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13th International Conference on Ambient systems, networks and Technologies, ANT 2022 / 5th International Conference on Emerging Data and Industry 4.0, EDI40 2022

作者： Shatnawi, Ahmed S. Yassen, Qussai Yateem, Abdulrahman Department of Computer Information Systems Jordan University of since and Technology Irbid Jordan Department of Network and Security Engineering Jordan University of since and Technology Irbid Jordan

In the past decade, mobile devices became necessary for modern civilization and contributed directly to its development stages in defining mobile information access. Nonetheless, along with these rapid developments in modern mobile devices, security issues rise dramatically, and malware is the most concerning of all. Therefore, many studies and research are still trending in this spectrum, using Machine Learning approaches to prevent and reduce malware's impact. This paper seeks to add to what is already a foundation of various malware detection efforts by presenting a static base classification approach for malware detection based on android permissions and API calls. This approach is based on three well-known Machine Learning algorithms, Support Vector Machines (SVM), K-nearest neighbors (KNN), and Naive Bayes (NB) against a comprehensive new Android malware dataset (CICInvesAndMal2019), in pursuit of achieving high malware detection rates and contribution to the efforts and studies in protecting the development of mobile information. access. © 2022 Elsevier B.V.. All rights reserved.

关键词： Android Malware CICInves KNN Machine Learning Mal2019 Dataset Malware Detection Mobile Information Access Naive Bayes SVM

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Enhancing MANETs Security Against Black Hole Attacks through Time-Based Node Analysis in AOMDV Protocol

Enhancing MANETs Security Against Black Hole Attacks through...

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Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Abdullah A. Naji Mogeeb A. Saeed Ammar H. Almagashi Alaa M. Ahmed Hashem S. Al-Atefi Mohammed N. Khaled Olayan M. Rashed Computer Network & Distributed Systems Department Al-Saeed Faculty Of Engineering &IT Taiz University Computer Networks & Distributed Systems Al-Saeed Faculty Of Engineering &IT Taiz University Computer Center & Information Technology Taiz University

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

Mobile ad-hoc networks (MANETs) rely solely on direct node communication and function without a fixed infrastructure. Due to their decentralized design, they are susceptible to numerous security risks, with black hole attacks posing significant threats to routing integrity and confidentiality. This paper proposes a technique to enhance the Ad hoc On-Demand Multi-path Distance Vector (AOMDV) routing protocol's security against black hole attacks. The method involves a time-based reply message analysis to identify and mitigate malicious nodes. This algorithm improves the protocol's ability to detect and prevent black hole attacks by closely analyzing response time differences between malicious and normal nodes. The results of the simulation show that the suggested solution greatly enhances network performance by lowering the Routing Overhead Ratio from 1388.04% to 0.73% and the Packet Loss Rate from 74% to 11% while keeping a high Packet Delivery Ratio—up to 93% in different scenarios. These enhancements sustain strong data transmission in dynamic MANET environments, supporting network integrity and reliability.

关键词： Protocols Packet loss Routing Ad hoc networks Vectors Security Time factors

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Conjectural Online Learning with First-order Beliefs in Asymmetric Information Stochastic Games

Conjectural Online Learning with First-order Beliefs in Asym...

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IEEE Conference on Decision and Control

作者： Tao Li Kim Hammar Rolf Stadler Quanyan Zhu Department of Electrical and Computer Engineering New York University USA Division of Network and Systems Engineering KTH Royal Institute of Technology Sweden

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Asymmetric information stochastic games (AISGs) arise in many complex socio-technical systems, such as cyberphysical systems and IT infrastructures. Existing computational methods for AISGs are primarily offline and can not adapt to equilibrium deviations. Further, current methods are limited to particular information structures to avoid belief hierarchies. Considering these limitations, we propose conjectural online learning (COL), an online learning method under generic information structures in AISGs. COL uses a forecaster-actorcritic (FAC) architecture, where subjective forecasts are used to conjecture the opponents’ strategies within a lookahead horizon, and Bayesian learning is used to calibrate the conjectures. To adapt strategies to nonstationary environments based on information feedback, COL uses online rollout with cost function approximation (actor-critic). We prove that the conjectures produced by COL are asymptotically consistent with the information feedback in the sense of a relaxed Bayesian consistency. We also prove that the empirical strategy profile induced by COL converges to the Berk-Nash equilibrium, a solution concept characterizing rationality under subjectivity. Experimental results from an intrusion response use case demonstrate COL’s faster convergence over state-of-the-art reinforcement learning methods against nonstationary attacks.

关键词： Learning systems Sociotechnical systems Games Reinforcement learning computer architecture Cyber-physical systems Cost function Bayes methods Convergence

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Cyber Security Posterior Distribution 13

Cyber Security Posterior Distribution

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13th IEEE International Conference on Communication systems and network Technologies, CSNT 2024

作者： Andrews, Leo John Baptist Venkatachary, Sampath Kumar Sarathkumar, D. Alagappan, Annamalai Fathima, M. Raj, Raymon Antony Rajeshkanna, R. Botho University Faculty of Engineering and Technology Department of Information Technology Gaborone Botswana Kongu Engineering College Department of Electrical and Electronics Engineering Erode district Tamilnadu 638 060 India Grant Thornton Gaborone Botswana Botho University Faculty of Engineering and Technology Department of Network and Infrastructure Management Gaborone Botswana Thamirabarani Engineering College Department of Eee Tamil Nadu Tirunelveli627 358 India Sri Krishna College of Engineering and Technology Department of Computer Science and Business Systems Tamilnadu Coimbatore India

ISBN: (纸本)9798350305463

Currently, the vast majority of international interactions and activities related to trade, government, culture, social interaction, and economics take place online. These interactions involve people, non-governmental organizations, governments, and government agencies at all levels. Recently, a sizeable number of commercial firms and government organizations all over the world have been presented with the challenge offered by cyberattacks as well as the danger represented by wireless communication technologies. A very little amount of time has passed since this had place. We were able to develop a model for the risk of cyber security by making use of Bayesian networks. This model has the capability of locating the point of cyber security that is weak and merging two different cyber analysis models. Among these is the activityquality model, which shows how individuals and/or groups adhere to the legal requirements for cyber security. Evidence describing the critical component of cyber security for a research reactor's RPS may be produced via the cyber security risk model. An further model that shows the probability of a cyberattack against RPS architecture is the cyber security risk model. © 2024 IEEE.

关键词： Bayesian networks

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Survey of Commercial Wi-Fi Devices’ Energy Detection Mechanism

Survey of Commercial Wi-Fi Devices’ Energy Detection Mechan...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Jeffrey Bailey Stone Liu Ioannis Lambadaris Sebastian Max David Sugirtharaj Department of Systems and Computer Engineering Carleton University Ottawa Canada Radio Network Research Ericsson Germany Ericsson Sweden

This paper presents an experimental survey of the capabilities of commercial IEEE 802.11 (Wi-Fi) devices to detect the state of the wireless medium. Wi-Fi devices use a Clear Channel Assessment (CCA) mechanism to determine if the wireless medium is occupied. By subjecting Wi-Fi devices to Gaussian interference signals transmitted through a Universal Software Radio Peripheral (USRP), we assess their CCA behavior. Moreover, we perform a deeper investigation of the Ericsson AP6321 Wi-Fi Access Point prompted by privileged access to its internal operations. Our findings highlight variations between different Wi-Fi devices’ CCA mechanisms and reveal floating CCA thresholds. Since CCA forms the fundamental basis for Wi-Fi operation, this study provides insights into coexistence of Wi-Fi with itself and dissimilar technologies. Because future Narrow Band Frequency Hopping (NB FH) systems are a potential technology that commercial Wi-Fi devices need to coexist with, we provide an extended survey of the capability of Wi-Fi devices to detect NB FH signals in unlicensed bands. This survey demonstrates that rapidly changing, on-off signalling does not have a disproportionate impact on Wi-Fi performance.

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Office Building Energy Community: A Case Study on Optimal Market Operation and Grid Impact 9

Office Building Energy Community: A Case Study on Optimal Ma...

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9th IEEE International Smart Cities Conference, ISC2 2023

作者： Lepisto, Juhani Forcan, Jovana Forcan, Miodrag Heine, Pirjo Helen Electricity Network Helsinki Finland University of East Sarajevo Faculty of Philosophy Department of Computer Science and Systems East Sarajevo Bosnia and Herzegovina University of East Sarajevo Faculty of Electrical Engineering Department of Electroenergetics East Sarajevo Bosnia and Herzegovina

ISBN: (纸本)9798350397758

In this paper, we study an office building connected to an urban distribution network from an energy community perspective. The office building and its electrical equipment have a real-world counterpart from which we construct synthetic time series based on the historical measurement data. The office building involves three stakeholders and their assets. The central stakeholders are the owner and the tenant of the building. The third stakeholder is the operator of flexible assets. The smartness of the office building is related to the control capabilities of its assets. These controllable assets are the battery energy storage system (BESS) and the electric vehicles (EV) charging system (EVCS) that both can operate in a flexible manner in response to energy price fluctuations and participate in a reserve market. We proposed different cases where either the owner or the tenant is paying the EV charging, and where the flexibility of the EV charging is either active or not. We show that, when the owner pays for the energy usage of the EVCS and the tenant is using it, there is a beneficial case to form a coalition between them and share the benefits from the flexibility, as otherwise there is no incentive for the tenant to be flexible in the first place. We conducted operative cost-benefit calculations where we shared the community benefits according to the Shapley value and simulated the power flows at the building's connection point based on the market operations. We found that harnessing benefits from the two market operations had significant effects on the power flows at the connection point. This was true when operating under the variable energy prices and in the reserve market. © 2023 IEEE.

关键词： Office buildings

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Empowering Software engineering Students: The Role of Gamification in Promoting Learning Independence 7

Empowering Software Engineering Students: The Role of Gamifi...

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7th International Conference on Vocational Education and Electrical engineering, ICVEE 2024

作者： Hidayat, Wahyu Nur Hamdan, Achmad Ichwanto, Muhammad Aris Muslihati Cakir, Gulsun Kurubacak Sari, Rahajeng Kartika Afni, Nur Hisyam, Mochammad Raffi Fadhil Universitas Negeri Malang Faculty of Engineering Department of Electrical Engineering and Informatics Malang Indonesia Universitas Negeri Malang Faculty of Vocational Department of Electronic Systems Engineering Technology Malang Indonesia Universitas Negeri Malang Faculty of Engineering Department of Civil Engineering and Planning Malang Indonesia Universitas Negeri Malang Faculty of Education Science Department of Guidance and Counseling Malang Indonesia Ankara Haci Bayram Veli University College of Communication Department of Journalism Ankara Turkey Smk Negeri 10 Malang Department of Computer Network and Telecommunication Engineering Malang Indonesia

ISBN: (纸本)9798331505103

The role of learning media greatly supports the learning process, increasing motivation and interest in the process. Learning media can also be a place to improve competence optimally through bootcamp training menus and the like with more specific training objectives. The main objective of this study is to develop a gamification-based website to enhance students' preparedness for their Final Competency Test by tackling challenges in comprehending programming absent practical experience. The learning method implemented in this website is case-based learning that integrates dynamic coding activities. The research method uses the Plomp approach with 3 main stages, namely preliminary research, prototyping, and assessment stage. The trial of the gamification website began with media and content validation followed by small group testing and large group testing. Validation by media and material experts led to the execution of small group trials (95.7%) and large group trials (91.7%), producing exceptionally positive outcomes. The results of the small group test with 12 respondents produced a very suitable value with a score of 95.7 and the large group test with 27 respondents produced a score of 9 1. 7 % with very suitable criteria. This indicates that the web-based platform is highly viable for assisting vocational students in acquiring software development skills, enhancing their preparedness for practical IT positions such as software developers and system analysts. Subsequent study involved the incorporation of gamification, such as computer-supported collaborative learning. © 2024 IEEE.

关键词： Software testing

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Conjectural Online Learning with First-order Beliefs in Asymmetric Information Stochastic Games

arXiv

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arXiv 2024年

作者： Li, Tao Hammar, Kim Stadler, Rolf Zhu, Quanyan The Department of Electrical and Computer Engineering New York University United States The Division of Network and Systems Engineering KTH Royal Institute of Technology Sweden

Asymmetric information stochastic games (AISGs) arise in many complex socio-technical systems, such as cyber-physical systems and IT infrastructures. Existing computational methods for AISGs are primarily offline and can not adapt to equilibrium deviations. Further, current methods are limited to particular information structures to avoid belief hierarchies. Considering these limitations, we propose conjectural online learning (COL), an online learning method under generic information structures in AISGs. COL uses a forecaster-actor-critic (FAC) architecture, where subjective forecasts are used to conjecture the opponents’ strategies within a lookahead horizon, and Bayesian learning is used to calibrate the conjectures. To adapt strategies to nonstationary environments based on information feedback, COL uses online rollout with cost function approximation (actor-critic). We prove that the conjectures produced by COL are asymptotically consistent with the information feedback in the sense of a relaxed Bayesian consistency. We also prove that the empirical strategy profile induced by COL converges to the Berk-Nash equilibrium, a solution concept characterizing rationality under subjectivity. Experimental results from an intrusion response use case demonstrate COL’s faster convergence over state-of-the-art reinforcement learning methods against nonstationary attacks. © 2024, CC BY.

关键词： Cost functions

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Automated Security Response through Online Learning with Adaptive Conjectures

arXiv

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arXiv 2024年

作者： Hammar, Kim Li, Tao Stadler, Rolf Zhu, Quanyan Division of Network and Systems Engineering KTH Royal Institute of Technology Sweden Department of Electrical and Computer Engineering New York University United States

We study automated security response for an IT infrastructure and formulate the interaction between an attacker and a defender as a partially observed, non-stationary game. We relax the standard assumption that the game model is correctly specified and consider that each player has a probabilistic conjecture about the model, which may be misspecified in the sense that the true model has probability 0. This formulation allows us to capture uncertainty and misconception about the infrastructure and the intents of the players. To learn effective game strategies online, we design Conjectural Online Learning (COL), a novel method where a player iteratively adapts its conjecture using Bayesian learning and updates its strategy through rollout. We prove that the conjectures converge to best fits, and we provide a bound on the performance improvement that rollout enables with a conjectured model. To characterize the steady state of the game, we propose a variant of the Berk-Nash equilibrium. We present COL through an advanced persistent threat use case. Testbed evaluations show that COL produces effective security strategies that adapt to a changing environment. We also find that COL enables faster convergence than current reinforcement learning techniques. © 2024, CC BY-SA.

关键词： Nash equilibrium

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Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G

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Science China(Information Sciences) 2023年第3期66卷 7-25页

作者： Guangxu ZHU Zhonghao LYU Xiang JIAO Peixi LIU Mingzhe CHEN Jie XU Shuguang CUI Ping ZHANG Shenzhen Research Institute of Big Data Future Network of Intelligence Institute (FNii) The Chinese University of Hong Kong (Shenzhen) School of Science and Engineering (SSE) The Chinese University of Hong Kong (Shenzhen) State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Department of Electrical and Computer Engineering and Institute for Data Science and Computing University of Miami Peng Cheng Laboratory State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

Pushing artificial intelligence(AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelligence of things(AIoT) in the sixth-generation(6G) era. This gives rise to an emerging research area known as edge intelligence, which concerns the distillation of human-like intelligence from the vast amount of data scattered at the wireless network edge. Typically, realizing edge intelligence corresponds to the processes of sensing, communication,and computation, which are coupled ingredients for data generation, exchanging, and processing, ***, conventional wireless networks design the three mentioned ingredients separately in a task-agnostic manner, which leads to difficulties in accommodating the stringent demands of ultra-low latency, ultra-high reliability, and high capacity in emerging AI applications like auto-driving and metaverse. This thus prompts a new design paradigm of seamlessly integrated sensing, communication, and computation(ISCC) in a taskoriented manner, which comprehensively accounts for the use of the data in downstream AI tasks. In view of its growing interest, this study provides a timely overview of ISCC for edge intelligence by introducing its basic concept, design challenges, and enabling techniques, surveying the state-of-the-art advancements, and shedding light on the road ahead.

关键词： sixth-generation (6G) edge intelligence artificial intelligence of things (AIoT) integrated sensing communication and computation (ISCC)

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