检索结果-内蒙古大学图书馆

CL-SCA: A Contrastive Learning Approach for Profiled Side-Channel Analysis

IEEE Transactions on information Forensics and security 2025年 20卷 5109-5122页

作者： Liu, Annyu Wang, An Sun, Shaofei Wei, Congming Ding, Yaoling Wang, Yongjuan Zhu, Liehuang Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China Beijing University of Posts and Telecommunications School of Cyberspace Security Beijing100876 China Information Engineering University Institute of Cyberspace Security Zhengzhou450001 China

Side-channel analysis (SCA) based on machine learning, particularly neural networks, has gained considerable attention in recent years. However, previous works predominantly focus on establishing connections between labels and related profiled traces. These approaches primarily capture label-related features and often overlook the connections between traces of the same label, resulting in the loss of some valuable information. Besides, the attack traces also contain valuable information that can be used in the training process to assist model learning. In this paper, we propose a profiled SCA approach based on contrastive learning named CL-SCA to address these issues. This approach extracts features by emphasizing the similarities among traces, thereby improving the effectiveness of key recovery while maintaining the advantages of the original SCA approach. Through experiments of different datasets from different platforms, we demonstrate that CL-SCA significantly outperforms other approaches. Moreover, by incorporating attack traces into the training process using our approach, we can further enhance its performance. This extension can improve the effectiveness of key recovery, which is fully verified through experiments on different datasets. © 2005-2012 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Teachers cooperation:team-knowledge distillation for multiple cross-domain few-shot learning

引用

Frontiers of Computer Science 2023年第2期17卷 91-99页

作者： Zhong JI Jingwei NI Xiyao LIU Yanwei PANG School of Electrical and Information Engineering Tianjin UniversityTianjin 300072China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin 300308China Tianjin Key Laboratory of Brain-Inspired Intelligence Technology Tianjin 300072China

Although few-shot learning(FSL)has achieved great progress,it is still an enormous challenge especially when the source and target set are from different domains,which is also known as cross-domain few-shot learning(CD-FSL).Utilizing more source domain data is an effective way to improve the performance of ***,knowledge from different source domains may entangle and confuse with each other,which hurts the performance on the target ***,we propose team-knowledge distllation networks(TKD-Net)to tackle this problem,which explores a strategy to help the cooperation of multiple ***,we distill knowledge from the cooperation of teacher networks to a single student network in a meta-learning *** incorporates task-oriented knowledge distillation and multiple cooperation among teachers to train an efficient student with better generalization ability on unseen ***,our TKD-Net employs both response-based knowledge and relation-based knowledge to transfer more comprehensive and effective *** experimental results on four fine-grained datasets have demonstrated the effectiveness and superiority of our proposed TKD-Net approach.

关键词： cross-domain few-shot learning meta-learning knowledge distillation multiple teachers

来源：评论

学校读者我要写书评

暂无评论

Aggregation-based dual heterogeneous task allocation in spatial crowdsourcing

引用

Frontiers of Computer Science 2024年第6期18卷 215-227页

作者： Xiaochuan LIN Kaimin WEI Zhetao LI Jinpeng CHEN Tingrui PEI College of Information Science and Technology&Cyberspace Security Jinan UniversityGuangzhou 510632China National&Local Joint Engineering Research Center of Network Security Detection and Protection Technology Guangzhou 510632China Guangdong Provincial Key Laboratory of Data Security and Privacy Protection Guangzhou 510632China School of Computer Science Beijing University of Posts and TelecommunicationsBeijing 100876China

Spatial crowdsourcing(SC)is a popular data collection paradigm for numerous *** the increment of tasks and workers in SC,heterogeneity becomes an unavoidable difficulty in task *** researches only focus on the single-heterogeneous task ***,a variety of heterogeneous objects coexist in real-world SC *** dramatically expands the space for searching the optimal task allocation solution,affecting the quality and efficiency of data *** this paper,an aggregation-based dual heterogeneous task allocation algorithm is put *** investigates the impact of dual heterogeneous on the task allocation problem and seeks to maximize the quality of task completion and minimize the average travel *** problem is first proved to be ***,a task aggregation method based on locations and requirements is built to reduce task ***,a time-constrained shortest path planning is also developed to shorten the travel distance in a *** that,two evolutionary task allocation schemes are ***,extensive experiments are conducted based on real-world datasets in various *** with baseline algorithms,our proposed schemes enhance the quality of task completion by up to 25% and utilize 34% less average travel distance.

关键词： task allocation aggregation shortest path dual heterogeneous spatial crowdsourcing

来源：评论

学校读者我要写书评

暂无评论

Solving Multi-Objective Vehicle Routing Problems with Time Windows: A Decomposition-Based Multiform Optimization Approach

引用

Tsinghua Science and technology 2024年第2期29卷 305-324页

作者： Yiqiao Cai Zifan Lin Meiqin Cheng Peizhong Liu Ying Zhou Xiamen Key Laboratory of Data Security and Blockchain Technology College of Computer Science and TechnologyHuaqiao UniversityXiamen361021China College of Engineering Huaqiao UniversityQuanzhou362000China School of Computer Sciences Shenzhen Institute of Information TechnologyShenzhen518000China

In solving multi-objective vehicle routing problems with time windows (MOVRPTW),most existing algorithms focus on the optimization of a single problem formulation. However,little effort has been devoted to exploiting valuable knowledge from the alternate formulations of MOVRPTW for better optimization performance. Aiming at this insufficiency,this study proposes a decomposition-based multi-objective multiform evolutionary algorithm (MMFEA/D),which performs the evolutionary search on multiple alternate formulations of MOVRPTW simultaneously to complement each other. In particular,the main characteristics of MMFEA/D are three folds. First,a multiform construction (MFC) strategy is adopted to construct multiple alternate formulations,each of which is formulated by grouping several adjacent subproblems based on the decomposition of MOVRPTW. Second,a transfer reproduction (TFR) mechanism is designed to generate offspring for each formulation via transferring promising solutions from other formulations,making that the useful traits captured from different formulations can be shared and leveraged to guide the evolutionary search. Third,an adaptive local search (ALS) strategy is developed to invest search effort on different alternate formulations as per their usefulness for MOVRPTW,thus facilitating the efficient allocation of computational resources. Experimental studies have demonstrated the superior performance of MMFEA/D on the classical Solomon instances and the real-world instances.

关键词： MOVRPTW multiform optimization multiform construction knowledge transfer adaptive local search

来源：评论

学校读者我要写书评

暂无评论

Computer Vision-Based Attendance System - A Review

Computer Vision-Based Attendance System - A Review

引用

2024 Arab ICT Conference, AICTC 2024

作者： Alshamsi, Wadima M. Alghaithi, Shamma H. Alkaabi, Taif A. Almheiri, Salama R. Alshemeili, Shayma K. Hamid, Yasir Ababneh, Nedal Information Security Engineering Technology Abu Dhabi Polytechnic Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350342086

Attendance systems are necessary in educational institutions to track student attendance and guarantee that students are present for lessons. Traditional attendance methods, on the other hand, are frequently inefficient and prone to mistakes. Computer vision-based attendance systems are a potential new solution that can overcome these issues. Cameras are used by computer vision-based attendance systems to recognize and identify students' faces. This can be done in real time, with no need for students to manually sign in or out. Computer vision-based attendance systems can also be utilized to track student attendance in big classes and other difficult conditions. This study describes a computer vision-based attendance system designed for use in a university environment. The system was tested on a group of students, and the findings revealed that it could recognize and identify students' faces effectively. In addition, the technology shows potential in tracking student attendance in big classrooms. The study's findings show that computer vision-based attendance systems might be a useful tool for educational institutions. These devices may be used to track student attendance in difficult circumstances and can assist in enhancing the efficiency and accuracy of attendance tracking. © 2024 IEEE.

关键词： Machine vision

来源：评论

学校读者我要写书评

暂无评论

A Novel Trustworthiness Measurement Model Based on Weight and User Feedback

引用

Chinese Journal of Electronics 2022年第4期31卷 612-625页

作者： ZHOU Wei MA Yanfang PAN Haiyu School of Computer Science and Technology Huaibei Normal University School of Computer Science and Information Engineering Changzhou Institute of Technology School of Computer Science and Information Security Guilin University of Electronic Technology

Software trustworthiness is an essential criterion for evaluating software quality. In componentbased software, different components play different roles and different users give different grades of trustworthiness after using the software. The two elements will both affect the trustworthiness of software. When the software quality is evaluated comprehensively, it is necessary to consider the weight of component and user feedback. According to different construction of components, the different trustworthiness measurement models are established based on the weight of components and user feedback. Algorithms of these trustworthiness measurement models are designed in order to obtain the corresponding trustworthiness measurement value automatically. The feasibility of these trustworthiness measurement models is demonstrated by a train ticket purchase system.

关键词： Component-based software Trustworthiness Weight User feedback Measurement

来源：评论

学校读者我要写书评

暂无评论

FirmPorter: Porting RTOSes at the Binary Level for Firmware Re-hosting 26th

FirmPorter: Porting RTOSes at the Binary Level for Firmwa...

引用

26th International Conference on information and Communications security, ICICS 2024

作者： Xin, Mingfeng Wen, Hui Deng, Liting Li, Hong Li, Qiang Sun, Limin Beijing Key Laboratory of IOT Information Security Technology Institute of Information Engineering CAS Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China School of Computer and Information Technology Beijing Jiaotong University Beijing China

ISBN: (纸本)9789819788002

The rapid growth of the Industrial Internet of Things (IIoT) has brought real-time operating system (RTOS) into focus as major targets for both security analysts and malicious adversaries. Due to the non-standard hardware and diverse software, embedded RTOS devices present unique challenges to security analysts for the accurate analysis of firmware binaries. The diversity in hardware components and tight coupling between firmware and hardware makes it hard to perform dynamic analysis, which must have the ability to execute firmware code in virtualized environments. However, emulating the large expanse of hardware peripherals makes analysts have to frequently modify the emulator for executing various firmware code in different virtualized environments, which greatly limits the ability of analysis. In this work, we explore the problem of firmware re-hosting related to the RTOS. A device driver is developed by developers so that RTOS can be run on their platform. By providing alternative implementations for device drivers, we can make minimal modifications to the firmware that is to be migrated from its original hardware environment into a virtualized one. We show that an approach is capable of offering the ability to emulate various RTOS firmware in an automated manner without modifying existing emulators. Our approach, called static binary-level driver porting, first locates device driver initialization function and identify driver types in the target firmware, then adapts pre-built drivers to the existing emulator hardware. Finally, it replaces the drivers in the firmware with ours by utilizing binary rewriting technique. We demonstrate the practicality of the proposed method on multiple hardware platforms and firmware samples for security analysis. The results show that the approach is flexible enough to emulate firmware for vulnerability assessment and exploit development. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Firmware

来源：评论

学校读者我要写书评

暂无评论

Open World Recognition of Communication Jamming Signals

引用

China Communications 2023年第6期20卷 199-214页

作者： Yan Tang Zhijin Zhao Jie Chen Shilian Zheng Xueyi Ye Caiyi Lou Xiaoniu Yang School of Communication Engineering Hangzhou Dianzi UniversityHangzhou 310018China Science and Technology on Communication Information Security Control Laboratory Jiaxing 314033China

To improve the recognition ability of communication jamming signals,Siamese Neural Network-based Open World Recognition(SNNOWR)is *** algorithm can recognize known jamming classes,detect new(unknown)jamming classes,and unsupervised cluseter new *** network of SNN-OWR is trained supervised with paired input data consisting of two samples from a known *** the one hand,the network is required to have the ability to distinguish whether two samples are from the same *** the other hand,the latent distribution of known class is forced to approach their own unique Gaussian distribution,which is prepared for the subsequent open set *** the test,the unknown class detection process based on Gaussian probability density function threshold is designed,and an unsupervised clustering algorithm of the unknown jamming is realized by using the prior knowledge of known *** simulation results show that when the jamming-to-noise ratio is more than 0d B,the accuracy of SNN-OWR algorithm for known jamming classes recognition,unknown jamming detection and unsupervised clustering of unknown jamming is about 95%.This indicates that the SNN-OWR algorithm can make the effect of the recognition of unknown jamming be almost the same as that of known jamming.

关键词： communication jamming signals Siamese Neural Network Open World Recognition unsupervised clustering of new jamming type Gaussian probability density function

来源：评论

学校读者我要写书评

暂无评论

An Enhanced Group Key-Based security Protocol to Protect 5G SON Against FBS

引用

Computer Systems Science & engineering 2023年第5期45卷 1145-1165页

作者： Hoonyong Park TaeGuen Kim Daniel Gerbi Duguma Jiyoon Kim Ilsun You dWilly Susilo Department of Information Security Engineering Soonchunhyang UniversityAsan-si31538Korea Department of Financial Information Security Kookmin UniversitySeoul-si02707Korea Institute of Cybersecurity and Cryptology School of Computing and Information TechnologyUniversity of WollongongWollongong2522Australia

Network operators are attempting many innovations and changes in 5G using self-organizing networks(SON).The SON operates on the measurement reports(MR),which are obtained from user equipment(UE)and secured against malware and userspace ***,the synchronization signal block that the UE relies on to measure the wireless environment configured by a base station is not *** a result,the UE will likely gauge the wrong wireless environment configured by a false base station(FBS)and transmit the corresponding MR to the serving base station,which poisons the data used for 5G ***,the serving base stations must verify the authenticity of the *** 3GPP has advocated numerous solutions for this issue,including the use of public key certificates,identity-based keys,and group *** the solution leveraging group keys have better efficiency and practicality than the other two,they are vulnerable to security threats caused by key leaks via insiders or malicious *** this paper,we analyze these security issues and propose an improved group key protocol that uses a new network function,called a broadcast message authentication network function(BMANF),which validates broadcasted messages on behalf of the *** protocol operates in two phases:initial and *** the initial phase,the 5G core network distributes a shared secret key to the BMANF and UE,allowing the latter to request an authentication ticket from the *** the verification phase,the UE requests the BMANF to validate the broadcasted messages received from base stations using the ticket and its corresponding shared *** evaluation,we formally verified the proposed protocol,which was then compared with alternative methods in terms of computing *** a result,the proposed protocol fulfills the security requirements and shows a lower overhead than the alternatives.

关键词： False base station NRmeasurement report 5Gnetwork self-organizing network

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：