检索结果-内蒙古大学图书馆

A secure double spectrum auction scheme

Digital Communications and Networks 2024年第5期10卷 1415-1427页

作者： Jiaqi Wang Ning Lu Ziyang Gong Wenbo Shi Chang Choi School of Computer Science and Engineering Northeastern UniversityShenyang110004China School of Computer Science and Technology Xidian UniversityXi©anChina Dept.of Computer Engineering Gachon University1342Seongnam-daeroSujeong-guSeongnam-si13120G School of Computer and Communication Engineering Northeastern UniversityQinhuangdao066004China

With the arrival of the 5G era,wireless communication technologies and services are rapidly exhausting the limited spectrum *** auctions came into being,which can effectively utilize spectrum *** of the complexity of the electronic spectrum auction network environment,the security of spectrum auction can not be *** scholars focus on researching the security of the single-sided auctions,while ignoring the practical scenario of a secure double spectrum auction where participants are composed of multiple sellers and *** begin to design the secure double spectrum auction mechanisms,in which two semi-honest agents are introduced to finish the spectrum auction *** these two agents may collude with each other or be bribed by buyers and sellers,which may create security risks,therefore,a secure double spectrum auction is proposed in this *** traditional secure double spectrum auctions,the spectrum auction server with Software Guard Extensions(SGX)component is used in this paper,which is an Ethereum blockchain platform that performs spectrum auctions.A secure double spectrum protocol is also designed,using SGX technology and cryptographic tools such as Paillier cryptosystem,stealth address technology and one-time ring signatures to well protect the private information of spectrum *** addition,the smart contracts provided by the Ethereum blockchain platform are executed to assist offline verification,and to verify important spectrum auction information to ensure the fairness and impartiality of spectrum ***,security analysis and performance evaluation of our protocol are discussed.

关键词： Secure double spectrum auction SGX technology Privacy information Ethereum platform Verification

来源：评论

学校读者我要写书评

暂无评论

Unforgettable Password Generation Using LoRA Fine-Tuned Large Language Model

Unforgettable Password Generation Using LoRA Fine-Tuned Larg...

引用

2024 International Conference on Advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Sameer, Mohammed Sudharsan, K. Benazir Begum, A. Hindustan Institute Of Technology And Science Dept.of Computer Science & Engineering Chennai India

ISBN: (纸本)9798350364828

In response to the challenges posed by complex and hard-to-remember passwords in traditional authentication systems, this research introduces an innovative approach leveraging Low Rank Adaption (LoRA) fine-tuned Large Language Models (LLMs) to generate natural language-like strong passwords. Focused on striking a balance between usability and security, proposed system methodology employs smaller-sized pre-trained LLMs, adapted using LoRA fine-tuning, to produce passwords that are both strong and memorable. By addressing the limitations of current password generation practices, proposed system framework aims to encourage user adoption of secure practices, contributing to a positive societal impact through improved cybersecurity hygiene. The proposed solution involves deploying a fine-tuned LLM and serving them through an frontend web UI which emphasizes resource efficiency scalability of deployment of such model, and ease of using the generated passwords in real life authentication purposes fostering good cybersecurity practices among non-technical users. © 2024 IEEE.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

BlogGen- A Blog Generation Application Using Llama-2

BlogGen- A Blog Generation Application Using Llama-2

引用

2024 International Conference on Advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Verma, Amitasha Anand Kurupudi, Deshik Sathyalakshmi, S. Hindustan Institute Of Technology And Science Dept.of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350364828

In recent years, Large Language Models (LLMs) have emerged as transformative tools in natural language processing (NLP) and artificial intelligence (AI) *** excel in generating coherent and contextually relevant text across a wide range of applications one such segment focusing on content generation for websites, blogs and creative writing platforms. In such cases,with an open-source LLM like Llama-2, any person or business can use it for their means without having to pay licensing fees. This includes deploying the LLM to their own infrastructure and fine-tuning it to fit their own needs eliminating the exposure of data to third party interfaces, also making it task specific. This paper introduces a unique model to generate customised blogs by fine-tuning Llama-2 model and perform a comparison with GPT-3.5 and BERT. © 2024 IEEE.

关键词： Blogs

来源：评论

学校读者我要写书评

暂无评论

Analysis of Pattern Matching Techniques used for Information Leakage 15

Analysis of Pattern Matching Techniques used for Information...

引用

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Kumar, Abhishek Senapati, K.K. Patnaik, K.S. Dept.of Computer Science & Engineering Birla Institute of Technology Mesra Ranchi India

ISBN: (纸本)9798331300579

In the rapidly evolving digital landscape, ensuring the utmost security of sensitive information against the pervasive risks of information leakage has become a paramount *** study dives deep into a critical facet of information security-the intricate world of pattern matching algorithms-vital tools in the ongoing battle against Information *** research embarks on a comprehensive exploration of a diverse array of pattern matching algorithms, shedding light on their pivotal roles in the identification and effective mitigation of potential information *** meticulously analyze their inherent strengths, nuanced limitations, and practical applications across real-world contexts, understanding their multifaceted ***, we delve into the complexities of commonly utilized datasets for training and rigorous testing, strategically accentuating essential evaluation criteria that guide algorithmic *** this extensive exploration, we seek to elucidate the landscape of pattern matching algorithms, placing emphasis on their dynamic nature and promising potential in advancing information ***, we put forth insightful proposals for pective research directions within this vital domain, aiming to shape the future of information protection and fortification. © Grenze Scientific Society, 2024.

关键词： Information leakage

来源：评论

学校读者我要写书评

暂无评论

Moth flame optimization algorithm for efficient feature selection and hybrid classification technique for intrusion detection system

引用

Multimedia Tools and Applications 2025年 1-21页

作者： Keerthanarani, U. Selvakumar, V. Singaravelan, S. Raja, S. Edwin Thenmozhi, K. Shunmugam, D. Arun Dept. of Computer Science and Engineering P.S.R Engineering College Sivakasi India Dept.Of Computer Science and Engineering Vel Tech Rangarajan Dr Sagunthala R & d Institute of Science and Technology Chennai Avadi India Dept. Of Computer Science and Engineering Coimbatore Institute of Engineering and Technology Coimbatore India Dept. Of Electronics and Communication Engineering P.S.R Engineering College Sivakasi India

The rapid expansion of the Internet of Things (IoT) brings numerous benefits but further presents fresh difficulties, especially in terms of security. The distributed and interconnected nature of IoT devices makes them susceptible to various security threats. An Intrusion Detection System (IDS) plays a crucial role in safeguarding IoT networks by monitoring, detecting, and responding to potential security incidents. The Internet of Things (IoT) connects billions of devices, sensors, and systems, transforming industries and everyday life. However, this extensive interconnectivity also introduces significant security risks, making Intrusion Detection Systems (IDS) a critical component for safeguarding IoT environments. Feature selection is a crucial aspect of building effective Intrusion Detection Systems (IDS). Selecting relevant features not only helps in achieving better classification accuracy but also contributes to reducing false alarm rates. In the proposed system a moth flame optimizer is utilized to select the efficient features from the dataset, overall accuracy of over 97%. Further it is classified employing Random Forest and J48 classifier which attains high classification accuracy and low false alarm rate. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Feature Selection

来源：评论

学校读者我要写书评

暂无评论

A Real-Time Worker's Monitoring System using Deep Learning 15

A Real-Time Worker's Monitoring System using Deep Learning

引用

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Harshavardhan, L. Kumar, Girish T.P. Gowda, Jayanth B.R. Keerthan, B.K. Bevinatti, Mohan K.S. Dept.of Computer Science and Engineering BGS Institute of Technology Karnataka BG Nagara India

ISBN: (纸本)9798331300579

The Real-Time Worker Monitoring System employing deep learning and web integration represents a cutting-edge solution for enhancing workplace safety and *** advanced deep learning algorithms, this system continuously analyzes real-time data from various sensors, such as cameras and wearable devices, to monitor workers' activities and *** integration with web platforms enables instant access to the monitored information, facilitating seamless communication and *** providing timely insights into worker behavior and environmental factors, this innovative system not only promotes a safer work environment but also optimizes productivity through informed management *** the convergence of deep learning technology and web integration, this monitoring system stands at the forefront of workplace safety solutions, offering a robust framework for real-time insights and proactive intervention. © Grenze Scientific Society, 2024.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

De-convolution and De-noising of SAR Based GPS Images Using Hybrid Particle Swarm Optimization

引用

Chinese Journal of Electronics 2023年第1期32卷 166-176页

作者： Rizwan Sadiq Muhammad Bilal Qureshi Muhammad Mohsin Khan Dept.of Electrical and Electronic Engineering Koc University Dept.of Electrical and Computer Engineering COMSATS University Dept.of Radiology and Biomedical Imaging Yale University Sino-Pak Center for Artificial Intelligence (SPCAI) Pak-Austria Fachhochschule:Institute of Applied Sciences and Technology (PAF-IAST)

Synthetic aperture radar(SAR) imaging is an efficient strategy which exploits the properties of microwaves to capture images. A major concern in SAR imaging is the reconstruction of image from back scattered signals in the presence of noise. The reflected signal consist of more noise than the target signal and it is a challenging problem to reduce the noise in the collected signal for better reconstruction of an image. Current studies mostly focus on filtering techniques for noise removal. This can result in an undesirable point spread function causing extreme smearing effect in the desired image. In order to handle this problem, a computational technique, particle swarm optimization(PSO) is used for de-noising purpose and later the target performance is further improved by an amalgamation of Wiener ***, to improve the de-noising performance we have exploited the singular value decomposition based morphological filtering. To justify the proposed improvements we have simulated the proposed techniques and results are compared with the conventional existing models. The proposed method revealed considerable decrease in mean square error compared to Wiener filter and PSO techniques. Quantitative analysis of image restoration quality are also presented in comparison with Wiener filter and PSO based on the improvement in signal to noise ratio and peak signal to noise ratio.

关键词： Radar remote sensing Wiener filters Filtering Statistical analysis Radar polarimetry Particle swarm optimization Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

E-ATM For Card Less Transactions Using Machine Learning 1

E-ATM For Card Less Transactions Using Machine Learning

引用

1st IEEE International Conference on Electronics, Computing, Communication and Control technology, ICECCC 2024

作者： Aishwarya, D. Muralikumar, A. Mohammed Inthiyaz, M. Sathyabama Institute of Science and Technology Dept.of Computer Science and Engineering Tamilnadu Chennai600119 India

ISBN: (数字)9798350371802

ISBN: (纸本)9798350371802

A fingerprint recognition technique in the ATM system is the foundation of this study. We chose this to improve client security and facilitate simple transactions. Since every person has unique fingerprint details, this method will be more widely applicable. It is not necessary to keep your ATM card on hand at all times, nor is there any concern that your card will be lost. It is shown that fingerprint recognition technology outperforms and is safer than other technologies when compared to other ATM security systems already in use. This facilitates safe and simple transactions while maintaining a user-friendly environment. Without a doubt, service providers should also consider security when designing their ATM products, in order to protect financial transactions against security threats. And a lot about security holes, identity theft, credit card fraud, and ways for hackers and criminals to get any sensible passwords or pin numbers. Similar to a username, identification is employed in the present architecture to provide access to the system. To ensure that the intended user is indeed who say they are, since passwords may be stolen or lost. Biometric identity and authentication technologies are the most modern answers to security and privacy problems. The study of traits that may be used to identify a person is known as face recognition. These bodily attributes include, among other things, faces, voices, fingerprints, and hand shapes. The different security system authentication techniques are surveyed in this paper. This face biometric with QR code verification offers the highest degree of security in authentication. One of the most promising technologies for electronic money transactions is this procedure. The need for quick and precise user identification and authentication has increased due to the expansion of the electronic transaction industry. The Automated Teller Machine (ATM) is a fantastic convenience for people to satisfy their financial requirements. Not

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Twitter Bot For Consumer Feedback Analysis 5

Twitter Bot For Consumer Feedback Analysis

引用

5th IEEE International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2023

作者： Dwivedi, Ashish Sharma, Santosh Mishra, Abhinav Sahu, Ashutosh Gupta, Himanshu United Institute Of Technology Dept.Of Computer Science & Engineering Prayagraj India

ISBN: (纸本)9798350330861

This research presents the development of a Twitter bot for consumer feedback analysis using natural language processing (NLP) techniques. The bot is designed to collect and analyze tweets related to specific products or services, and provide businesses with real-time insights on consumer sentiment and feedback. The bot uses a combination of NLP techniques, including sentiment analysis, topic modeling, and keyword extraction, to identify trends and insights from the tweets. The resulting analysis can be used by businesses to improve their products or services, as well as their customer engagement strategies. The paper also discusses the challenges and opportunities associated with developing and deploying such a bot, including ethical considerations related to privacy and data protection. © 2023 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Automated AI Tool for Log File Analysis 6

Automated AI Tool for Log File Analysis

引用

6th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Lohar, Prerna Baraskar, Trupti Dept.of Computer Engineering & Technology Dr. Vishwanath Karad MIT World Peace University Pune India

ISBN: (纸本)9798331522667

Log file analysis has a critical role in monitoring and maintaining software systems, yet the manual inspection of logs becomes increasingly impractical with the growing volume of data. This survey paper explores recent advancements in automated log file analysis, with a particular focus on the integration of AI techniques, which includes ML models and NLP. The study identifies key challenges in traditional methods, such as the need for human interpretation, difficulty in detecting new errors, and issues in backtracking within continuous data streams. Moreover, we examine state-of-the-art AI approaches, like LLaMA 2, to streamline log analysis by automating error detection, summarization, and anomaly identification. Research deficiencies are identified, notably the necessity for advanced methodologies to manage variety of log formats, automated model optimization, and ongoing learning processes. This comprehensive review endeavors to provide a thorough examination of the current landscape, encompassing perspectives on potential outcomes and prospective trajectories in the domain of AI-enhanced log file analysis. In addition to providing insights into prospective solutions and future directions in AI-driven log file analysis, this study attempts to give an in-depth analysis of the current situation. © 2025 IEEE.

关键词： Economic and social effects

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：