundational principles of schema theory, including the schema theorem and its implications for the efficiency and behavior of GAs. The paper also explores advanced topics such as schema disruption mechanisms, the impact of multimodal and epistatic fitness landscapes, and the integration of schema theory with hybrid approaches. Additionally, practical implications and real-world applications of schema theory are discussed through case studies and best practices. By elucidating the mechanisms of schema formation and their influence on genetic algorithm performance, this review seeks to offer valuable insights and directions for future research. Ultimately, this theoretical exploration aims to bridge the gap between abstract concepts and practical application, contributing to the advancement of genetic algorithms as robust optimization tools. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Genetic algorithms

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