检索结果-内蒙古大学图书馆

An Optimal Text Watermarking Method for Sensitive Detecting of Illegal Tampering Attacks

computers, Materials & Continua 2022年第3期70卷 5583-5600页

作者： Anwer Mustafa Hilal Fahd N.Al-Wesabi Mohammed Alamgeer Manar Ahmed Hamza Mohammad Mahzari Murad A.Almekhlafi Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Information Systems King Khalid UniversityMuhayel AseerKingdom of Saudi Arabia Department of English College of Science&HumanitiesPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia Faculty of Engineering Department of Electrical EngineeringCommunication EngineeringSana’a UniversityYemen

Due to the rapid increase in the exchange of text information via internet networks,the security and authenticity of digital content have become a major research *** main challenges faced by researchers are how to hide the information within the text to use it later for authentication and attacks tampering detection without effects on the meaning and size of the given digital *** this paper,an efficient text-based watermarking method has been proposed for detecting the illegal tampering attacks on theArabic text transmitted online via an Internet *** this purpose,the accuracy of tampering detection and watermark robustness has been improved of the proposed method as compared with the existing *** the proposed method,both embedding and extracting of the watermark are logically implemented,which causes no change in the digital *** is achieved by using the third level and alphanumeric strategy of the Markov model as a text analysis technique for analyzing the Arabic contents to obtain its features which are considered as the digital *** digital watermark will be used later to detecting any tampering of illegal attack on the received Arabic *** extensive set of experiments using four data sets of varying lengths proves the effectiveness of our approach in terms of detection accuracy,robustness,and effectiveness under multiple random locations of the common tampering attacks.

关键词： Text analysis text-watermarking tampering detection text authentication

来源：评论

学校读者我要写书评

暂无评论

Robust Transmission Design in Multiobjective RIS-Aided SWIPT IoT communications

引用

IEEE Internet of Things Journal 2024年第10期11卷 18605-18618页

作者： Sharma, Vaibhav Allu, Raviteja Singh, Sandeep Kumar Singh, Keshav Duong, Trung Q. Tsiftsis, Theodoros A. Institute of Communications Engineering National Sun Yat-sen University Kaohsiung804 Taiwan Motilal Nehru National Institute of Technology Allahabad Electronics and Communication Engineering Department Prayagraj211004 India Memorial University of Newfoundland Faculty of Engineering and Applied Science St. John'sNLA1B 3X5 Canada Queen's University Belfast School of Electronics Electrical Engineering and Computer Science BelfastBT7 1NN United Kingdom University of Thessaly Department of Informatics and Telecommunications Lamia35100 Greece

This work investigates the performance of simultaneous wireless information and power transfer (SWIPT) in a reconfigurable intelligent surface (RIS)-aided Internet of Things (IoT) communications under imperfect channel state information (CSI). We formulate a multiobjective optimization problem (MOOP) to design a transmit precoding vector (TPV) at the base station (BS) and phase shift matrix (PSM) at the RIS that jointly maximizes energy efficiency (EE) and harvested power (HP) under the norm-bounded CSI error model. Due to the conflicting objective functions and nonconvex nature of the above optimization problem, the MOOP is simplified using the ϵ-constraint method and subsequently adopting advanced optimization tools, such as the Dinkelbach method, S-procedure, general sign-definiteness, semidefinite programming and convex-concave procedure. Thereafter, we propose an alternating optimization-based algorithm which determines optimal TPV and PSM iteratively that jointly maximizes the EE and HP of the considered system. Through numerical simulations, we validate the robustness, optimality, convergence, accuracy, and effectiveness of our proposed algorithm. Furthermore, we assess the impact of several key parameters, such as the number of RIS elements, available transmit power at BS, and the minimum HP on the performance of the considered system. © 2014 IEEE.

关键词： Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Resilience of Federated Learning Against False Data Injection Attacks in Energy Forecasting

Resilience of Federated Learning Against False Data Injectio...

引用

2024 International Conference on Green Energy, Computing and Sustainable Technology, GECOST 2024

作者： Shabbir, Attia Manzoor, Habib Ullah Ahmed, Ridha Alaa Halim, Zahid Gik Institute of Engg. Sciences & Tech. Faculty of Computer Science & Engg. Topi23640 Pakistan James Watt School of Engineering University of Glasgow United Kingdom University of Kufa Department of Electronics and Communication Engineering Najaf Iraq

ISBN: (纸本)9798350357905

Federated learning (FL) has established itself as a communication-efficient, privacy-aware, and cost-effective technique for training machine learning models in energy forecasting. This approach enables simultaneous model training across multiple smart grids while keeping data decentralized at edge nodes. However, FL is not immune to backdoor adversarial attacks, such as data and model poisoning. In this paper, we scrutinize the impact of two data poisoning techniques: scaling and random noise effects. The attack was initiated on one client among ten. As the attack percentage increases, the Mean Absolute Percentage Error (MAPE) of the local model also rises. Our simulation results reveal that the scaling effect elevated MAPE from 0.193% to 32.72%, while random noise increased MAPE from 0.183% to 129.75% as the attacked percentage rose from 10% to 100%. It is concluded that data poisoning solely affects the local model and does not significantly impact the global model;hence, it can provide more resilience than centralized machine learning models. © 2024 IEEE.

关键词： Cost effectiveness

来源：评论

学校读者我要写书评

暂无评论

The Influence of Human Factors in Ensuring Cybersecurity in Organizations: Effectiveness of PDPA and GDPR Implementation 3

The Influence of Human Factors in Ensuring Cybersecurity in ...

引用

3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Sharifi, Ahmad Zia Walid, Md. Abul Ala Momand, Mohammad Dawood Safi, Ihsan Ul Haq Safi, Hamidullah Khanzai Hossain, Sadia Nangarhar University Faculty of Computer Science Department of Networking and Communication Afghanistan Bangabandhu Sheikh Mujibur Rahman Digital University Department of Data Science and Engineering Gazipur Bangladesh Lautsprecher Teufel GMbH Berlin Germany Bangabandhu Sheikh Mujibur Rahman Digital University Department of Internet of Things and Robotics Engineering Gazipur Bangladesh

ISBN: (纸本)9798331518592

Modern organizations face rising levels of cyber risks, making cybersecurity a top priority for safeguarding sensitive data and maintaining operational continuity. Recent studies find human factors as the most critical contributors to cyber risks. These human-related risks include user misuse, user mistakes, and user malice. A large proportion of cyber risks arise when hackers use social engineering or phishing techniques to manipulate employees into disclosing confidential information. While some employees knowingly engage in these actions, some incidents occur accidentally due to a lack of awareness about cybersecurity protocols. As a result, governments around the world are enacting data protection legislation aimed at enhancing employees' cyber risk. This study explores the perception of US employees on the effectiveness of data protection legislation in countering cyber threats. It surveyed 30 randomly selected employees from various industries. The results showed that employees perceive data protection legislation as effective in mitigating employeerelated cyber risks. © 2024 IEEE.

关键词： Phishing

来源：评论

学校读者我要写书评

暂无评论

An Efficient Intrusion Detection Framework in Software-Defined Networking for Cybersecurity Applications

引用

computers, Materials & Continua 2022年第8期72卷 3529-3548页

作者： Ghalib H.Alshammri Amani K.Samha Ezz El-Din Hemdan Mohammed Amoon Walid El-Shafai Department of Computer Science Community CollegeKing Saud UniversityRiyadh28095Saudi Arabia Deanship of Scientific Research Saudi Electronic UniversityRiyadhSaudi Arabia Management Information System Department College of Business AdministrationKing Saud UniversityRiyadh28095Saudi Arabia Department of Computer Science and Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Electronics and Electrical Communications Eng.Depart. Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Network management and multimedia data mining techniques have a great interest in analyzing and improving the network traffic *** recent times,the most complex task in Software Defined Network(SDN)is security,which is based on a centralized,programmable ***,monitoring network traffic is significant for identifying and revealing intrusion abnormalities in the SDN ***,this paper provides an extensive analysis and investigation of the NSL-KDD dataset using five different clustering algorithms:K-means,Farthest First,Canopy,Density-based algorithm,and Exception-maximization(EM),using the Waikato Environment for Knowledge Analysis(WEKA)software to compare extensively between these five ***,this paper presents an SDN-based intrusion detection system using a deep learning(DL)model with the KDD(Knowledge Discovery in Databases)***,the utilized dataset is clustered into normal and four major attack categories via the clustering ***,a deep learning method is projected for building an efficient SDN-based intrusion detection *** results provide a comprehensive analysis and a flawless reasonable study of different kinds of attacks incorporated in the KDD ***,the outcomes reveal that the proposed deep learning method provides efficient intrusion detection performance compared to existing *** example,the proposed method achieves a detection accuracy of 94.21%for the examined dataset.

关键词： Deep neural network DL WEKA network traffic intrusion and anomaly detection SDN clustering and classification KDD dataset

来源：评论

学校读者我要写书评

暂无评论

Trust-Based Blockchain for Improving Supply Chain communication in Internet of Vehicles 1

Trust-Based Blockchain for Improving Supply Chain Communicat...

引用

1st IEEE International Interdisciplinary Humanitarian Conference for Sustainability, IIHC 2022

作者： Shaheen, H. MohanRaj, A. Shobha Rani, Meesala Sreeraj, S. Amutha, M. Kannadhasan, S. UWL-RAK Faculty of Computing and Engineering United Arab Emirates Sri Eshwar College of Engineering Department of Computer Science and Engineering Coimbatore India MVJ College of Engineering Department of Computer Science and Engineering Bangalore India Sri Krishna College of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Hindusthan College of Engineering Technical Campus Department of Computer Science and Engineering Coimbatore India Study World Collge of Engineering Department of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9781665456876

The motto behind the keenness of urban areas has become unmistakable in current cities because of the rise of installed and associated shrewd gadgets, frameworks, and innovations. It is possible to connect every object to the Internet. As a result, in the impending Internet of Things era, the 'Internet of Vehicles-IoV' will play a critical role in newly developed dazzling urban communities. The IoV can possibly address different traffic and street wellbeing issues successfully to forestall deadly crashes. In any case, a specific test of IoV, particularly in 'Vehicle-to-Vehicle' as well as 'Vehicle-to-Infrastructure' communications, guarantees quick, in order to transmit securely and exact performance of the information. The above effort is modifying Blockchain innovation for continuous application called RTA to meet 'Vehicle-to-Every thing-V2x' communications problems in order to overcome these challenges. As a result, the main goal of the study is to develop a Blockchain-based IoT framework for establishing communication security and creating a completely decentralized computing platform. Research methodology used here is divided into two major sections. In the part 1 presented below, authors discuss the traceability and optimization over Merkle trees. The second section deals with implementing an actual blockchain with our optimized Merkle tree as the underlying technology to represent a distributed trust based ledger. © 2022 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

A Deep Convolution Network-Based Pneumonia Identification from Thoracic X-Ray Imagery Scans 6th

A Deep Convolution Network-Based Pneumonia Identification fr...

引用

6th World Conference on Smart Trends in systems, Security and Sustainability, WS4 2022

作者： Upreti, Kamal Mishra, Prateet Maheshwari, Manish Vats, Prashant Dhankar, Aisha Batra, Reenu Yadav, Saneh Lata Chawla, Tanvi Bhardwaj, Jayant Department of Computer Science and Engineering Dr. Akhilesh Das Gupta Institute of Technology and Management Delhi New Delhi India Department of Computer Science and Information Technology Symbiosis University of Applied Sciences MP Indore India Department of Computer Science and Applications Makhanlal Chaturvedi National University of Journalism and Communication MCNUJC Madhya Pradesh Bhopal India Department of Computer Science and Engineering Faculty of Engineering and Technology SGT University Haryana Gurugram India Department of Electronics and Communication Bhagwan Parshuram Institute of Technology GGSIPU New Delhi India

ISBN: (纸本)9789811976599

Pneumonia is an infectious ailment which affects the respiratory system and is caused by microbes that infect the human by affecting their lung air sacs and fill them with fluid. Using chest X-ray is the most popular approach for detecting pneumonia, and the results must be calculated and examined by medical experts. The inconvenient way of detecting pneumonia results in a loss of human life owing to incorrect approach and treatment. With the advancement of computer and information technology, developing an autonomous system that can help in the diagnosis and prevention of pneumonia is now viable, especially if the patient is in a place where the medical facilities and expert doctors are limited. In order to solve this challenge, this project uses deep learning technologies. The neural network was customized to accomplish the difficult task of detecting diseases such as pneumonia in order to aid medical experts in their diagnosis and treatment options. CNN applies a filter to a photo in order to extract data from a chest X-ray. The above-mentioned goal was achieved using Python programming language, as well as deep learning and neural network methodologies. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Chest X-rays Deep CNN Recognition of pneumonia Rectified linear function Thoracic X-ray component

来源：评论

学校读者我要写书评

暂无评论

Fingerprint Liveness Detection with Voting Ensemble Classifier 6

Fingerprint Liveness Detection with Voting Ensemble Classifi...

引用

6th International Conference on Information Technology, InCIT 2022

作者： Sittirit, Napahatai Mongkolwat, Pattanasak Thaipisutikul, Tipajin Supratak, Akara Chen, Zhi-Sheng Wang, Jia-Ching Mahidol University Faculty of Information and Communication Technology Thailand Providence University Department of Computer Science and Information Engineering Taiwan National Central University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9781665489126

Detecting a user's fingerprint is a common verification process in many daily products such as smartphones and laptops. The convenience makes it popular, but this method is vulnerable to a presentation attack. Any fingerprint can be copied onto materials such as wood glue and gelatin, using only a few simple steps. Therefore, detecting whether the fingerprint comes from a live person is essential. In this paper, we proposed a method that employs a voting ensemble classification model to aggregate predictions from multiple individually trained machine learning models to determine whether an input fingerprint image is a live or a fake one. The input image is first pre-processed with a wavelet denoising algorithm, then Local Binary Pattern (LBP) and Local Phase Quantization (LPQ) are used for feature extraction. Next, we train a Voting Ensemble Classifying Model, utilizing predictions from several trained models, to find the majority vote for fingerprint liveness detection. According to the performance on the public LivDet 2015 dataset, the proposed method achieved better accuracy classification error (ACE) compared to the state-of-the-art models on three out of four sensor types: Greenbit (ACE=0.95%), Digital Persona (ACE=3.71%), and Hi Scan (ACE=1.39%). © 2022 IEEE.

关键词： Local binary pattern

来源：评论

学校读者我要写书评

暂无评论

Optimization Techniques in University Timetabling Problem:Constraints,Methodologies,Benchmarks,and Open Issues

引用

computers, Materials & Continua 2023年第3期74卷 6461-6484页

作者： Abeer Bashab Ashraf Osman Ibrahim Ibrahim Abakar Tarigo Hashem Karan Aggarwal Fadhil Mukhlif Fuad A.Ghaleb Abdelzahir Abdelmaboud Faculty of Computer Science&Information Technology Alzaiem Alazhari University13311KhartoumSudan Faculty Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400SabahMalaysia Department of Computer Science University of SharjahSharjah27272United Arab Emirates Electronic and Communication Engineering Department Maharishi Markandeshwar Deemed to be UniversityMullanaAmbala133207HaryanaIndia Information Assurance and Security Research Group(IASRG) School of ComputingFaculty of EngineeringUniversiti Teknologi Malaysia81310JohorMalaysia Department of Information Systems King Khaled UniversityMuhayel61913AseerSaudi Arabia

University timetabling problems are a yearly challenging task and are faced repeatedly each *** problems are considered nonpolynomial time(NP)and combinatorial optimization problems(COP),which means that they can be solved through optimization algorithms to produce the aspired optimal *** techniques have been used to solve university timetabling problems,and most of them use optimization *** paper provides a comprehensive review of the most recent studies dealing with concepts,methodologies,optimization,benchmarks,and open issues of university timetabling *** comprehensive review starts by presenting the essence of university timetabling as NP-COP,defining and clarifying the two formed classes of university timetabling:University Course Timetabling and University Examination Timetabling,illustrating the adopted algorithms for solving such a problem,elaborating the university timetabling constraints to be considered achieving the optimal timetable,and explaining how to analyze and measure the performance of the optimization algorithms by demonstrating the commonly used benchmark datasets for the *** is noted that meta-heuristic methodologies are widely used in the ***,recently,multi-objective optimization has been increasingly used in solving such a problem that can identify robust university timetabling ***,trends and future directions in university timetabling problems are *** paper provides good information for students,researchers,and specialists interested in this area of *** challenges and possibilities for future research prospects are also explored.

关键词： University timetabling timetabling approaches meta-heuristics combinatorial optimization

来源：评论

学校读者我要写书评

暂无评论

K-Banhatti Sombor Invariants of Certain computer Networks

引用

computers, Materials & Continua 2022年第10期73卷 15-31页

作者： Khalid Hamid Muhammad Waseem Iqbal Abaid Ur Rehman Virk Muhammad Usman Ashraf Ahmed Mohammed Alghamdi Adel A.Bahaddad Khalid Ali Almarhabi Department of Computer Science Superior UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Mathematics University of SialkotSialkot51013Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computing in Al-QunfudahUmm Al-Qura UniversityMakkah24381Saudi Arabia

Any number that can be uniquely determined by a graph is called a graph *** the last twenty years’countless mathematical graph invariants have been characterized and utilized for correlation ***,no reliable examination has been embraced to decide,how much these invariants are related with a network graph or molecular *** this paper,it will discuss three different variants of bridge networks with good potential of prediction in the field of computer science,mathematics,chemistry,pharmacy,informatics and biology in context with physical and chemical structures and networks,because k-banhatti sombor invariants are freshly presented and have numerous prediction qualities for different variants of bridge graphs or *** study solved the topology of a bridge graph/networks of three different types with two invariants KBanhatti Sombor Indices and its reduced *** deduced results can be used for the modeling of computer networks like Local area network(LAN),Metropolitan area network(MAN),and Wide area network(WAN),backbone of internet and other networks/structures of computers,power generation,bio-informatics and chemical compounds synthesis.

关键词： Bridge networks invariants k-banhatti sombor indices maple network graph molecular graph

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：