检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Guo, Yuejun Patsakis, Constantinos Hu, Qiang Tang, Qiang Casino, Fran Luxembourg Institute of Science and Technology Luxembourg Department of Informatics University of Piraeus 80 Karaoli & Dimitriou str. Piraeus18534 Greece Information Management Systems Institute of Athena Research Centre Greece Department of Computer Science The University of Tokyo Japan Department of Computer Engineering and Mathematics Rovira i Virgili University Tarragona Spain

The significant increase in software production driven by automation and faster development lifecycles has resulted in a corresponding surge in software vulnerabilities. In parallel, the evolving landscape of software vulnerability detection, highlighting the shift from traditional methods to machine learning and large language models (LLMs), provides massive opportunities at the cost of resource-demanding computations. This paper thoroughly analyses LLMs’ capabilities in detecting vulnerabilities within source code by testing models beyond their usual applications to study their potential in cybersecurity tasks. We evaluate the performance of six open-source models that are specifically trained for vulnerability detection against six general-purpose LLMs, three of which were further fine-tuned on a dataset that we compiled. Our dataset, alongside five state-of-the-art benchmark datasets, were used to create a pipeline to leverage a binary classification task, namely classifying code into vulnerable and non-vulnerable. The findings highlight significant variations in classification accuracy across benchmarks, revealing the critical influence of fine-tuning in enhancing the detection capabilities of small LLMs over their larger counterparts, yet only in the specific scenarios in which they were trained. Further experiments and analysis also underscore the issues with current benchmark datasets, particularly around mislabeling and their impact on model training and performance, which raises concerns about the current state of practice. We also discuss the road ahead in the field suggesting strategies for improved model training and dataset curation. Copyright © 2024, The Authors. All rights reserved.

关键词： Pipeline codes

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning Approach for the Underwater Investigation of Malicious Activity in a Wireless Sensor Network

A Machine Learning Approach for the Underwater Investigation...

引用

Sustainable Communication Networks and Application (ICSCNA), International Conference on

作者： Murali Dhar M S Mahaveerakannan R F. ravindaran Kommisetti Murthyraju Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu Department of Spatial Informatics The Institute of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering (Cyber Security) Karpagam College of Engineering Coimbatore Tamil Nadu Department of Electronics and Communication Engineering Shri Vishnu Engineering College For Women BHIMAVARAM Andha Pradesh

Underwater Wireless Sensor Networks (UWSN) have drawn increased interest from researchers in recent years due to advancements in underwater tracking, the implementation of multiple uses, and marine monitoring. Both researchers and business are drawn to the UWSN field. It is also susceptible to hostile attacks and threats because of the harsh undersea surroundings, its own capabilities, and the open acoustic channel. These features make it simple for attackers to intercept information across the source and destination. Many studies have been done to secure UWSN from malicious attacks, but the majority of them rely on a threshold that is determined before deployment or a training set of data. Because there is no proven security foundation, it is difficult and challenging for UWSN to identify harmful attacks. To identify harmful attacks in a UWSN, we support vector machines in this research. SVM produces good results and requires significantly less time to train than neural networks. This study will help the researchers design the routing protocols to cover the known security threats and help industries manufacture the devices to observe these threats and security issues.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Improved detection mechanism in MANETs using adaptive IP tracing mechanism

引用

International Journal of Intelligent Networks 2020年 1卷 102-106页

作者： Mamade, Bayisa Kune Dhas, C. Suresh Gnana School of Informatics and Electrical Engineering Institute of Technology Ambo University Ethiopia Department of Computer Science Institute of Technology Ambo University Ethiopia

The network has enabled enormous volumes of services without any restrictions, different users need to have access to the service provided are more focused by malicious users. It is imperative to identify malicious entry or access to services, hence this paper discusses the various aspects of malicious access due to DDoS attacks and on how to detect it also this method uses the decisions made by hackers to manage the Traceback information science. In this paper, we consider the flash crowds based on the difference between DDoS attacks, a flash crowd is used to mitigate the DDoS attack. There is a tendency to see information on flux entropy variations on routers’ short-term and store them. Once the victim has been aware of a DDoS attack, the victim starts pushback tracing. The initial Traceback rule identifies its upstream routers where attacks have taken place and transmits the requests for Traceback to the upstream connected routers. If the flow rate is low, the low detection rule is initiated to trace the attackers and therefore the study is evaluated based on the instances where the packets are attacked by malicious users. The evaluation is conducted based on whether the packet traversed is malicious or normal and finally the accuracy of IP Traceback techniques and time complexity are tested. © 2020 The Author(s)

关键词： Entropy

来源：评论

学校读者我要写书评

暂无评论

Hybrid-RIS Empowered UAV-Assisted ISAC Systems: Transfer Learning-based DRL

引用

IEEE Transactions on Communications 2025年

作者： Saikia, Prajwalita Jee, Anand Singh, Keshav Huang, Wan-Jen Boulogeorgos, Alexandros-Apostolos A. Tsiftsis, Theodoros A. National Sun Yat-sen University Institute of Communications Engineering Kaohsiung Taiwan Indian Institute of Technology Delhi Department of Electrical Engineering New Delhi110016 India University of Western Macedonia Department of Electrical and Computer Engineering Kozani50131 Greece University of Thessaly Department of Informatics and Telecommunications Lamia35100 Greece University of Nottingham Ningbo China Department of Electrical and Electronic Engineering Ningbo315100 China

In this paper, we consider a novel hybrid reconfigurable intelligent surface (HRIS) consisting of active as well as passive reflecting elements mounted on unmanned aerial vehicle (UAV). The aim is to improve air-to-ground communication by assisting multiple users, while detecting several low mobility targets. We formulate a sum-rate optimization problem that accounts for statistical channel estimation errors (SCEEs) to concurrently fine-tune both active and passive phase-shift matrices, UAV trajectory, and transmit beamformer for integrated sensing and communication (ISAC). Subsequently, we introduce a transfer learning based approach combining with deep deterministic policy gradient (DDPG) to enhance the overall data rate while minimizing the time it takes for users to transmit data. Additionally, we present an alternating optimization (AO) algorithm that employs a repetitive method to address the combinatorial nonconvex optimization problem and offers a solution that is very close to optimal. Finally, we showcase the superiority of the proposed scheme through Monte Carlo simulations. Also, we have compared the performance with perfect channel state information (CSI) counterpart. The outcomes of simulations confirm the theoretical analysis and demonstrate the efficiency of the proposed framework. Additionally, the results reveal the advantages of incorporating HRIS aided UAV assisted ISAC in improving the quality of both communication and sensing performance. © 1972-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

EHHGSO: Enhancing Hybrid Hugo Gas Solubility Optimization Algorithm Using Backtracking Technique 5

EHHGSO: Enhancing Hybrid Hugo Gas Solubility Optimization Al...

引用

5th International Conference on Sustainable Technologies for Industry 5.0, STI 2023

作者： Mahanta, Ajoy Bin Nur, Md. Oshama Islam, rakibul Azad, Saiful Wadith, Shadman Mahmud, Mufti Kaiser, M. Shamim Green University of Bangladesh Department of Computer Science and Engineering Dhaka Bangladesh Nottingham Trent University Department of Computer Science NottinghamNG118NS United Kingdom Nottingham Trent University Computing and Informatics Research Centre NottinghamNG118NS United Kingdom Nottingham Trent University Medical Technologies Innovation Facility NottinghamNG118NS United Kingdom Institute of Information Technology Jahangirnagar University Savar Dhaka1342 Bangladesh

ISBN: (纸本)9798350394290

Metaheuristic algorithms play a pivotal role in solving complex optimization problems. This study addresses a common challenge faced by such algorithms, i.e., getting trapped in local optima. This problem hampers the efficacy of metaheuristic algorithms in achieving globally optimal solutions. This limitation is also observed in Hybrid Henry Gas Solubility Optimization Algorithm (HHGSO)-a new metaheuristic based algorithm-which employs a cluster-based approach for population management. While this approach fosters exploration by diversifying the search process, it lacks adaptiveness in cluster assignments and the potentiality of hybridization with other algorithms. These shortcomings hinder the algorithm's ability to effectively escape local optima and harness the strengths of diverse optimization techniques. To mitigate these challenges, this study proposed an Enhanced HHGSO (EHHGSO) algorithm, an advanced hybridization of HHGSO. Here, a novel backtracking based technique is incorporated that can detect the trapping into local optima and can escape from it. Empirical findings substantiate the efficacy of EHHGSO in comparison to its ancestor, HHGSO for various benchmark functions. © 2023 IEEE.

关键词： Solubility

来源：评论

学校读者我要写书评

暂无评论

The Implementation of TOGAF for Enterprise System Planning on XYZ Campus

The Implementation of TOGAF for Enterprise System Planning o...

引用

Networking, Electrical engineering, computer Science, and technology (IConNECT), International Conference on

作者： Tamsir Hasudungan Sirait Ford Lumban Gaol Suhono Harso Supangkat Benny ranti Binus Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Bina Nusantara University Jakarta Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Computer Science Department Universitas Indonesia Jakarta Indonesia

Universities can employ information technology as one means of achieving their goals and objectives. Universities can get advantages from information technology, such as effective resource management and information management for decision-making. However, don't forget that the campus must consider what technology is appropriate to assist them achieve their goals, particularly in the current industrial era 4.0 where technology is available with many different choices. The campus requires an enterprise architecture in order to design, manage, and coordinate information technology infrastructure, applications, and processes strategically and thoroughly. The adoption of enterprise information system architecture (EA) is also intended to improve the quality of services provided to internal and external stakeholders. In this case, Enterprise Architecture can help an organization to match its information technology resources with business processes and strategies to achieve their goals. This research was conducted using TOGAF ADM, also known as the Open Group Architecture Framework Architecture Development Method. This method offers best practices for creating enterprise architecture and emphasizes several steps that include creating an architectural vision, information systems, business architecture modeling to help XYZ campus manage all their information technology.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Benchmark for CEC 2024 Competition on Multiparty Multiobjective Optimization

arXiv

引用

arXiv 2024年

作者： Luo, Wenjian Xu, Peilan Yang, Shengxiang Shi, Yuhui School of Computer Science and Technology Harbin Institute of Technology Shenzhen518055 China School of Artificial Intelligence Nanjing University of Information Science and Technology Nanjing210044 China School of Computer Science and Informatics The De Montfort University LeicesterLE1 9BH United Kingdom Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

The competition focuses on Multiparty Multiobjective Optimization Problems (MPMOPs), where multiple decision makers have conflicting objectives, as seen in applications like UAV path planning. Despite their importance, MPMOPs remain understudied in comparison to conventional multiobjective optimization. The competition aims to address this gap by encouraging researchers to explore tailored modeling approaches. The test suite comprises two parts: problems with common Pareto optimal solutions and Biparty Multiobjective UAV Path Planning (BPMO-UAVPP) problems with unknown solutions. Optimization algorithms for the first part are evaluated using Multiparty Inverted Generational Distance (MPIGD), and the second part is evaluated using Multiparty Hypervolume (MPHV) metrics. The average algorithm ranking across all problems serves as a performance benchmark. © 2024, CC BY-NC-SA.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

Patch-NetVLAD+: Learned patch descriptor and weighted matching strategy for place recognition

Patch-NetVLAD+: Learned patch descriptor and weighted matchi...

引用

2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2022

作者： Cai, Yingfeng Zhao, Junqiao Cui, Jiafeng Zhang, Fenglin Feng, Tiantian Ye, Chen Tongji University School of Electronics and Information Engineering Department of Computer Science and Technology Shanghai201804 China Tongji University Institute of Intelligent Vehicle Shanghai201804 China Tongji University School of Surveying and Geo-Informatics Shanghai200092 China

ISBN: (数字)9781665460262

ISBN: (纸本)9781665460262

Visual Place Recognition (VPR) in areas with similar scenes such as urban or indoor scenarios is a major challenge. Existing VPR methods using global descriptors have difficulty capturing local specific region (LSR) in the scene and are therefore prone to localization confusion in such scenarios. As a result, finding the LSRs that are critical for location recognition becomes key. To address this challenge, we introduced Patch-NetVLAD+, which was inspired by patch-based VPR researches. Our method proposed a fine-tuning strategy with triplet loss to make NetVLAD suitable for extracting patch-level descriptors. Moreover, unlike existing methods that treat all patches in an image equally, our method extracts patches of LSR, which present less frequently throughout the dataset, and makes them play an important role in VPR by assigning proper weights to them. Experiments on Pittsburgh30k and Tokyo247 datasets show that our approach achieved up to 9.3% performance improvement than existing patch-based methods. © 2022 IEEE.

关键词： Location awareness Visualization Aggregates Semantics Intelligent systems IEEE Regions

来源：评论

学校读者我要写书评

暂无评论

Telecom Churn Analysis using Machine Learning in Smart Cities

Telecom Churn Analysis using Machine Learning in Smart Citie...

引用

Advanced Innovations in Smart Cities (ICAISC), International Conference on

作者： Ashish Sharma Prafullit Shukla Mahendra Kumar Gourisaria Bhisham Sharma Imed Ben Dhaou Department of Computer Engineering & Applications GLA University Mathura UP India School of Computer Engineering KIIT Deemed to be University Bhubaneswar Odisha India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Computer Science Hekma School of Engineering Computing and Informatics Dar Al-Hekma University Jeddah Saudi Arabia

With the increase in the Telecom industry, service providers are more attentive toward the action of becoming larger or more extensive to the subscriber base. For surviving in telecom companies, the continued possession of holding customers must be a big challenge. According to consideration in the telecom environment, the market price of obtaining the new purchaser is more than holding the existing purchaser. Through collecting knowledge from the telecom industry to analyze the association of the customer whether will leave or not the company. Such types of the Decision tree and Logistic regression model have been compared on the 3334 instances of the dataset. The classification model derived from logistic regression has an accuracy of 80% and the decision tree classifier with an accuracy of 97%.

关键词： Industries Training Support vector machines Analytical models Smart cities Databases Companies

来源：评论

学校读者我要写书评

暂无评论

Psychological Stress Classification Using Extreme Gradient Boosting Algorithm

Psychological Stress Classification Using Extreme Gradient B...

引用

International Conference on Information and Communication technology Convergence (ICTC)

作者： Maria Mahardini Sakanti Viacheslav Siniaev Aurelia Amaris Win-Jet Luo Suhartono C. Bambang Dwi Kuncoro Graduate Institute of Precision Manufacturing National Chin-Yi University of Technology Taichung Taichung Taiwan Institute of Applied Computer Science ITMO University St. Petersburg Russian Federation Department of Informatics Engineering Faculty of Computer Science Universitas Brawijaya Malang Indonesia Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taichung Taiwan Department of Refrigeration Air Conditioning and Energy Engineering National Chin-Yi University of Technology Taichung Taiwan

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Stress, as a reaction to threatening situations, can raise heart rate and result in serious conditions that might cause significant damage or even be life-threatening. Traditional methods for evaluating stress, which rely on subjective self-reporting and clinical assessments, often suffer from biases and inconsistencies. Artificial intelligence models have been explored to predict stress levels more accurately. This paper investigates the application of Extreme Gradient Boosting in classifying psychological stress using the WESAD dataset, which includes parameters such as acceleration, electrocardiogram, electromyography, electrodermal activity, temperature, and respiration. The dataset was balanced and sampled to create a manageable subset for experimental. Extreme Gradient Boosting was chosen for its efficiency and scalability in handling complex datasets. The model was trained and validated, achieving a 95% accuracy in predicting stress levels. This study highlights the potential of integrating Extreme Gradient Boosting models into wearable devices for real-time stress monitoring. Future work involves optimizing the model to utilize fewer sensors without decreasing accuracy, ensuring it can be integrated into portable/wearable systems using tiny microcontrollers.

关键词： Accuracy Microcontrollers Psychology Human factors Predictive models Boosting Prediction algorithms Real-time systems Sensors Wearable devices

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：