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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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TRE-DSP:A traceable and revocable CP-ABE based data sharing scheme for IoV with partially hidden policy

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Digital Communications and Networks 2025年第2期11卷 455-464页

作者： Yousheng Zhou Rundong Peng Yuanni Liu Pandi Vijayakumar Brij Gupta College of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing 400065China College of Cyber Security and Information Law Chongqing University of Posts and TelecommunicationsChongqing 400065China Department of Computer Science and Engineering University College of EngineeringTindivanamMelpakkamTamil nadu 604001India Department of Computer Engineering National Institute of Technology KurukshetraIndia

With the popularity of the Internet of Vehicles(IoV),a large amount of data is being generated every *** to securely share data between the IoV operator and various value-added service providers becomes one of the critical *** to its flexible and efficient fine-grained access control feature,Ciphertext-Policy Attribute-Based Encryption(CP-ABE)is suitable for data sharing in ***,there are many flaws in most existing CP-ABE schemes,such as attribute privacy leakage and key *** paper proposes a Traceable and Revocable CP-ABE-based Data Sharing with Partially hidden policy for IoV(TRE-DSP).A partially hidden access structure is adopted to hide sensitive user attribute values,and attribute categories are sent along with the ciphertext to effectively avoid privacy *** addition,key tracking and malicious user revocation are introduced with broadcast encryption to prevent key *** the main computation task is outsourced to the cloud,the burden of the user side is relatively *** of security and performance demonstrates that TRE-DSP is more secure and practical for data sharing in IoV.

关键词： Privacy-preserving Attribute-based encryption Partially hidden policy Traceability User revocation Internet of vehicles

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High-Secured Image LSB Steganography Using AVL-Tree with Random RGB Channel Substitution

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computers, Materials & Continua 2024年第10期81卷 183-211页

作者： Murad Njoum Rossilawati Sulaiman Zarina Shukur Faizan Qamar Center of Cyber Security Faculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia Computer Science and Cyber Security Faculty of Engineering and Information TechnologyBirZeit UniversityBirZeitRamallahP.O.Box 14Palestine

Random pixel selection is one of the image steganography methods that has achieved significant success in enhancing the robustness of hidden *** property makes it difficult for steganalysts’powerful data extraction tools to detect the hidden data and ensures high-quality stego image ***,using a seed key to generate non-repeated sequential numbers takes a long time because it requires specific mathematical *** addition,these numbers may cluster in certain *** hidden data in these clustered pixels will reduce the image quality,which steganalysis tools can ***,this paper proposes a data structure that safeguards the steganographic model data and maintains the quality of the stego *** paper employs the AdelsonVelsky and Landis(AVL)tree data structure algorithm to implement the randomization pixel selection technique for data *** AVL tree algorithm provides several advantages for image ***,it ensures balanced tree structures,which leads to efficient data retrieval and insertion ***,the self-balancing nature of AVL trees minimizes clustering by maintaining an even distribution of pixels,thereby preserving the stego image *** data structure employs the pixel indicator technique for Red,Green,and Blue(RGB)channel *** green channel serves as the foundation for building a balanced binary ***,the sender identifies the colored cover image and secret *** sender will use the two least significant bits(2-LSB)of RGB channels to conceal the data’s size and associated *** next step is to create a balanced binary tree based on the green *** the channel pixel indicator on the LSB of the green channel,we can conceal bits in the 2-LSB of the red or blue *** first four levels of the data structure tree will mask the data size,while subsequent levels will conceal the remaining digits of secret *** embedding the bits i

关键词： Image steganography pixel random selection(PRS) AVL tree peak signal-to-noise ratio(PSNR) imperceptibility capacity

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A hybrid encryption for secure data deduplication the cloud

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International Journal of Cloud Computing 2023年第2-4期12卷 295-307页

作者： Ebinazer, Silambarasan Elkana Savarimuthu, Nickolas Bhanu, S. Mary Saira Department of Computer Science and Engineering Cyber Security IIIT Kottayam India Department of Computer Applications National Institute of Technology Tiruchirappalli India Department of Computer Science and Engineering National Institute of Technology Tiruchirappalli India

Cloud computing (CC) is a cost-effective platform for users to store their data on the internet rather than investing in additional devices for storage. Data deduplication (DD) defines a process of eliminating redundant data in the cloud by leaving a single copy. This paper provides a hybrid encryption scheme using genetic algorithm (GA) and attribute-based encryption (ABE) to ensure secure data transmission in the cloud and preventing the data deduplication by using message locked encryption (MLE). The hybrid encryption scheme provides a secure data transmission in the cloud. From the simulation output, the time requirement is reduced up to 94% and consumes 43% bandwidth compared with existing works. The proposed method tends to be quite effective in reducing storage and bandwidth costs. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Genetic algorithms

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An Energy Efficient Access and Handover Authentication Scheme for 6G Satellite-Terrestrial Integrated Network

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2024年第2期9卷 1-1页

作者： Xu, Zisang Peng, Hao Gu, Ke Li, Xiong Huang, Peng School of Computer and Communication Engineering Changsha University of Science and Technology Changsha China School of Computer Science and Engineering Institute for Cyber Security University of Electronic Science and Technology of China Chengdu China

6G Satellite-Terrestrial Integrated Network (STIN) extends connectivity services globally, attracting an increasing number of users to access the Internet with its advantages of wide coverage, high speed, and large capacity. However, the complex communication environments, such as link exposure and high dynamics of satellites in the network, pose challenges to designing authentication schemes that are applicable to 6G STIN. Although researchers have proposed many authentication schemes for 6G STIN, most of them have only focused on access authentication, which cannot guarantee the stability of subsequent communications. A few schemes have considered providing seamless services through handover authentication, but they still face issues such as security vulnerabilities and high energy consumption. To tackle these issues, this paper proposes an energy efficient authentication scheme for 6G STIN, capable of achieving mutual authentication between entities and negotiating a secure session key. Additionally, it designs a handover mechanism that is more suitable for 6G STIN and supports handover authentication for multiple users. Through security analysis, our scheme is proven to withstand various attacks, and its security is further verified using the ProVerif tool. Performance analysis shows that our scheme has lower authentication latency and communication overhead, while reducing energy consumption and ensuring security. IEEE

关键词： Authentication Protocol

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3GPP Edge–Fog federation: Transparent 3rd-party authentication and application mobility

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computer Communications 2024年 222卷 220-229页

作者： Ali, Asad Islam, Minhajul Mallick, Tushin Islam, Mohammad Sakibul Sakib, Sadman Shohrab Hossain, Md. Lin, Ying-Dar National Institute of Cyber Security Ministry of Digital Affairs Taiwan Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Computer Science and Engineering Bangladesh University of Engineering and Technology Bangladesh

3GPP edge and fog computing paradigms provide computational services to users at low latency. These paradigms alone are not enough to fulfill the users’ requirements completely. Therefore, a federation among these computing paradigms is necessary. To realize such federation, there is a need of an authentication mechanism where subscribers of a fog, can access 3GPP edge's services, or vice versa, without buying new subscription, and an application mobility mechanism for continuous service during handover from 3GPP edge to fog, or vice versa, without re-authentication. In this work, we propose: (1) a proxy-based state transfer and third-party authentication (PS3A), that uses a transparent proxy to transfer the authentication and application state information between 3GPP edge and fog, and (2) a token-based state transfer and proxy-based third-party authentication (TSP3A), that uses the proxy to transfer the authentication information and tokens to transfer application state information between 3GPP edge and fog. The proxy plays different roles, via virtual counterparts of entities involved in these protocols, to provide transparency. When the 3GPP edge, using EPS-AKA, receives an authentication request, the proxy relays and behaves as a virtual Home Subscriber Server (vHSS) for the 3GPP edge, and behaves as a virtual user for the fog, which is using OIDC. We applied PS3A and TSP3A to three federation scenarios among 3GPP edge and fog. Experimental results show that PS3A and TSP3A provide authentication within 0.345–2.858 s for a 0–100 Mbps proxy load. The results further show that TSP3A provides application mobility, while taking 40%–52% less time than PS3A, using state tokens. TSP3A and PS3A also reduce the service interruption latency by 82.4% and 84.6%, compared to the cloud-based service, via tokens and prefetching. © 2024 Elsevier B.V.

关键词： Authentication

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Genetic Algorithm-optimized k-nearest Neighbors and Support Vector Machines for Breast Cancer Detection in Resource-constrained Environments

IAENG International Journal of Computer Science

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IAENG International Journal of computer Science 2025年第3期52卷 848-861页

作者： Alemu, Abebe Girma, Anteneh Abebe, Mesfin Srinivasagan, Ramasamy Adama Science and Technology University Adama Ethiopia Computer Science/Cyber-Security department University of the District of Columbia WashingtonDC United States Computer Science and Engineering department Adama Science and Technology University Adama Ethiopia Computer Engineering department CCSIT King Faisal University Al Hufuf Saudi Arabia

Breast cancer poses a significant global threat, highlighting the urgent need for early detection to reduce mortality rates. Researchers are working to minimize the occurrence of false positives and false negatives, thereby improving the efficiency of breast cancer detection models. To achieve this, they employ advanced techniques such as artificial intelligence, machine learning, deep learning, and computational intelligence. Support vector machines (SVM) and k-nearest neighbors (KNN) are two popular lightweight machine-learning techniques.;however, their effectiveness depends on proper feature selection and parameter tuning. Genetic algorithm optimization provides a solution by intelligently selecting relevant features and fine-tuning parameters, which enhances classification accuracy for early diagnosis. This study demonstrates the effectiveness of a hybrid computational intelligence model that utilizes genetic algorithms for feature selection. The proposed GAKNN-SVM model shows superior performance in detecting breast tumors, utilizing the Wisconsin Breast Cancer Diagnostic Dataset. The results indicate significant improvements, with accuracy, sensitivity, and specificity rates reaching 98.25%, 98.15%, and 98.41%, respectively, based on 171 test samples. Overall, genetic algorithms and machine learning approaches hold great promise for improving breast cancer detection accuracy, ultimately leading to better diagnostic outcomes and reduced mortality rates, especially in resource-constrained environments. © (2025), (International Association of Engineers). All rights reserved.

关键词： Support vector machines

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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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The Role of AI in Vehicle-to-Infrastructure Communication for Tolling Systems

The Role of AI in Vehicle-to-Infrastructure Communication fo...

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2024 IEEE International Women in engineering (WIE) Conference on Electrical and computer engineering, WIECON-ECE 2024

作者： Mahalakshmi, S. Baskaran, Nithiya Partheeban, Pachaivanna Krishnara, Kowsalyadevi Arjun, S. Chennai Institute of Technology Department of Computer Science and Engineering Kundrathur Chennai India Chennai Institute of Technology Department Cyber Security Kundrathur Chennai India Chennai Institute of Technology Department Civil EngDepartment Cyber Security Kundrathur Chennai India Sona Institute of Technology Department of Cyber Security Salem India

ISBN: (纸本)9798331535476

The number of vehicles people use is substantial;thus, surveillance must be accurate. License plates are detected and recognized by detecting static and real-time images captured by the camera using OCR technology, computer vision, and AI in the tool booth and other important roads. This model can be used for many things, such as automated services, increased security, determining whether a car is registered, and identifying and validating vehicles connected to traffic violations. Real-time investigations are part of the automated recognition of license plates and their application to other traffic control and highway surveillance aspects. To detect plates from the images and in real-time video, Use Easy OCR with the license plates to read the plate number, utilize tensor flow object detection to detect and recognize, and save the detected license plate for further analysis and search. © 2024 IEEE.

关键词： Highway traffic control

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Energy Efficiency Maximization for Cooperative NOMA with Hardware Impairments

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China Communications 2024年第12期21卷 80-91页

作者： Wang Zhengqiang Chang Ruifei Wan Xiaoyu Fan Zifu Duo Bin School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China College of Computer Science and Cyber Security Chengdu University of TechnologyChengdu 610059China

The massive connectivity and limited energy pose significant challenges to deploy the enormous devices in energy-efficient and environmentally friendly in the Internet of Things(IoT).Motivated by these challenges,this paper investigates the energy efficiency(EE)maximization problem for downlink cooperative non-orthogonal multiple access(C-NOMA)systems with hardware impairments(HIs).The base station(BS)communicates with several users via a half-duplex(HD)amplified-and-forward(AF)***,we formulate the EE maximization problem of the system under HIs by jointly optimizing transmit power and power allocated coefficient(PAC)at BS,and transmit power at the *** original EE maximization problem is a non-convex problem,which is challenging to give the optimal solution ***,we use fractional programming to convert the EE maximization problem as a series of subtraction form ***,variable substitution and block coordinate descent(BCD)method are used to handle the ***,a resource allocation algorithm is proposed to maximize the EE of the ***,simulation results show that the proposed algorithm outperforms the downlink cooperative orthogonal multiple access(C-OMA)scheme.

关键词： block coordinate descent cooperative non-orthogonal multiple access energy efficiency hardware impairments resource allocation

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