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Deep Learning Based Side-Channel Attack Detection for Mobile Devices security in 5G networks

清华大学学报自然科学版（英文版） 2025年第3期30卷 1012-1026页

作者： Amjed A.Ahmed Mohammad Kamrul Hasan Ali Alqahtani Shayla Islam Bishwajeet Pandey Leila Rzayeva Huda Saleh Abbas Azana Hafizah Mohd Aman Nayef Alqahtani Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600Malaysia Imam Alkadhim University College Department of Computer Techniques EngineeringBaghdad 10066Iraq Center for Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600Malaysia Department of Networks and Communications Engineering College of Computer Science and Information SystemsNajran UniversityNajran 61441Saudi Arabia Institute of Computer Science and Digital Innovation UCSI UniversityKuala Lumpur 56000Malaysia Department of Intelligent Systems and Cyber Security Astana IT UniversityAstana 20000Kazakstan Department of Computer Science College of Computer Science and EngineeringTaibah UniversityMadinah 42353Saudi Arabia Department of Electrical Engineering College of EngineeringKing Faisal UniversityAl-Hofuf 31982Saudi Arabia

Mobile devices within Fifth Generation(5G)networks,typically equipped with Android systems,serve as a bridge to connect digital gadgets such as global positioning system,mobile devices,and wireless routers,which are vital in facilitating end-user communication ***,the security of Android systems has been challenged by the sensitive data involved,leading to vulnerabilities in mobile devices used in 5G *** vulnerabilities expose mobile devices to cyber-attacks,primarily resulting from security ***-permission apps in Android can exploit these channels to access sensitive information,including user identities,login credentials,and geolocation *** such attack leverages"zero-permission"sensors like accelerometers and gyroscopes,enabling attackers to gather information about the smartphone's *** underscores the importance of fortifying mobile devices against potential future *** research focuses on a new recurrent neural network prediction model,which has proved highly effective for detecting side-channel attacks in mobile devices in 5G *** conducted state-of-the-art comparative studies to validate our experimental *** results demonstrate that even a small amount of training data can accurately recognize 37.5％of previously unseen user-typed ***,our tap detection mechanism achieves a 92％accuracy rate,a crucial factor for text *** findings have significant practical implications,as they reinforce mobile device security in 5G networks,enhancing user privacy,and data protection.

关键词： Fifth Generation(5G)networks smartphone information leakage Side-Channel Attack(SCA) deep learning

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LCEFL: A Lightweight Contribution Evaluation Approach for Federated Learning

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IEEE Transactions on Mobile Computing 2025年第7期24卷 6643-6657页

作者： Guo, Jingjing Li, Jiaxing Liu, Zhiquan Xiong, Yupeng Ma, Yong Vasilakos, Athanasios V. Li, Xinghua Ma, Jianfeng Xidian University School of Cyber Engineering Xi’an710071 China Jinan University College of Cyber Security Guangzhou510632 China Jiangxi Normal University Department of Computer Science and Technology Nanchang330022 China Department of Networks and Communications College of Computer Science and Information Technology Dammam31441 Saudi Arabia Grimstad4879 Norway

The prerequisite for implementing incentive mechanisms and reliable participant selection schemes in federated learning is to obtain the contribution of each participant. Available evaluation methods for participant contributions require the server to possess a test dataset, often impractical. Additionally, the excessively high complexity of these works is unacceptable when training complex models in large-scale federated learning system. To address these issues, we propose a lightweight contribution evaluation method for federated learning participants, named LCEFL, based on model projection theory, which does not require the server to provide a test dataset. In addition, a model compression method is designed to be used in LCEFL to reduce the computational complexity. Furthermore, a trusted aggregation method based on LCEFL is proposed, where the weight of each participant's local model is determined by its trust level, which can be calculated using its contribution evaluation result. Experimental results show that LCEFL can achieve nearly the same accuracy as schemes based on Shapley Value, while significantly reducing computational overhead by more than 50%. Compared to available aggregation methods, the proposed trusted aggregation scheme is able to accelerate the convergence speed of the global model and improve its accuracy by 2% to 45%. © 2002-2012 IEEE.

关键词： Federated Learning Computational Modeling Accuracy Servers Training Data Models Machine Learning Mobile Computing Particle Measurements Convergence Federated Learning Contribution Evaluation Trust Evaluation Model Projection Theory Secure Aggregation Federated Learning Computational Complexity Test Dataset Global Model Selection Of Participants Model Projections Aggregation Method Shapley Value Speed Of The Model Contributions Of Participants Number Of Participants Accuracy Of Model Computational Cost Local Data Learning Task Layer Model Participation Outcomes Updated Model Value Of Participation Model Aggregation Server Aggregates Global Convergence Iterative Rounds Trust Value Local Updates MNIST Dataset Total Amount Of Data Local Training Aggregation Algorithm Complex Model Structure

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An Unmanned Aerial Vehicle as a Multi-State System 16

An Unmanned Aerial Vehicle as a Multi-State System

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16th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer Engineering, TCSET 2022

作者： Kliushnikov, Ihor Kharchenko, Vyacheslav Fesenko, Herman Department of Computer Systems Networks and Cyber Security National Aerospace University 'KhAI' Kharkiv Ukraine

ISBN: (纸本)9781665468619

An unmanned aerial vehicle (UAV) is considered as a multi-state system (MSS). The results of the decomposition of the UAV into degradable and non-degradable components are presented. The reliability models of UAV as MSS have been developed and researched. Dependencies are obtained take into account the possible degradation levels of the UAVs various equipment. An example of the developed models application for evaluating the reliability of UAV-based monitoring system that collects two types of data from several target points is given. The results obtained can be used to assess the UAV and UAV fleets dependability and survivability considering complex physical and informational conditions. © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Reliability Models of Multi-state UAV-based Monitoring systems: Mission Efficiency Degradation Issues

Reliability Models of Multi-state UAV-based Monitoring Syste...

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2023 International Conference on Information and Digital Technologies, IDT 2023

作者： Kliushnikov, Ihor Kharchenko, Vyacheslav Fesenko, Herman Zaitseva, Elena Levashenko, Vitaly Networks and Cyber Security National Aerospace University KhAI Department of Computer Systems Kharkiv Ukraine University of Zilina Faculty of Management Science and Informatics Zilina Slovakia

ISBN: (纸本)9798350305869

General classification of multi-state UAV-based monitoring systems (MsUMSs) in view of types of used main and redundant unmanned aerial vehicles (UAVs), automatic battery maintenance stations (ABMSs), and mission efficiency degradation parameters is presented. General classification of reliability models for the MsUMS in view of the numbers of the main routes, route sections, UAVs, ABMSs, and degradation levels, is given and discussed. Reliability models for the MsUMS with various parameters are developed. The mission efficiency of the MsUMS and the probability of successful UAV mission plan fulfilment within the specified time frame on each of the degradation levels are utilized as basic indicators. Zero, one, and two-level-degradation reliability models for the MsUMS are explored and discussed in detail. A comparative analysis of the developed models is carried out. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Navigating the Waves: IoT Border Alert System for Maritime Safety

Navigating the Waves: IoT Border Alert System for Maritime S...

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2024 International Conference on Advances in Computing Research on Science Engineering and Technology, ACROSET 2024

作者： Koppaka, Ajay Aravindh, P. Aneesh, M. Valsan, Vipina Amrita Vishwa Vidyapeetham Centre for Cyber Security Systems & Networks Amritapuri India Amrita Vishwa Vidyapeetham Department of Electrical and Electronics Engineering Amritapuri India

ISBN: (纸本)9798350388800

The safety of fishermen navigating maritime borders is a pressing concern exacerbated by frequent unintentional border crossings that often lead to confrontations with foreign coast guards. The development of an Internet of Things (IoT)-based Border Alert System is motivated by these challenges. The comprehensive system proposed in this paper integrates an Arduino Nano, LoRa module (SX1278) for long-range communication, a GPS module (NEO-6M) for precise location tracking, and a buzzer for real-time alerts. The system aims to establish a robust safety mechanism that proactively notifies fishermen when they cross predefined borders with the help of barycentric coordinates system. The solution addresses not only the complexities of irregular sea borders but also the limitations of existing commercial tools and the lack of integration of systems and sensors. © 2024 IEEE.

关键词： Guards (shields)

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Enhancing Traffic Safety: An Automated License Plate Recognition System for Effective Law Enforcement

Enhancing Traffic Safety: An Automated License Plate Recogni...

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2024 International Conference on Advances in Computing Research on Science Engineering and Technology, ACROSET 2024

作者： Harish, Sam Mg Aksharasree, S. Deepak, S.G. Mamatha, S. Valsan, Vipina Amrita Vishwa Vidyapeetham Center for Cyber Security Systems & Networks Amritapuri India Amrita Vishwa Vidyapeetham Department of Electrical and Electronics Engineering Amritapuri India

ISBN: (纸本)9798350388800

In recent years, the number of accidents has been increased due to unsafe driving that has become a global concern. In India, 90% of road accidents had been reported in 2021 due to speeding, overtaking and rash driving. This paper presents an automated number plate recognition system using photo and video footage captured during both day and night. The system uses computer vision and image processing techniques, offering an efficient and scalable method to enforce traffic laws. © 2024 IEEE.

关键词： Highway accidents

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Securing Sustainable Energy Trading: An RSA-Encrypted IoT Solution for Smart Meter Data Transmission

Securing Sustainable Energy Trading: An RSA-Encrypted IoT So...

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2024 International Conference on Computational Intelligence and Computing Applications, ICCICA 2024

作者： Valsan, Vipina Keerthan, K.K. Devnath, N.S. Ajithkumar, Anirudh Sasikumar, Adarsh Amrita Vishwa Vidyapeetham Department Of Electrical And Electronics Engineering Amritapuri India Amrita Vishwa Vidyapeetham Center For Cyber Security Systems & Networks Amritapuri India

ISBN: (纸本)9798350306446

Smart grids have been replacing conventional energy grids in recent years and are deemed the next generation of today's power infrastructure distribution. However, due to the digitization of the energy grid framework, smart grids are prone to multiple cyber threats such as phishing attacks and data breaches. The number of cyberattacks against smart meters is estimated to have risen from 6,000 to 7,900 by 2023 and is expected to rise further in the coming years. These attacks allow attackers to manipulate access to the smart meter, thus leaking sensitive information. This paper proposes a Rivest-Shamir-Adleman (RSA) encryption algorithm to securely encrypt the data of the telemetry received, which is then sent to the servers. The received data is displayed to the user via an application. The need to maintain the integrity of the financial transactions in energy trading points to the importance of cyber security. This plays a major role in the construction of a sustainable community which is empowered with energy trading. Implementation of a secure algorithm like RSA enhances the security and resilience of the transactions. © 2024 IEEE.

关键词： Smart meters

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Robust steganographic approach using generative adversarial network and compressive autoencoder

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Multimedia Tools and Applications 2024年 1-38页

作者： Qasaimeh, Malik Qtaish, Alaa Abu Aljawarneh, Shadi Department of Computer Information Systems Faculty of Computer and Information Technology Jordan University of Science and Technology Irbid Jordan Department of Software Engineering co-joint with the Department of Cyber Security Faculty of Computer and Information Technology Jordan University of Science and Technology Irbid Jordan

Nowadays, social media applications and websites have become a crucial part of people’s lives;for sharing their moments, contacting their families and friends, or even for their jobs. However, the fact that these valuable data are transferred via the Internet and open channels, which are vulnerable to attacks and espionage, requires using defense methods to improve the security of data transmission. Recently, the progress of Deep Learning (DL) inspired researchers to use it with security methods such as steganography, the art of hiding secret data in unrelated content. DL and steganography combined enhanced the hiding properties, especially in the Coverless Image Steganography (CIS) methods. In this paper, we propose a Compressive Coverless Image Steganography (CCIS) model, which is a generated-based CIS, to improve the capacity and robustness of Steganography. This model uses the compressive autoencoder to compress the message, thus increasing the capacity, and uses the Generative Adversarial Network (GAN) to generate a stego image from the compressed vector, thus enhancing concealment ability, besides using a regression model and optimization method to extract the data. Another version was designed to enable sending binary messages by replacing the compressive autoencoder network with a robust mapping rule. Experiments show that the proposed model could improve the characteristics of Steganography. Furthermore, the proposed model could extract binary messages with 256 bits from attacked stego images with 99% recovery accuracy. Thus, capacity and robustness were enhanced using our model with both images and text as secret messages. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Generative adversarial networks

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A Digital Evidences Preservation Framework for a Logic Based Smart Contract

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Informatica (Slovenia) 2023年第8期47卷 141-152页

作者： Wala’a, Al-Omari Sabri, Khair Eddin Obeid, Nadim Department of Cyber Security College of Computer Sciences and Informatics Amman Arab University Amman Jordan Department of Computer Information Systems King Abdullah II School for Information Technology The University of Jordan Amman Jordan

Recently, smart contracts were introduced as a necessity to automatically execute specific operations within blockchain systems. The popularity and diversity of blockchain systems attracted intensive attentions from academia, industry and other sectors. Blockchain systems were implemented using different programming languages that used in defining the triggering events and their consequent actions within the smart contract. In this article, we propose a digital evidences preservation framework that supports logic-based smart contracts to manage entries associated with digital evidences. Combining logic-based approach and blockchain systems may result in ensuing contracts that have technical advantages over procedural coding. The paper shows the motivation for choosing logic-based approach to define a smart contract. We introduce the rules and structure of the proposed logic-based contract. © 2023 Slovene Society Informatika. All rights reserved.

关键词： Smart contract

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Energy-Aware Reliable Routing with Blockchain security for Heterogeneous Wireless Sensor networks 5th

Energy-Aware Reliable Routing with Blockchain Security for H...

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5th International Conference on Advances in Information Communication Technology and Computing, AICTC 2024

作者： Swapna, M.P. Ramkumar, J. Karthikeyan, R. Center for Cyber Security Systems and Networks Amrita Vishwa Vidyapeetham Kollam Amritapuri India Department of Information Technology & Cognitive Systems Sri Krishna Arts & Science College Coimbatore India Department of Computer Technology Sri Krishna Adithya College of Arts and Science Coimbatore India

ISBN: (纸本)9789819761050

Wireless sensor networks, the dynamic networks with spatially dispersed sensors are used indispensably in a wide range of applications. Heterogeneous wireless sensor networks represent a collection of sensor nodes of varying capabilities. However, if the energy in the network is not handled effectively, the resource-constrained sensors may reach an early death, affecting the network lifetime. security and routing are the two vital phenomena in wireless sensor networks that need careful and effective algorithmic execution. The proposed approach is an energy-aware routing algorithm combined with secure data transmission. TDDSRP is an innovative protocol to ensure security while reducing energy consumption. The residual energy and the direct trust value of nodes are crucial parameters to evaluate the energy trust value. The effectiveness of the protocol is tested against the existing counterparts using MATLAB simulations. The experimental results illustrate the performance of the protocol in energy consumption rate, throughput, and security measures. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： MATLAB

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