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5th International Conference on Circuits, Control, Communication and Computing, I4C 2024

作者： Sanath, G. Deekshitha, S. Shravya, H. Jayanthi, M.G. Kannadaguli, Prashanth Cambridge Institute of Technology Computer Science and Engineering Bengaluru India Cambridge Institute of Technology Information Science and Engineering Bengaluru India Senior Data Science Trainer Dhaarini Academy Bengaluru India

ISBN: (纸本)9798331528539

Effective monitoring of water quality remains a problem, in real-time contamination detection and prediction. Despite advancements in the sector, many existing approaches continue to rely on labor-intensive laboratory testing, which limits their capacity to give rapid and accurate results. By leveraging advanced ML/DL models, it is possible to build a more robust and adaptable platform for real-time analysis, prediction, and decision support. Approaches based on models such as Random Forest, XGBoost, CNN, RNN, LSTM, and GRU have been good with the accuracy of water quality predictions. They help identify pollution sources and diagnose water quality issues, providing essential information to stakeholders in sustainable water resource management. The ML and DL approaches help improve water quality monitoring and boost future research in environmental sustainability and natural resource management. © 2024 IEEE.

关键词： Resource allocation

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Solving Multi-Objective Vehicle Routing Problems with Time Windows: A Decomposition-Based Multiform Optimization Approach

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Tsinghua science and Technology 2024年第2期29卷 305-324页

作者： Yiqiao Cai Zifan Lin Meiqin Cheng Peizhong Liu Ying Zhou Xiamen Key Laboratory of Data Security and Blockchain Technology College of Computer Science and TechnologyHuaqiao UniversityXiamen361021China College of Engineering Huaqiao UniversityQuanzhou362000China School of Computer Sciences Shenzhen Institute of Information TechnologyShenzhen518000China

In solving multi-objective vehicle routing problems with time windows (MOVRPTW),most existing algorithms focus on the optimization of a single problem formulation. However,little effort has been devoted to exploiting valuable knowledge from the alternate formulations of MOVRPTW for better optimization performance. Aiming at this insufficiency,this study proposes a decomposition-based multi-objective multiform evolutionary algorithm (MMFEA/D),which performs the evolutionary search on multiple alternate formulations of MOVRPTW simultaneously to complement each other. In particular,the main characteristics of MMFEA/D are three folds. First,a multiform construction (MFC) strategy is adopted to construct multiple alternate formulations,each of which is formulated by grouping several adjacent subproblems based on the decomposition of MOVRPTW. Second,a transfer reproduction (TFR) mechanism is designed to generate offspring for each formulation via transferring promising solutions from other formulations,making that the useful traits captured from different formulations can be shared and leveraged to guide the evolutionary search. Third,an adaptive local search (ALS) strategy is developed to invest search effort on different alternate formulations as per their usefulness for MOVRPTW,thus facilitating the efficient allocation of computational resources. Experimental studies have demonstrated the superior performance of MMFEA/D on the classical Solomon instances and the real-world instances.

关键词： MOVRPTW multiform optimization multiform construction knowledge transfer adaptive local search

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Enhanced Clickbait Detection through Ensemble Machine Learning Techniques

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Procedia computer science 2025年 258卷 599-608页

作者： Neetu Sardana Deepika Varshney Seema Luthra Department of Computer Science & Engineering-Data Science ABES Engineering College Ghaziabad India

Nowadays online news websites are one of the quickest ways to get information. However, the credibility of news from these sources is sometimes questioned. One common problem with online news is the prevalence of clickbait. Clickbait uses exaggerated headlines to lure people to click the suspected link, but the content often disappoints the reader and degrades user experience it may also hamper public emotions. The proposed work aims to examine diverse set of models for clickbait detection. The models are formed by integration of Machine learning (ML) and Ensemble learning methods (EL) with Term Frequency and Inverse Document Frequency (TF-IDF) & Embedding technique. Five ML and three EL are analysed &compared. Random Forest along with TF-IDF gave the best results of 85%. The resultant model shows significant improvements with a minimal false-positives.

关键词： Clickbait Detection Machine Learning text classification NLP Ensemble learning Stacking classifir

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Criminal Identification Based On database Management Using Blockchain 4

Criminal Identification Based On Database Management Using B...

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4th International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2024

作者： Suganya, R. Ashok, P. Lekshitha, J. Shanmuga Priya, S. Monica, K. Somasundaram, K. Sri Sai Ram Institute of Technology Department of Computer Science and Engineering Chennai India Saveetha Engineering College Department of Artificial Intelligence and Data Science Chennai India Sri Muthukumaran Institute of Technology Department of Computer Science and Engineering Chennai India

ISBN: (数字)9798331508845

ISBN: (纸本)9798331508845

The crime monitoring system is a unique and authentic project which functions with the concepts of block chain language. Blockchain technology has the potential to revolutionize the management of criminal records by providing a secure network where documents are readily accessible and immune to tampering. This innovation ensures the safety and integrity of sensitive information, offering a robust solution to the challenges posed by traditional recordkeeping system. The basic use of the crime identification system is to maintain and process the criminal records and data that are given by the user. This can be used in the security system during the arrival of dignitary people for the occasional events by recognizing the people based upon the criminal records. Thus, criminals are restricted from entering inside the event. This can also be embedded for the security cameras of the event and are constantly monitored. © 2024 IEEE.

关键词： Records management

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Secure Consumer-Centric Demand Response Management in Resilient Smart Grid as Industry 5.0 Application with Blockchain-Based Authentication

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IEEE Transactions on Consumer Electronics 2024年第1期70卷 1370-1379页

作者： Ayub, Muhammad Faizan Li, Xiong Mahmood, Khalid Shamshad, Salman Saleem, Muhammad Asad Omar, Marwan University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu12599 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan Illinois Institute of Technology Information Technology and Management ChicagoIL60616 United States

The development of the industrial Internet of Things and smart grid networks has emphasized the importance of secure smart grid communication for the future of electric power transmission. However, the current deployment of smart meters and wireless communication methods presents several security concerns that must be addressed to ensure sustainable and resilient smart grid networks for Industry 5.0, with a focus on consumer-centric technologies. In this context, we propose a privacy-focused authentication solution for secure consumer-centric demand response management in smart grid networks, incorporating consumer electronics. Our proposed protocol utilizes blockchain-based authentication to enhance resistance against potential attacks and ensure the integrity of demand response data. Additionally, we have incorporated a PUF to prevent physical attacks. We have conducted informal and formal security analyses to verify the effectiveness of our proposed protocol against various threats and to confirm the session key security. Our comparison study has demonstrated that our protocol provides superior security and added functionalities, with lower computation and communication costs compared to similar protocols. Furthermore, we have measured the computational time for implementing the blockchain component of our protocol while considering the impact of varying numbers of block additions and transactions per block. © 1975-2011 IEEE.

关键词： Authentication

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A Length-Adaptive Non-Dominated Sorting Genetic Algorithm for Bi-Objective High-Dimensional Feature Selection

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IEEE/CAA Journal of Automatica Sinica 2023年第9期10卷 1834-1844页

作者： Yanlu Gong Junhai Zhou Quanwang Wu MengChu Zhou Junhao Wen College of Computer Science Chongqing UniversityChongqing 400044China IEEE Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA College of Big Data and Software Engineering Chongqing UniversityChongqing 400044China

As a crucial data preprocessing method in data mining,feature selection(FS)can be regarded as a bi-objective optimization problem that aims to maximize classification accuracy and minimize the number of selected *** computing(EC)is promising for FS owing to its powerful search ***,in traditional EC-based methods,feature subsets are represented via a length-fixed individual *** is ineffective for high-dimensional data,because it results in a huge search space and prohibitive training *** work proposes a length-adaptive non-dominated sorting genetic algorithm(LA-NSGA)with a length-variable individual encoding and a length-adaptive evolution mechanism for bi-objective highdimensional *** LA-NSGA,an initialization method based on correlation and redundancy is devised to initialize individuals of diverse lengths,and a Pareto dominance-based length change operator is introduced to guide individuals to explore in promising search space ***,a dominance-based local search method is employed for further *** experimental results based on 12 high-dimensional gene datasets show that the Pareto front of feature subsets produced by LA-NSGA is superior to those of existing algorithms.

关键词： Bi-objective optimization feature selection(FS) genetic algorithm high-dimensional data length-adaptive

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A Secure Approach to Avoid data Repetition in Cloud Storage Systems 2

A Secure Approach to Avoid Data Repetition in Cloud Storage ...

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2nd International Conference on Artificial Intelligence and Machine Learning Applications, AIMLA 2024

作者： Swedhaa, M.A. Sathya, V. Vanitha, M. Jothilakshmi, T. Kongunadu College of Engineering and Technology Artificial Intelligence and Data Science Trichy India Mohamed Sathak A.J. College of Engineering Computer Science and Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350349221

Cloud Storage will be current data research and data management field in terms of security and elimination of repeated data-sets. In simple terms, this current research introduces a strong system called "Cloud-SecureDedupe(C-SD)". to make sure data is safe and cloud storage works well. The system helps with a common problem called data repetition, where the same information is stored more than once. "Cloud-SecureDedupe (SDP)"uses a safe method to solve this issue, making sure your data is reliable in cloud storage. It adds extra protection by using advanced techniques to keep important information secure. Additionally, it smartly identifies and removes any repeated data, not only making your data more secure but also saving space in the storage, so it's used more efficiently. The system has been carefully tested and proven to work well, ensuring that your experience with cloud storage is both safe and smooth. © 2024 IEEE.

关键词： Cloud storage

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PALCT: vehicle-to-vehicle communication based on pseudonym assignment and encryption scheme using delay minimisation cover tree algorithm

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International Journal of Vehicle Information and Communication Systems 2025年第2期10卷 132-147页

作者： Tandon, Righa Gupta, P.K. Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Computer Science and Engineering Jaypee University of Information Technology HP Solan173 234 India Department of Data Science School of Computing Mohan Babu University AP Tirupati517 102 India

Vehicle-to-vehicle communication is one of the new paradigms of networking, which should be secure, fast, and efficient. In this paper, we propose a framework that implements the pseudonym-based authentication scheme in which communication among vehicles is encrypted by using a matrix array symmetric key (MASK), digital signature algorithm (DSA), and intelligent water drop (IWD). The proposed security scheme also ensures the handling of many security attacks like key-guessing, non-repudiation, replay, and modification. In the proposed scheme, to preserve the identity of the vehicle, we have provided the different pseudonyms for each vehicle in the network that ensure secure communication among vehicles. Furthermore, the proposed delay minimisation cover tree algorithm ensures the issue of timed delay during vehicle-to-vehicle communication. In this algorithm, we have used Dijkstra’s algorithm for finding the optimal shortest path during vehicular communication. The results obtained show that the proposed scheme is effective and efficient, as it reduces the time delay by 4% for 140 vehicle nodes and 28.4% for 1000 vehicle nodes. Copyright © 2025 Inderscience Enterprises Ltd.

关键词： Encryption algorithms

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An Empirical Investigation of Docker Sockets for Privilege Escalation and Defensive Strategies 5

An Empirical Investigation of Docker Sockets for Privilege E...

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5th International Conference on Innovative data Communication Technologies and Application, ICIDCA 2024

作者： Rajyashree, R. Mathi, Senthilkumar Saravanan, G. Sakthivel, M. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Coimbatore India Department of Artificial Intelligence and Data Science Erode Sengunthar Engineering College Erode India Department of Computer Science and Engineering Erode Sengunthar Engineering College Erode India

Cloud-based infrastructures often leverage virtualization, but its implementation can be expensive. Traditional coding methods can lead to issues when transitioning code from one computing environment to another. In response, the container paradigm emerged to offer cost-effective and agile delivery. Containers differ from full machine virtualization by compactly encapsulating the entire software and its dependencies. Leveraging containers, developers can create more secure and efficient applications. Docker, a prominent containerization platform, facilitates the execution of docker images. The Docker Hub serves as a popular repository for various images. Given the importance of application security, especially in the face of threats like malware, ransomware, and data breaches, ensuring robust security is imperative. The paper investigates vulnerabilities within Docker containers and proposes defensive strategies to mitigate potential breaches. In addition, it investigates attacks involving Docker sockets and suggests preventive measures for non-root users. © 2024 The Authors. Published by Elsevier B.V.

关键词： Containers

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CredAct: Privacy-Preserving Activity Verification for Benefits Schemes in Self-Sovereign Identity 6

CredAct: Privacy-Preserving Activity Verification for Benefi...

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6th IEEE International Conference on Blockchain and Cryptocurrency, ICBC 2024

作者： Mukta, Rahma Paik, Hye-Young Lu, Qinghua Kanhere, Salil S. Unsw School of Computer Science and Engineering Sydney Australia Csiro Data61 Sydney Australia

ISBN: (纸本)9798350316742

We propose CredAct, a user activity verification designed with data minimisation to protect privacy. Many Benefits Schemes, such as discount offers, loyalty programs, and incentive systems, require verification of user activity (e.g., buying healthy food, step counts) in their business processes. These service providers can collect a large amount of users' personal information, and often users do not have fine-grained control over the scope of data disclosure. In CredAct, we propose a Self-Sovereign Identity based framework implemented on blockchain that enables users participating in a benefits scheme to minimise data sharing during the submission and verification of data. We use a smart contract-based function along with a Zero-Knowledge Proof cryptographic commitment scheme, that forces the entities involved in the business process to collect or disclose only the required (minimum) data to fulfill the intended purpose. The evaluation shows that the system is feasible with minimal operational overheads compared to traditional cryptographic techniques. We also perform a qualitative privacy and security analysis considering relevant threats to CredAct. © 2024 IEEE.

关键词： Differential privacy

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