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Annual Hawaii International Conference on System Sciences (HICSS)

作者： Qing Hu Chenghong Zhang Zhengchuan Xu Iowa State University USA Fudan University China

While research on computer hackers has a long history, most of the studies in the past three decades have been qualitative and anecdotal in nature. The question why young computer talents become computer hackers remains. Based on the results of a case study, we conducted a survey based empirical study using the scenario based research methodology. Statistical analyses show that three primary factors contribute to the likelihood of talents becoming hackers: moral beliefs, self-control, and time spent on computer games vs. sports activities. Our results indicate that individuals who have strong moral beliefs against hacking activities, strong abilities to control temper, and spend more time in sports than on computer games are less likely to be involved in computer hacking activities. The significant implications of these findings for scholars, educators, and policy makers are discussed and future research directions are explored.

关键词： computers computer hacking computer crime Educational institutions Ethics Games Programming

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Consecutive Load Redistribution Attack Without Line Admittance Information

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IEEE TRANSACTIONS ON SMART GRID 2025年第2期16卷 1762-1774页

作者： Liu, Zelin Liu, Tao Song, Yue Hill, David J. Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China Univ Hong Kong Shenzhen HKU Shenzhen Inst Res & Innovat Shenzhen 518057 Peoples R China Tongji Univ Dept Control Sci & Engn Natl Key Lab Autonomous Intelligent Unmanned Syst Shanghai 201804 Peoples R China Tongji Univ Shanghai Inst Intelligent Sci & Technol Shanghai 201804 Peoples R China Monash Univ Dept Elect & Comp Syst Engn Clayton Vic 3800 Australia

This paper develops a novel method for launching a stealthy Load Redistribution Attack (LRA) without requiring knowledge of the power network's admittance matrix. Initially, equations involving the admittance matrix in the conventional LRA model are substituted with equivalent conditions utilizing the Power Transfer Distribution Factor (PTDF) matrix. Subsequently, a ridge regression approach is applied to estimate the PTDF matrix based on the hijacked Supervisory Control and Data Acquisition (SCADA) data. To maximize the damage inflicted by the proposed LRA, a consecutively small-scale attack strategy is designed to gather more informative data, and the PTDF matrix estimation is then updated accordingly to enhance its accuracy. Ultimately, a stealthy LRA is completed using the final PTDF matrix estimation. The rationale behind employing the PTDF matrix estimation in the proposed method, as opposed to the estimation of the admittance matrix, is that the latter requires information on bus voltage phase angles not supplied by the SCADA system. Simulations on the IEEE 30-bus and IEEE 118-bus system, without admittance information for grid transmission lines, demonstrate the accuracy and efficacy of the proposed attack.

关键词： Transmission line matrix methods Admittance Generators Power transmission lines Transmission line measurements Costs Indexes computer hacking Phasor measurement units Load flow False data injection attack load redistribution attack ridge regression power transfer distribution factor

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ABDM: Anonymity-Based Big Data Management for Protecting Healthcare Data from Privacy Breach

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IEEE NETWORK 2025年第1期39卷 298-305页

作者： Kim, Jinyong Jeong, Jaehoon Kim, Jeonghyeon Kim, Joomin Sungkyunkwan Univ Dept Comp Sci & Engn Suwon 16419 Gyeonggi Do South Korea Huinno Co Ltd Seoul 06011 South Korea

As the healthcare industry has continued to develop and the medical data becomes digitized, the risk of data leakage from attacks grows. All medical data is encrypted and stored to prevent data leakage, but from big data perspective, it is inefficient because the encryption of this medical data lowers the big data processing performance. To address this problem, this paper proposes an Anonymity-based Big Data Management (ABDM) for protecting healthcare data from privacy breach without compromising on performance. The idea of ABDM is to separate and store identity data and healthcare data in databases on different cloud servers. By storing the identity data and healthcare data separately in databases on different cloud servers, hackers are unable to identify whose healthcare data is obtained until they obtain both the identity data and healthcare data. Through experiments in a public cloud, ABDM outperforms existing healthcare data management systems by two times speed.

关键词： Medical services Databases computer hacking Encryption Cryptography Big Data Cloud computing Data privacy Servers Medical diagnostic imaging

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Robust Intrusion Detection With Combinatorial Fusion and Generative Artificial Intelligence

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computer 2025年第4期58卷 46-57页

作者： Owusu, Evans Mapkar, Mariyam Rahouti, Mohamed Verma, Dinesh C. Fordham Univ Dept Comp & Informat Sci New York NY 10458 USA IBM Thomas J Watson Res Ctr Yorktown Hts NY 10598 USA

This article proposes an advanced intrusion detection system that combines combinatorial fusion analysis with generative artificial intelligence to improve anomaly detection in intelligent systems. It addresses challe... 详细信息

关键词： Generative AI computer hacking Intrusion detection Intelligent systems Anomaly detection

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Event-Triggered Resilient Control for Interconnected Servo Systems Under Malicious Attacks

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IEEE INTERNET OF THINGS JOURNAL 2025年第6期12卷 7590-7598页

作者： Miao, Zhenhai Li, Meng Chen, Yong Zhang, Meng Univ Elect Sci & Technol China Sch Automat Engn Chengdu 611731 Peoples R China Jiaotong Univ Sch Cyber Sci & Engn Xian 710049 Peoples R China

This article investigates the tracking control of interconnected servo systems, where Denial-of-Service attacks and false-data-injection attacks are considered. In order to ensure the control performance and security, a sliding mode tracking control scheme based on event triggered is designed. First, a mathematical model of the interconnected servo system subjected to hacking is established. Then, an adaptive sliding mode state observer is proposed to cope with the malicious attack. Third, a higher order sliding mode consistent tracking control method is proposed and the convergence of the tracking error is demonstrated. In addition, an event-triggered mechanism is introduced to save communication resources. Finally, simulation results demonstrate the effectiveness of the proposed algorithm.

关键词： Event detection Multi-agent systems Motors computer hacking Security Servomotors Actuators Mathematical models Interconnected systems Attack event triggered interconnected servo systems observer sliding mode sliding mode

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MAD-CTI: Cyber Threat Intelligence Analysis of the Dark Web Using a Multi-Agent Framework

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IEEE ACCESS 2025年 13卷 40158-40168页

作者： Shah, Sayuj Madisetti, Vijay K. Georgia Inst Technol Coll Comp Atlanta GA 30332 USA Georgia Inst Technol Sch Cybersecur & Privacy Atlanta GA 30332 USA

The dark web is a host to illicit activities where hacker forums, blogs, and articles provide significant insights into Cyber Threat Intelligence (CTI) that are frequently unavailable on the surface web. The increasing incidence of security breaches underscores the necessity for advanced CTI solutions to defend against emerging threats. This paper introduces MAD-CTI, a novel multi-agent framework based on Large Language Models (LLM) designed to extract insights from dark web sources. It independently scrapes, analyzes, and classifies content related to vulnerabilities, malware, and hacking, by leveraging a multi-agent architecture to improve efficiency, scalability, and consistency. By utilizing state-of-the-art LLM models and agents, we demonstrate how organizations can adopt this methodology to enhance the accuracy and efficiency of CTI.

关键词： Dark Web Cyber threat intelligence Malware Translation Oral communication computer hacking Blogs Accuracy Large language models computer architecture Cybersecurity defense cyber threat intelligence dark web hack large language models (LLMs) malware multi-agent systems (MAS) predictive intelligence vulnerability

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Enhancing Networked Control System Resilience to TCP/IP Protocol DoS Attacks: Performance Analysis and Intelligent Controller Design

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 6608-6618页

作者： Cai, Xiao Sun, Yanbin Shi, Kaibo Xie, Xiangpeng Soh, Yeng Chai Qiao, Cheng Tian, Zhihong Guangzhou Univ Cyberspace Inst Adv Technol Guangzhou 510006 Peoples R China Lion Rock Labs Cyberspace Secur Hong Kong Peoples R China Chengdu Univ Sch Informat Sci & Engn Chengdu 610106 Sichuan Peoples R China Nanjing Univ Posts & Telecommun Sch Internet Things Nanjing 210023 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

This study examines denial-of-service (DoS) attacks on networked control systems (NCSs) caused by TCP/IP protocol vulnerabilities. It conducts a comprehensive analysis of hacker tactics to uncover vulnerability exploitation techniques. The research reformulates the performance error estimation (PEE) problem, framing it as a search for ellipsoid constraints within a $P$ -dependent set. It introduces the Higher-Order Weight Method (HOWM) to optimize sampling intervals, leveraging the unique properties of zero-order-hold sampling. The study enhances Lyapunov-Krasovskii functions (LKFs) using HOWM by partitioning integral terms and applying quadratic scaling to optimize control algorithms, thereby reducing conservatism and tightening upper-bound criteria. Additionally, it proposes an innovative Integral Event-Triggered Control (IETC) strategy for estimating system performance errors. The performance of the proposed control algorithm is rigorously evaluated through simulations on a complex 2-degree of freedom (DoF) helicopter system (HS). Note to Practitioners-This study delves into DoS attacks targeting NCSs due to TCP/IP protocol vulnerabilities. It conducts an exhaustive analysis of hacker tactics to uncover techniques used to exploit these vulnerabilities. The research reframes the PEE problem, casting it as a search for ellipsoid constraints within a $P$ -dependent ellipsoidal set. It introduces the HOWM to optimize sampling intervals, leveraging the unique characteristics of zero-order-hold sampling. Additionally, the study enhances LKFs using HOWM by partitioning integral terms and applying quadratic scaling to optimize the control algorithm, thereby reducing conservatism and tightening upper-bound criteria. Moreover, it introduces an innovative IETC strategy for estimating system performance errors. The performance of the proposed control algorithm is rigorously evaluated through simulations on a complex 2-DoF HS.

关键词： Protocols computer hacking Security Throughput System performance Networked control systems Data communication Lyapunov-Krasovskii function cyber attacks event-triggered control helicopter system networked control system

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Security Vulnerability (Backdoor Trojan) During Machine Learning Accelerator Design Phases

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IT PROFESSIONAL 2025年第1期27卷 65-72页

作者： Sengupta, Anirban Anshul, Aditya Chourasia, Vishal Bhui, Nabendu Indian Inst Technol Indore Comp Sci & Engn Indore 453552 India Indian Inst Technol Indore Comp Sci & Engn CSE Indore 453552 India Indian Inst Technol Indore Indore 453552 India

This article provides a broad perspective for readers on how security vulnerabilities can be exploited by hackers during the design of machine learning (ML) accelerators such as convolutional neural networks. The article also highlights different ML accelerators from academia and industry, along with various design stages where Trojan attacks can be launched. It also provides a broad spectrum review of existing literatures on how Trojan attacks can be injected, triggered, and exploited to cause various payloads, such as degraded performance, denial of service, data damage, and power/battery exhaustion, on ML accelerators. The article also discusses possible detection/mitigation techniques from the literature for some of the attacks and recommends a possible solution.

关键词： Industries Reviews computer hacking Machine learning Trojan horses Convolutional neural networks Payloads

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A Decentralized Reputation Management Model for Enhanced IoV Networks With 5G Broadcast Services

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IEEE TRANSACTIONS ON BROADCASTING 2025年第1期71卷 63-73页

作者： Zuo, Jinxin Wang, Ziping Guo, Chenqing Xie, Weixuan Wu, Hao Yu, Peng Lu, Yueming Beijing Univ Posts & Telecommun Sch Cyberspace Secur Minist Educ Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Key Lab Trustworthy Distributed Comp & Serv Beijing 100876 Peoples R China CNCERT CC Beijing 100094 Peoples R China Beijing Univ Posts & Telecommun Sch Informat & Commun Engn Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

This paper investigates the challenges of data trust sharing faced by Internet of Vehicles (IoV) network with 5G broadcast services. Particularly we develop a decentralized IoV reputation management model with spatiotemporal feature perception fusion (RMM-STFP) based on blockchain. The proposed reputation evaluation method evaluates the reputation value of nodes from the two aspects of time continuity and spatial transitivity and thus improves the identification accuracy of malicious nodes. To further accelerate the dissemination of reputation data, we have constructed a blockchain-based management storage system, where PBFT consensus scheme combines reputation and Bayesian inference. Finally, numerical results are given to justify the superiority of our proposed scheme. When proportion of malicious nodes reaches 45%, the accuracy of our proposed method is 94.5%, and the suppression rate of malicious messages is 83%. Moreover, compared with the traditional PBFT consensus scheme, the consensus delay and communication overhead are reduced by 87.57% and 78.45%, respectively, and the transaction throughput is increased by 70.65%.

关键词： 5G mobile communication Blockchains Accuracy Spatiotemporal phenomena Broadcasting computer hacking Roads Internet of Vehicles 5G broadcast services reputation evaluation spatiotemporal features blockchain reputation management

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Differential Privacy, Firm-Level Data, and the Binomial Pathology

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IEEE SECURITY & PRIVACY 2025年第1期23卷 8-16页

作者： Clark, David D. Garfinkel, Simson Claffy, K. C. MIT Comp Sci & Artificial Intelligence Lab Cambridge MA 02139 USA BasisTech Technol Accelerator Somerville MA 02144 USA Ctr Appl Internet Data Anal La Jolla CA 92093 USA

Differential privacy (DP) is a privacy-enhancing technology that is increasingly being used by policy makers in the United States and Europe, but it is not well suited to protect corporate proprietary information that... 详细信息

关键词： Data privacy Noise Databases Protection Data models computer hacking Accuracy

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