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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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Detection and Taxonomy of Aircraft using Synthetic Aperture Radar Imaging 2

Detection and Taxonomy of Aircraft using Synthetic Aperture ...

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2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Sairam, D.V. Tamilselvi, M. Devi, S Gayathri Bhuvaneswari, R. Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Amrita School of Computing Chennai India Roever Engineering College Department of Computer Science and Engineering Tamilnadu Perambalur India Sri Ramakrishna Institute of Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350317558

Improvements in aircraft detection are necessary to improve surveillance. This work investigates the exact detection and classification of airplanes using YOLOv8 in conjunction with Synthetic Aperture Radar (SAR) photos. SAR imaging performs well in dimly lit and unfavorable environments. The objective is to use YOLOv8's object detection to identify aircraft kinds and categories in SAR pictures. A variety of SAR datasets are gathered, preprocessed, and trained on the model to allow for a thorough assessment of YOLOv8's performance in differentiating between different types of aircraft. Measures that assess model performance across aircraft classes include mean average precision (mAP), recall, and loss. The results demonstrate the effectiveness of YOLOv8 and show promising results in terms of speed and precision. This work drives progress in aerial surveillance by highlighting the robustness of SAR when combined with cutting edge deep learning for aircraft taxonomy. The achieved 98.5% mean average precision (mAP) attests to exceptional performance in aircraft detection and categorization from SAR images, reinforcing the utility of this integrated approach in bolstering security systems. © 2024 IEEE.

关键词： Aerospace Surveillance Aircraft Detection Aircraft Taxonomy Classification Deep Learning Imaging Techniques Machine Learning Synthetic Aperture Radar (SAR)

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Performance comparison of multipath routing protocols for mobile ad hoc network

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International Journal of Systems, Control and Communications 2022年第1期13卷 82-98页

作者： Prasad, Sanjeev Kumar Sharma, Tripti Department School of Computing Science and Engineering Galgotias University NCR India Department Computer Science and Engineering Inderprastha Engineering College NCR India

In mobile ad hoc networks (MANETs), nodes are connected by multihop wireless connections and topology is changing very frequently due to movement of nodes. Therefore, it leads to the need of efficient dynamic routing protocols. Many routing protocols have been proposed for communication in dynamic environments and it is observed that multipath routing protocols are more preferred over the single path routing protocols in terms of many network parameters such as delay, energy consumption etc. These protocols are designed to fulfil the requirements of communication in the network. Therefore, the aim of this paper is to determine the difference between multipath routing protocols when operating in large-area MANETs with the help of constant bit rate, and variable bit rate data-traffic patterns;and these traffic patterns applied on the network with the different speeds and varying simulation pause time. This paper tests the performance of the following multipath protocols AOMDV, BAOMDV, BAMR, and LLECP-AOMDV on the NS-2 network platform. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Mobile ad hoc networks

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PAC-MC: An Efficient Password-Based Access Control Framework for Time Sequence Aware Media Cloud

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IEEE Transactions on Mobile computing 2025年第7期24卷 5632-5648页

作者： Wang, Haiyan Liu, Penghui Zhong, Xiaoxiong Luo, Fucai Xiao, Bin Yang, Yuanyuan Peng Cheng Laboratory Department of New Networks Shenzhen518000 China Zhejiang Gongshang University School of Computer Science and Technology Hangzhou China Hong Kong Polytechnic University Department of Computing Hong Kong Stony Brook University Department of Electrical and Computer Engineering Stony BrookNY11794 United States

Cloud storage makes it easier for users to access and share data remotely, but it often requires integration with cryptographic technologies to address consumer-oriented applications, such as fine-grained data access, secure data sharing and retrieval. This paper focuses on the fine-grained access problem of media applications based on time sequence, that is, certain critical media applications based on time sequences should ideally be accessible only to authorized clients. The traditional keyword-based searchable encryption (SE) allows effective search and access over encrypted data while preserving data privacy, but most existing solutions do not support temporal access control (i.e., a mechanism that grants access permissions to users within a specified time range). In this paper, we propose PAC-MC, an efficient password-based access control framework for media cloud relying on content control with the time sequence attribute. PAC-MC not only supports multi-keyword search using any monotonic boolean formulas but also allows media owners to control content-encryption keys for different time periods with an updatable password. Furthermore, it supports the self-retrieval of content-encryption keys. In addition, PAC-MC is provably secure under the standard model. Finally, the detailed performance evaluation results and experimental comparisons indicate that PAC-MC is very efficient and outperforms the previous solutions in terms of computation, communication, and storage costs. © 2025 IEEE.

关键词： Media Encryption Access control Cloud computing Servers Passwords Keyword search Copyright protection Streaming media Performance evaluation

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Intelligent Decision Support Systems: Transforming Smart Cities Management 1

Intelligent Decision Support Systems: Transforming Smart Cit...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Ahmed, Zeinab E. Hashim, Aisha H.A. Mokhtar, Rania A. Saeed, Mamoon M. Department of Computer Engineering University of Gezira Sudan Department of Electrical and Computer Engineering International Islamic University Malaysia Malaysia Department of Computer Engineering College of Computers and Information Technology Taif University Saudi Arabia Yemen

ISBN: (纸本)9798331533557

Since urban cities are expanding due to technology, economy, and influx of more people the need for better management systems is paramount. This paper aims to examine the use of Intelligent Decision Support Systems (IDSS) in enhancing the urban infrastructure, safety and resources in smart cities. Hereby, we present a complex framework that involves Internet of Things (IoT) devices, Neural Networks, Artificial Intelligence (AI) to make decisions in traffic controlling, environmental issues and safety. When used with machines learning (ML) algorithms and predictive analytics, the framework increases the efficiency of urban management operations. A comparison of the energy used by promised by these algorithms including LSTM, SVM, KNN, and the OPTIMUS, a system is developed that enables smart cities to significantly save energy hence highlighting its efficiency. Furthermore, a performance comparison of Random Forest, LSTM, SVM, and KNN for traffic management shows KNN achieving the highest accuracy and precision. The paper discusses data collection, processing, and integration methodologies, and presents case studies demonstrating cost reductions and sustainability improvements. The present paper provides evidence to support the assumption that the development of IDSS can greatly enhance the progress of smart cities by underpinning the process by data, feedback and other forms of information. © 2024 IEEE.

关键词： Sustainable city

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Machine Learning-Based Models for Magnetic Resonance Imaging(MRI)-Based Brain Tumor Classification

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Intelligent Automation & Soft computing 2023年第4期36卷 299-312页

作者： Abdullah A.Asiri Bilal Khan Fazal Muhammad Shams ur Rahman Hassan A.Alshamrani Khalaf A.Alshamrani Muhammad Irfan Fawaz F.Alqhtani Department of Radiological Sciences College of Applied Medical SciencesNajran UniversityNajranSaudi Arabia Department of Computer Science City University of Science and Information TechnologyPeshawarPakistan Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan Department of Computer Science Engineering University of Engineering and TechnologyMardan23200Pakistan Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia

In the medical profession,recent technological advancements play an essential role in the early detection and categorization of many diseases that cause *** technique rising on daily basis for detecting illness in magnetic resonance through pictures is the inspection of ***(computerized)illness detection in medical imaging has found you the emergent region in several medical diagnostic *** diseases that cause death need to be identiﬁed through such techniques and technologies to overcome the mortality *** brain tumor is one of the most common causes of *** have already proposed various models for the classiﬁcation and detection of tumors,each with its strengths and weaknesses,but there is still a need to improve the classiﬁcation process with improved efﬁ***,in this study,we give an in-depth analysis of six distinct machine learning(ML)algorithms,including Random Forest(RF),Naïve Bayes(NB),Neural Networks(NN),CN2 Rule Induction(CN2),Support Vector Machine(SVM),and Decision Tree(Tree),to address this gap in improving *** the Kaggle dataset,these strategies are tested using classiﬁcation accuracy,the area under the Receiver Operating Characteristic(ROC)curve,precision,recall,and F1 Score(F1).The training and testing process is strengthened by using a 10-fold cross-validation *** results show that SVM outperforms other algorithms,with 95.3%accuracy.

关键词： MRI images brain tumor machine learning-based classiﬁcation

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Survey on Video Security:Examining Threats,Challenges,and Future Trends

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computers, Materials & Continua 2024年第9期80卷 3591-3635页

作者： Ali Asghar Amna Shifa Mamoona Naveed Asghar Department of Artificial Intelligence Faculty of ComputingThe Islamia University of BahawalpurBahawalpur63100Pakistan School of Computer Science College of Science and EngineeringUniversity of GalwayGalwayH91 TK33Ireland

Videos represent the most prevailing form of digital media for communication,information dissemination,and ***,theirwidespread use has increased the risks of unauthorised access andmanipulation,posing significant *** response,various protection approaches have been developed to secure,authenticate,and ensure the integrity of digital *** study provides a comprehensive survey of the challenges associated with maintaining the confidentiality,integrity,and availability of video content,and examining how it can be *** then investigates current developments in the field of video security by exploring two critical research ***,it examine the techniques used by adversaries to compromise video data and evaluate their *** these attack methodologies is crucial for developing effective defense ***,it explores the various security approaches that can be employed to protect video data,enhancing its transparency,integrity,and *** compares the effectiveness of these approaches across different use cases,including surveillance,video on demand(VoD),and medical videos related to disease ***,it identifies potential research opportunities to enhance video data protection in response to the evolving threat *** this investigation,this study aims to contribute to the ongoing efforts in securing video data,providing insights that are vital for researchers,practitioners,and policymakers dedicated to enhancing the safety and reliability of video content in our digital world.

关键词： Attacks threats security services video manipulation video security

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Exploring the Role of Internet of Things in Wireless Sensor Networks for Industry 4.0 Applications 1

Exploring the Role of Internet of Things in Wireless Sensor ...

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1st International Conference on Pioneering Developments in computer Science and Digital Technologies, IC2SDT 2024

作者： Palarimath, Suresh Maran, Pyingkodi N.r, Wilfred Blessing Sujatha, T. Renuga, S. R.s, Chithra College of Computing and Information Sciences University of Technology and Applied Sciences Salalah Oman Kongu Engineering College Department of Computer Application Erode India College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman Sri Krishna College of Engineering and Technology Department of Artificial Intelligence and Data Science Coimbatore India Panimalar Engineering College Department of Artificial Intelligence and Data Science Chennai India Ponjesly College of Engineering Department of Computer Science and Engineering Kanyakumari India

ISBN: (纸本)9798350365016

Recent developments in computer networking have made it possible to access information from a faraway location via either wireless or wired networks. The recent advancements in wireless infrastructure are directly responsible for the advent of wireless sensor networks, often known as WSNs. These networks make it easier to keep track of environmental happenings and activities, as well as document them and manage them. In WSNs, data relaying is accomplished through the use of a variety of routing strategies. Industry 4.0, also known as the fourth industrial revolution, is characterized by the incorporation of highly developed physical automation systems. These systems are made up of several pieces of machinery and gadgets that are linked together by sensors and are operated by software. The goal of the fourth industrial revolution is to improve the effectiveness and dependability of business processes. The Internet of Things (IoT) can be leveraged in manufacturing, which gives a means of linking engines, power grids, and sensors to the cloud in an industrial context. This is accomplished through the use of Industrial IoT. The purpose of this paper is to gain an understanding of how the Internet of Things functions in wireless sensor networks and its possible applications in a variety of settings. © 2024 IEEE.

关键词： Wireless sensor networks

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The Smart Analysis of Poisson Distribution Pattern Based Industrial Automation in Industry 4.0 2

The Smart Analysis of Poisson Distribution Pattern Based Ind...

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2nd IEEE International Conference on Distributed computing and electrical Circuits and Electronics, ICDCECE 2023

作者： Shashikala, H.K. Dalal, Surjeet Department of Computer Science and Engineering Bangalore India Teerthanker Mahaveer University College of Computing Science & It Department of Computing Science & It Moradabad India

ISBN: (纸本)9798350347456

Industry 4.0 is the term used to describe the fourth industrial revolution, which is characterized by the use of advanced technologies such as artificial intelligence, the Internet of Things, and big data analytics. One of the patterns that is commonly found in Industry 4.0 is the Poisson distribution pattern, which describes how certain real-world events are distributed over time. This pattern can be used to measure how often certain events occur and how long it takes for them to occur. The Poisson distribution is a type of probability distribution that is used to model the frequency of events over a given period of time. This pattern is characterized by a short-term burst of events, followed by a longer period of less frequent events. This pattern is especially useful in Industry 4.0, as it can be used to predict the occurrence of certain events, such as machine failures or maintenance alerts. It can also be used to identify potential bottlenecks or areas of improvement in the production process. The Poisson distribution pattern is an important tool in Industry 4.0. It can be used to identify potential problems, optimize production processes, and improve efficiency. By leveraging this pattern, manufacturers can ensure that their production processes are running smoothly and efficiently. © 2023 IEEE.

关键词： Industry 4.0

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Traffic Condition Prediction for Urban and Highway Scenarios using Artificial Intelligence 2

Traffic Condition Prediction for Urban and Highway Scenarios...

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2nd IEEE International Conference on Distributed computing and electrical Circuits and Electronics, ICDCECE 2023

作者： Mathur, Ashwini Bishnoi, Ashish Department of Computer Science and Engineering Bangalore India Teerthanker Mahaveer University College of Computing Science & It Department of Computing Science & It Moradabad India

ISBN: (纸本)9798350347456

A major study topic, particularly in machine learning and artificial intelligence, has resulted from the prediction of traffic congestion in recent years (AI). During the last few decade, this study field has greatly increased due to the emergence of huge data from stationary sensor or probe vehicle data. Congestion forecasting requires analysing a wide range of traffic variables, especially for short-term planning. Predictions of future traffic congestion are based mostly on analyses of past patterns. Using traffic data like taxi trip records, urban traffic statistics, and junction counts, we propose a new method for calculating traffic flows. The suggested method makes use of CGAN and GCN, and we enhanced Unet to realise a key component of the generator. The interaction between junctions with surveillance and intersections without monitoring is then captured using floating taxis that are spread out over the whole city. The CGAN architecture may modify the weights and improve the inference capability to provide an accurate traffic status under the present circumstances. The results of the experiment demonstrate that our technique is more accurate at estimating traffic volume than other methods. © 2023 IEEE.

关键词： Traffic congestion

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