检索结果-内蒙古大学图书馆

3rd IEEE International Conference on Intelligent Technologies, CONIT 2023

作者： Johnson, Plezzant Columbus Kant, Shri Kumar, Sandeep Sharda University Department of Computer Science Engineering India Sharda University Center for Cyber Security and Cryptology India

ISBN: (纸本)9798350338607

Today as we all know that maintaining of employee credential have been some major issues around the world. Finding it more difficult to keep track of employees. With this, the company, institution, or government entity does not know who has entered their work-spaces to steal important information from their systems or databases. This serves as a deep wound for any company that does not keep track of its employees. This has been a major issue within so many Africans country, most especially Liberia. where so many companies, institutions, and governmental entities losing huge amounts of data. The means by which they do not track employee records have been with the traditional sign-in method, which has to do with the pen and paper or book sign in and sign out method, which can easily be stolen or damaged. This is one of the methods that employees use to not sign in when they get to work in order to steal data without anyone knowing that they were at work that day. Coming up with a method that will enable strong security and secure maintenance of employees records with less consuming and a strong level of three-factor authentication (3FA) will enable all employees to sign in with their three-level credentials, which have to do with something you know (knowledge), something you have (possession), or something you are (Inherence).The trustworthiness of identification is increased because this data cannot be copied or hacked. Furthermore, Three (3) Factor Authentication attempts to demonstrate, from a broader perspective, why it is more important to review your security procedures in order to prevent unauthorized persons from gaining access to your systems and obtaining data and information that you have not provided them with. Our system is going to allow user signing in with their user credential on your system after entering your username and password which authenticate you into the system, you as an employee to be verified and attendance to be mark you will use your Fa

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Demand Response in Smart Grids: Challenges, Solutions, and security Implications 2

Demand Response in Smart Grids: Challenges, Solutions, and S...

引用

2nd International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2024

作者： Abdelraouf, Hussien Gogolkiewicz, Ryker Kim, Nathaniel McCaughan, Nicholas Alanes, Joel Nadhaif, Ali Fouda, Mostafa M. Ibrahem, Mohamed I. Augusta University School of Computer and Cyber Sciences AugustaGA30912 United States George Mason University Cyber Security Engineering Department FairfaxVA United States Idaho State University Department of Electrical and Computer Engineering PocatelloID United States

ISBN: (纸本)9798331529529

This paper discusses demand response (DR) in the context of smart grids (SGs). DR is a method of controlling electricity consumption and production, usually for financial and security reasons. The topics covered include security in DR, solutions to related attacks, and the implementation of one of these solutions. Attacks on DR involve various methods of injecting perturbations into the system to cause damage to the grid. Understanding these attacks is crucial for protecting future systems. It is also important to learn more about cyber-physical systems and how they operate. Another significant topic discussed in this paper is energy management in SGs, specifically how to produce zero marginal cost renewable energies efficiently and cleanly. The methods for achieving this outcome, including various formulas and systems, are discussed in the two referenced papers and will be explained further in this paper. These energy-saving methods also contribute to the cybersecurity aspect of this paper to encompass DR. © 2024 IEEE.

关键词： Demand response

来源：评论

学校读者我要写书评

暂无评论

Red deer algorithm to detect the secret key of the monoalphabetic cryptosystem

引用

Soft Computing 2024年第17-18期28卷 10569-10582页

作者： Jain, Ashish Bansal, Sulabh Das, Nripendra Narayan Gupta, Shyam Sunder Department of Information Technology School of Information Security and Data Science Manipal University Jaipur Jaipur303007 India Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Madhya Pradesh Gwalior474005 India

Encryption of a plaintext involves a secret key. The secret key of classical cryptosystems can be successfully determined by utilizing metaheuristic techniques. Monoalphabetic cryptosystem is one of the famous classical cryptosystems. In this paper, we determine the secret key of the monoalphabetic cryptosystem using a recently proposed metaheuristic technique, namely, red deer algorithm. The existing red deer algorithm framework has been tailored to solve the above considered problem. Performance of the developed red deer algorithm is compared with the following metaheuristic techniques: tabu search, genetic algorithm, and cuckoo search using three criteria, namely, effectiveness, efficiency, and accuracy. The results obtained show that the proposed red deer algorithm can compete with all the above three algorithms with respect to all the criteria. This signifies the importance of the proposed red deer algorithm is that it can be utilized to solve the similar problems effectively, efficiently, and with more accuracy. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Tabu search

来源：评论

学校读者我要写书评

暂无评论

Privacy Preservation Techniques in Smart Grids: Balancing security and Utility in IoT-Driven Environments 2

Privacy Preservation Techniques in Smart Grids: Balancing Se...

引用

2nd International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2024

作者： Abdelraouf, Hussien Long, Michael Tran, Paul Baral, Luna Khan, Zuha Mahmoud, Mohamed Fouda, Mostafa M. Ibrahem, Mohamed I. Augusta University School of Computer and Cyber Sciences AugustaGA30912 United States George Mason University Cyber Security Engineering Department FairfaxVA United States Idaho State University Department of Electrical and Computer Engineering PocatelloID United States

ISBN: (纸本)9798331529529

The Internet of Things (IoT) has significantly impacted the energy industry, leading to increased reliance on smart grid (SG) technology. However, integrating electricity with the internet introduces security vulnerabilities, exposing customers' consumption profiles. To protect this sensitive data, energy companies must employ novel algorithms that balance security compliance with utility. These models mask customer data using various methods, including differential privacy, which obfuscates data by adding noise. Another approach combines perturbation and encryption to generate noise from both central and local units. This study aims to identify factors that determine the most effective model, balancing utility and security. Comparing these solutions will provide insights for improving current deployments in smart meter (SM) privacy preservation. © 2024 IEEE.

关键词： Power grids

来源：评论

学校读者我要写书评

暂无评论

Enhancing Side-Channel Attacks Prediction using Convolutional Neural Networks 14

Enhancing Side-Channel Attacks Prediction using Convolutiona...

引用

14th International Conference on Advanced computer Information Technologies, ACIT 2024

作者： Alemerien, Khalid Al-Suhemat, Sadeq Alsuhimat, Fadi Altarawneh, Enshirah Tafila Technical University Information Technology Department Tafila Jordan Isra University Faculty of Information Technology Amman Jordan Philadelphia University Cyber Security Department Amman Jordan Hashemite University Computer Engineering Department Zarqa Jordan

ISBN: (纸本)9798350350036

A common type of cyberattack is the side channel attack (SCA), which affects many devices and equipment connected to a network. These attacks have different types, like power attacks such as DPA, electromagnetic attacks, storage attacks, and others. Researchers and information security experts are concerned about SCA targeting devices, as they can lead to the loss and theft of important information. Using deep learning (DL) techniques in SCA analysis can be an efficient tool for detecting the SCA. Many previous works have tried to carry out the SCA in order to mitigate the impact of these attacks, but they encountered difficulties in detecting the SCA, whether in selecting the suitable dataset or applying the most efficient machine learning or deep learning techniques for achieving high performance. Therefore, we developed in this paper a deep learning-based model to detect SCAs using a dataset related to power attacks (the DPAv4 dataset) and the Convolutional Neural Networks (CNN) algorithm to train and test the DPAv4 dataset. The findings of our experiments showed a significant improvement in the performance of DL-based techniques in the detection of SCA. The proposed CNN-based model achieved an accuracy of 0.814 in detecting SCA and a loss rate of 0.581. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

AI-Driven Solutions for Cloud security Implementing Intelligent Threat Detection and Mitigation Strategies

AI-Driven Solutions for Cloud Security Implementing Intellig...

引用

2024 IEEE International Conference on Intelligent Computing and Emerging Communication Technologies, ICEC 2024

作者： Yasani, Rajashekar Reddy Prasad, Putalpattu Muni Srinivas, Pattlola Reddy, N V Raja Sekhar Jawarkar, Parag Raghunath, Vedaprada Cloud Security Cloud Computing Cyber Security India University of Rome Tor Vergata Department of Industrial Engineering Italy Department of Computer Science and Engineering Telangana India Mlr Institute of Technology Department of It India Shri Ramdeobaba College of Engineering and Management Electronics Engineering Nagpur India Visveswaraya Technological University India

ISBN: (纸本)9798331508432

Adapting threat detection and response procedures is essential for businesses to stay ahead of the constantly developing cyberattack landscape. Researching cutting-edge tools like XDR, SIEM, SOAR, and NDR - which shed light on the dynamic realm of detection and response systems - is crucial. Other areas of investigation include real-time monitoring and network forensics. security and threat detection have both been greatly enhanced since businesses began storing their apps and data in the cloud. In order to safeguard vulnerable network infrastructures in cloud settings against advanced attacks, traditional security procedures must be revised. Artificial intelligence (AI) is used to learn more about this problem so that threat reaction and identification can be done more quickly and accurately. Artificial intelligence has changed cloud security and threat identification, as this study shows. Because cyberattacks on cloud infrastructures and service providers are becoming more common, strong security steps that are also easy to use are still needed. This piece will talk about how cloud security and AI operations work together, with a focus on how this collaboration speeds up the time it takes to respond to incidents. The paper will also show how this relationship helps a company improve its defences and lessen the impact of security events. Organisations that want to keep up with the constantly changing danger landscape need to use cloud security and AI and understand how the two work together. This is because it is necessary to keep a security stance that is both flexible and strong. © 2024 IEEE.

关键词： Cloud security

来源：评论

学校读者我要写书评

暂无评论

Using dummy data for RFID tag and reader authentication

引用

Digital Communications and Networks 2022年第5期8卷 804-813页

作者： Baha’A.Alsaify Dale R.Thompson Abdallah Alma'aitah Jia Di Department of Network Engineering and Security Jordan University of Science and TechnologyIrbid21163Jordan Computer Science and Computer Engineering Department University of ArkansasFayetteville72701ARUSA

Radio-Frequency IDentification(RFID)technology is an essential enabler of a multitude of intelligent *** robust authentication of RFID system components is critical in providing trustworthy data delivery from/to *** this paper,we propose an authentication protocol based on monitoring the transmissions between readers and tags in the *** proposed authentication scheme is based on injecting decoys within the exchanged communications(between RFID readers and tags)and is used in the authentication ***,the proposed authentication scheme is mathematically modeled and validated using extensive *** simulations results show that the proposed scheme provides a 100%confidence level in the authentication of tags and detection of compromised readers.

关键词： RFID Authentication Dummy data security Decoys

来源：评论

学校读者我要写书评

暂无评论

Image-Based Malware Classification: A Systematic Literature Review 1

Image-Based Malware Classification: A Systematic Literature ...

引用

1st IEEE International Conference on Cryptography, Informatics, and cybersecurity, ICoCICs 2023

作者： Yudhistira Utomo, Dimas Wahyu Lim, Charles Cyber and Crypto Polytechnic Cyber Security Engineering Bogor Indonesia Swiss German University Information Technology Department Banten Tangerang Indonesia

ISBN: (纸本)9798350339437

Malware, a shortened term for malicious software, refers to software or code designed to harm targets using malicious activities. Effective classification of malware is essential for developing robust detection and prevention mechanisms. This study presents a systematic review of the literature on image-based malware classification. The research methodology employed the DICARe technique. The results and discussion section revealed that 31 papers met the criteria and were highly quality. The study also examined the distribution of research on image-based malware classification by country of origin, with contributions from 15 different countries. Various classification techniques were identified in the literature, indicating the continuous development and evolution of solutions in this area. The findings suggest increased research output due to the growing importance of cybersecurity and increased funding for research in this field. This study provides valuable insights into the current state of image-based malware classification research and highlights the need for further advancements in this area. © 2023 IEEE.

关键词： Malware

来源：评论

学校读者我要写书评

暂无评论

An Enhanced Product Quality Evaluation using Hybrid LSTM-FCNN Model and GWO Algorithm for Social Media Sentiment Analysis 8

An Enhanced Product Quality Evaluation using Hybrid LSTM-FCN...

引用

8th International Conference on Electronics, Communication and Aerospace technology, ICECA 2024

作者： Raj Kumar, V.S. Kumaresan, T. Kanna, P. Rajesh Jagadeesan, S. Showmiya, P. Nithin, P. Bannari Amman Institute of Technology Department of Artificial Intelligence and Data Science Erode India Bannari Amman Institute of Technology Department of Computer Science and Engineering Erode India Nandha Engineering College Department of Computer Science and Engineering Erode India Nehru Institute of Technology Department of Computer Science - Cyber Security Coimbatore India Bannari Amman Institute of Technology Department of Artificial Intelligence and Machine Learning Erode India

ISBN: (纸本)9798350367904

Sentiment analysis is still in its developing era, and sometimes, struggles are faced in evaluating user sentiment due to the use of traditional models to analyze the relationship structures in social media interactions. To tackle the issue, we proposed an innovative approach Hybrid LSTM neural network and a fully connected neural network (FCNN) integrated with the Grey Wolf Optimization (GWO) algorithm. The objective of this proposed method is to improve sentiment analysis by employing the LSTM to capture the sequence of data and improve the ability of FCNNs to improve feature extraction and the analysis process. The proposed system process initiated with the data preprocessing of input Twitter sentiment dataset transformed into a suitable input to the Hybrid LSTM-FCNN neural network. Then, temporal dependency of the data captured by LSTM and FCNN is used to extract the features. The GWO method mimics the grey wolf hunting behaviour, for optimizing the proposed Hybrid LSTM-FCNN model's parameters to enhance the classification accuracy. The system models start with the initialization of the model, parameters, and training the models using the dataset to reduce the cross-entropy loss, estimating the testing dataset from unseen data and fine-tuning using GWO as necessary. Results demonstrate significant improvements in sentiment categorization compared to traditional methods. The Hybrid LSTM-FCNN model, enhanced with GWO, effectively captures nuanced sentiment patterns, leading to more accurate classification. Additionally, GWO's computational efficiency contributes to scalability. In conclusion, our proposed approach offers a promising solution for enhancing product quality evaluation through advanced neural network architectures and optimization algorithms applied to social media sentiment analysis. © 2024 IEEE.

关键词： Tweets

来源：评论

学校读者我要写书评

暂无评论

Personalized Educational Video Evaluation Combining Student's Cognitive and Teaching Style

Personalized Educational Video Evaluation Combining Student'...

引用

2023 IEEE International Conference on Systems, Man, and cybernetics, SMC 2023

作者： Weng, Jinta Dong, Haoyu Deng, Yifan Hu, Yue Wu, Hao Huang, Heyan School of Cyber Security University of Chinese Academy of Sciences China School of Computer Science and Cyber Engineering Guangzhou University China School of Computer Science and Technology Southeast Academy of Information Technology Beijing Institute of Technology China

ISBN: (纸本)9798350337020

AI-powered technologies, like ChatGPT and learning analytic technologies, have encouraged the sharing of online teaching resources and the transformation of teaching methods and learning pathways. However, the mixed resources and the result-oriented video evaluation repeatedly let students fall into an information trap and only appeal to students' attention to unsuitable resources. Inspired by human-computer interaction, a novel online video assessment LPSA(Linguistic- Presentative-scientific-Artistic) is proposed, integrated by cognitive style and teaching style, to realize more precise learning detection and teaching quality assessment. The LPSA evaluation consists of a four-level classification and eight secondary indexes quantified by machine learning algorithms. By automatically searching for an appropriate threshold of all secondary indexes, a real-time video assessment system is developed to certify its technical feasibility and pedagogical availability. The results show that the proposed AI-assisted assessment could realize practical pedagogical recommendations and real-time supervision. © 2023 IEEE.

关键词：

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：