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3rd International Seminar on Artificial Intelligence, Networking, and Information technology, AINIT 2022

作者： Luo, Jie Li, Zhong College of Information Science and Technology Donghua University Shanghai201620 China Key Laboratory of the Ministry of Education for Embedded System and Service Computing Department of Computer Science Tongji University Shanghai201804 China

ISBN: (数字)9781510662971

ISBN: (纸本)9781510662964

Vehicular networks improve traffic safety and efficiency by wireless communications among vehicles and infrastructures. However, security has always been a challenge to vehicular networks, which may cause severe harm to the intelligent transportation systems. Sybil attack is considered as a serious security threat to vehicular networks since the attacker can disseminate false messages with multiple forged identities. In this paper, we designed a behavior feature and multi-scenario-based Sybil attack detection method, named BMSAD in vehicular networks. In BMSAD, we propose solutions for two scenarios: normal traffic and traffic congestion. A node is allowed to verify the authenticity of another node by estimating their geographic distance based on received signal strength, and compare them to its claimed localizations. Then we design long- and short-term pattern to analyze the similarity of vehicles' behavior features and trajectory for Sybil nodes detection, which act as the second line of defense in normal traffic scenario. At last, the Sybil nodes of the traffic congestion scenario are detected by logical inference based on kinematics theory. And experiment results demonstrate that the proposed scheme achieves high detection rate and low false positive rate. © 2023 SPIE.

关键词： Traffic congestion

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Community Opinion Maximization in Social Networks

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IEEE Transactions on Evolutionary Computation 2024年 1-1页

作者： Liu, Yilu Zhang, Qingfu Wang, Zhenkun Department of Computer Science City University of Hong Kong Hong Kong China School of System Design and Intelligent Manufacturing and the Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China

Maximizing the influence of opinions is an emerging research topic in social networks. Although the community is a key structure of social networks, little effort has been made to investigate how to maximize the influence of opinions on all communities. This paper proposes a systematic approach to address this issue. First, we construct a multi-faceted opinion evolution (MFOE) model with three critical influence factors, namely, individuals, neighbors, and communities, to describe the opinion evolution process in social networks. The convergence analysis confirms its ability to reveal the influence of opinions. Then, we define the overall community opinion to measure the influence of opinions on all communities and employ it as the objective function to formulate an optimization problem called community opinion maximization (COM). We show that the COM problem is NP-hard. To optimize this problem, a memetic algorithm with three problem-specific schemes is developed and termed MACOM. Extensive experimental studies on real-world social networks demonstrate the plausibility of the MFOE model and the effectiveness of MACOM. IEEE

关键词： Optimization

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Dynamic Searchable Scheme with Forward Privacy for Encrypted Document Similarity 22

Dynamic Searchable Scheme with Forward Privacy for Encrypted...

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22nd IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2023

作者： Al Sibahee, Mustafa A. Luo, Chengwen Zhang, Jin Huang, Yijing Abduljabbar, Zaid Ameen Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China Iraq University College Computer Technology Engineering Department Basrah61004 Iraq University of Basrah College of Education for Pure Sciences Department of Computer Science Basrah61004 Iraq Huazhong University of Science and Technology Shenzhen Institute Shenzhen518000 China

ISBN: (纸本)9798350381993

Document retrieval plays an essential role in many real-world applications especially when the data storage is outsourced. Due to the great advantages offered by cloud computing, clients tend to outsource their personal data to remote servers maintained by external service providers. This raises serious privacy concerns about outsourced data because such providers are usually considered untrusted entities. The majority of previous schemes of document similarity search share the same limitation: they focus mainly on static collections. Dynamic searchable schemes (DSE) allow adding or removing documents at the expense of more leakage than static schemes. To thwart certain attacks, DSE schemes should support forward privacy property, which ensures that newly added documents cannot be related to previously issued search queries. We design and implement dynamic secure similarity search schemes with forward privacy for textual documents utilizing simhash method for hamming similarity. Our scheme provides an efficient search time and a sufficient level of privacy. To show the practicality of our proposed scheme, we performed excremental results with large document collections. © 2023 IEEE.

关键词： Cryptography

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Enhancing Cybersecurity with Transformers: Preventing Phishing Emails and Social Media Scams

Enhancing Cybersecurity with Transformers: Preventing Phishi...

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IEEE Conference on Dependable and Secure Computing

作者： Essam Al Daoud Laith Al Daoud Mahmoud Asassfeh Ala'a Al-Shaikh Ala'a Saeb Al-Sherideh Suha Afaneh Department of Cybersecurity Zarqa University Zarqa Jordan Computer Information System Jordan University of Science and Technology Jordan

ISBN: (数字)9798331540289

ISBN: (纸本)9798331540296

In this study, the enhancement of cybersecurity through the use of transformer models is explored, specifically focusing on the prevention of phishing emails and social media scams. Two modern datasets were utilized: the Phishing_Pot dataset, which provided phishing emails across 19 languages, and a collection of legitimate emails. Additionally, a dataset from Baaz, an Arabic social media platform, was compiled. Four approaches to phishing detection were compared: zero-shot learning with large language models (LLMs), transformers for feature extraction followed by random forest classification, fine-tuning of small language models (SLMs) on newly generated datasets, and an ensemble method combining the top models from the previous approaches. The experiments demonstrated that LLMs such as GPT-4o, Gemini 1.5, and Claude 3 achieved high accuracy, while SLMs showed improved performance post fine-tuning. The ensemble methods can be used to enhance the accuracy of fine-tuned SLM for phishing detection and scam prevention, reaching an accuracy of 98.50% for the first dataset and 95.25% for the second.

关键词： Adaptation models Accuracy Social networking (online) Phishing Prevention and mitigation Zero shot learning Transformers Data models Electronic mail Ensemble learning

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A Scalable Solution for Pneumonia Diagnosis: Transfer Learning for Chest X-ray Analysis 7

A Scalable Solution for Pneumonia Diagnosis: Transfer Learni...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Haque, Rezaul Sultana, Shayma Prasad, Chandan Hasan, Sayed Fardin, Hasib Sakib, Abdullah Al Malik, Neeru Kaushik, Keshav East West University Department of Cse Dhaka Bangladesh International American University Department of Management Information System United States Pimpri Chinchwad University Department of Computer Science and Engineering Maharashtra Pune India Westcliff University Department of Engineering Management United States Westcliff University Department of Information Technology United States Pimpri Chinchwad University School of Engineering & Technology Maharashtra Pune India Amity University Amity School of Engineering and Technology Punjab India

ISBN: (纸本)9798350350067

The high death rate and rapid spread of pneumonia make it a serious global health concern. The precision of traditional diagnostic techniques is often compromised, particularly in resource-limited settings. Existing studies have predominantly focused on either binary or multi-class classification, often relying on limited datasets, which affects the generalizability and robustness of models. Additionally, the interpretability and transparency of deep learning models remain challenging in clinical environments. Addressing these challenges is crucial for advancing diagnostic methodologies to combat pneumonia. This study explores the use of transfer learning to improve the reliability of pneumonia classification using chest X-ray images. An automated classification system was developed, utilizing a combination of image preprocessing techniques, feature extraction with GLRLM, and various machine learning and transfer learning algorithms. Two datasets were employed: the GWCMCx dataset with 5856 chest X-rays and another dataset comprising 9207 chest X-rays. The system was designed for both binary and multi-class classification scenarios. CapsuleNet emerged as the most effective model, achieving an accuracy of 99.02% in binary classification and 90.43% in multi-class classification, significantly outperforming previous studies. Additionally, a user-friendly web application was developed to facilitate the integration of the classification system into clinical workflows, accelerating clinical decision-making. This study demonstrates the potential of transfer learning to automate and improve pneumonia diagnosis, offering a scalable solution that can alleviate radiologists' workload and improve patient outcomes. © 2024 IEEE.

关键词： Transfer learning

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Battery Degradation Modeling in Hybrid Power Plants: An Island system Unit Commitment Study 4

Battery Degradation Modeling in Hybrid Power Plants: An Isla...

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4th Annual IEEE Kansas Power and Energy Conference, KPEC 2023

作者： Huang, Jianqiao Fang, Xin Zhou, Xinyang Tan, Jin Dong, Shuan Hoke, Andy National Renewable Energy Laboratory Power System Engineering Center GoldenCO United States Illinois Institute of Technology Electrical and Computer Engineering Chicago United States Mississippi State University Electrical and Computer Engineering Department StarkvilleMS United States

ISBN: (纸本)9798350335408

As hybrid power plants (HPPs), such as photovoltaic (PV) and battery combinations, become increasingly important in power systems with high renewable energy penetration to address PV variability and ensure grid stability. This paper focuses on the urgent need to model the coordination between PV and battery systems in HPPs while accounting for battery degradation. We present a generation scheduling model that explicitly incorporates PV-battery hybridization in the unit commitment problem. Moreover, the cost function of the HPP scheduling problem endogenously considers battery degradation with adjustable weights to strike a balance between minimizing production costs and prolonging battery life, particularly when providing energy arbitrage and ancillary services. Using a realistic island system simulation, we demonstrate that accounting for battery degradation in the scheduling problem can significantly extend battery life with only minor additional production costs. © 2023 IEEE.

关键词： Cost functions

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DEEP LEARNING-BASED CHANNEL ESTIMATION FOR RIS-ASSISTED UAV-ENABLED WIRELESS COMMUNICATIONS system

DEEP LEARNING-BASED CHANNEL ESTIMATION FOR RIS-ASSISTED UAV-...

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2023 International Conference on Innovation, Communication and Engineering, ICICE 2023

作者： Tesfaw, Belayneh A. Lin, Hsin-Piao Tarekegn, Getaneh B. Juang, Rong-Terng Jeng, Shiann-Shiun Department of International Graduate Program in Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan Institute of Aerospace and System Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Electrical and Computer Engineering National Yang-Ming Chiao Tung University Hsinchu30010 Taiwan Department of Electrical Engineering National Dong Hwa University Hualien Taiwan

ISBN: (纸本)9781839539954

Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. This problem can be effectively addressed by employing reconfigurable intelligent surfaces (RIS). To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communications system. Simulation results showed that LSTM can effectively improve the channel estimation performance of RIS-assisted UAV-enabled wireless communications. © The Institution of Engineering & technology 2023.

关键词： Channel estimation

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Model for Assessment Information Security Awareness Level for Data Stewardship by Understanding the Context of Use 2022

Model for Assessment Information Security Awareness Level fo...

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11th International Conference on Software and computer Applications, ICSCA 2022

作者： Lubis, Muharman Azies Muslim, Abdul Ridho Lubis, Arif Alkhowarizmi, Alkhowarizmi Department of Information System Telkom University Indonesia Department of Computer Engineering and Informatics Politeknik Negeri Medan Indonesia Department of Information Technology Universitas Muhammadiyah Sumatera Utara Indonesia

ISBN: (纸本)9781450385770

The role of data stewardship satisfies various requirement for the users, employee or staff to provide necessary awareness in ensuring information security strategy take place accordingly. It relates to have properly understand the definition and standard across the organization in term of quality, accuracy, workflows, usage, compliance, format and attribute of content and metadata. Unfortunately, many organization have neglected the importance of data stewardship as the assistance for leveraging the valuable asset of data at the optimization capacity. One of advantages that can be generated automatically related to improve the awareness of relevant party within the environment in protecting the information assets based on policy implemented. This study identifies the relationship by accessing data stewardship with the awareness campaign strategy through security awareness domain and resources (SADAR) framework. The study compare between the utilization in the banking industry by using enterprise resource planning (ERP) and in the education with open platform of database management system (DBMS). © 2022 ACM.

关键词： Data Stewardship Security Awareness Assessment

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Path Planning Algorithm for Multiple UAVs Based on Artificial Potential Field 11

Path Planning Algorithm for Multiple UAVs Based on Artificia...

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11th Joint International Information technology and Artificial Intelligence Conference, ITAIC 2023

作者： Ren, Chongde Chen, Jinchao Du, Chenglie Yu, Wenquan School of Software Northwestern Polytechnical University Xi'an China Northwestern Polytechnical University Department of Computer Science Xi'an China North Automatic Control Technology Research Institute Department of Land Unmanned System Research and Development Taiyuan China

ISBN: (纸本)9798350333664

Due to the lower cost and higher maneuverability, unmanned aerial vehicles (UAVs) have found extensive use in both the civilian and military worlds. Path planning, as a crucial problem in the process of UAVs flight, aims to determine the optimal routes for multiple UAVs from various starting points to a single destination. However, because of the involvement of complex conditional constraints, path planning becomes a highly challenging problem. The path planning problem involving numerous UAVs is examined in this research, and a SAAPF-MADDPG algorithm based on Artificial Potential Field (APF) is suggested as a solution. First, a SA-greedy algorithm that can change the probability of random exploration by agents based on the number of steps and successful rounds to prevent UAVs from getting trapped in a local optimum. Then, we design complex reward functions based on APF to guide UAVs to destination faster. Finally, SAAPF-MADDPG is evaluated against the MADDPG, DDPG, and MATD3 methods in simulation scenarios to confirm its efficacy. © 2023 IEEE.

关键词： autonomous navigation deep reinforcement learning multi-agent systems path planning

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The Impact of Information system and technology of Courier Service During Pandemic 7th

The Impact of Information System and Technology of Courier S...

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7th International Conference on Inventive Communication and Computaional Technologies, ICICCT 2023

作者： Siahaan, Andre Timiko Pinajung, Bagas Rizkyka Kennidy Gaol, Ford Lumban Matsuo, Tokuro School of Information System Bina Nusantara University Alam Sutra Tangerang13960 Indonesia Computer Science Department BINUS Graduate Program—Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9789819951659

Courier services are a means of transport that can be used to deliver orders to customers or claim orders from them, and customers can use technology from the courier service like track order to track their order. The use of courier service nowadays is common that every day, people use courier service as their daily means of transport for delivering goods. However, in situations like pandemic, the courier services need to put more effort into their services, so that customers can use courier services with trust. The courier service must be more careful to deliver customer orders or send orders to customers. For this research methodology, the data collection technique using Google Forms and collecting data directly from people about their opinion toward the research have been employed. The result of the data collecting technique is depicted as the usage of the courier service during COVID-19 pandemic starting from March 2020. The results vary every month because not everyone uses the courier service every day. Moreover, the conclusion on why the months starting from March to June do not show high usage of courier service is that the pandemic has not been that worse than the later months, and so, people were going out to deliver or to do activities like shopping or buying groceries on their own. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Information systems

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