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12th International Conference on Recent Trends in computing, ICRTC 2024

作者： Christy Jeba Malar, A. Deva Priya, M. Naveen Kumaran, R. Sanjay Abhishek, J. Bhuvana, S. Karthick, S. Department of Information Technology Sri Krishna College of Technology Tamilnadu Coimbatore India Department of Computer Science and Engineering Karpagam College of Engineering Tamilnadu Coimbatore India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India Department of Computer Science and Engineering SRM Institute of Science and Technology Uttar Pradesh Delhi–NCR Campus Ghaziabad India

ISBN: (纸本)9789819788354

Recent advancements in Smart Assistants (SAs) as well as home automation have captured the attention of both researchers and consumers. Virtual Assistants (VAs) that are speech-enabled are commonly referred to as smart speakers. They offer a wide range of network-based services. In some cases, they seamlessly link to smart environments, introducing innovative and efficient user interfaces. Nevertheless, these devices present their own set of challenges and limitations. The distinctive features of this technology, particularly its hand-free operation handled by voice and implementation of voice-user interface create a unique landscape. Existing technology adoption models, however, fall short in offering a comprehensive explanation for the adoption of this innovative technology. To gain deeper insights into the motivation behind approving and using in-home voice assistants, this work shifts its focus towards examining voice interactions. Utilization of speech recognition for converting speech into text enables constructing an attractive personalized assistant. This development facilitates seamless tasks such as sending emails without manual typing, conducting Google searches without opening the browser, and accomplishing various daily activities including playing music or launching a preferred IDE, all with a single voice command. To assess its performance, the system is seamlessly integrated with home automation (open-source) environment and operated continuously for some days. During this period, users are encouraged to interact with it, and the results demonstrate increased accuracy, reliability and appeal. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Speech recognition

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mLBOA-DML: modified butterfly optimized deep metric learning for enhancing accuracy in intrusion detection system

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Journal of Reliable Intelligent Environments 2023年第3期9卷 333-347页

作者： Prabhakaran, Varun Kulandasamy, Ashokkumar Department of Computer Science and Engineering St.Joseph’s College of Engineering Chennai India Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India

Intrusion detection is a prominent factor in the cybersecurity domain that prevents the network from malicious attacks. Cloud security is not satisfactory for securing the user’s information because it is based on standard protocols. Hence, cloud users cannot fully trust the security offered by cloud service providers. The state-of-the-art techniques create clusters for classes and manually label the unknown classes to detect novel attacks. This notion binds the network traffic associated with each attack together and drifts the similarity between the same attacks. These techniques are often prone to errors and degrade performance. To overcome this drawback, various researchers have developed different intrusion detection system which relies on specific attack patterns to distinguish between normal and abnormal behavior. This paper presents a modified Lagrange interpolated Butterfly optimization algorithm-based deep metric learning (mLBOA-DML) architecture for intrusion detection to detect both host-based and network attacks. DML architecture parameters are optimized utilizing mLBOA algorithm via its global optimization capability for increasing the accuracy of attack prediction. DML algorithm does both feature extraction and classification processes. When evaluated using the UNSW-NB15 and NSL-KDD datasets, the proposed model offers improved accuracy near 99% for both datasets. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Intrusion detection

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Sign-Based Distributed Learning with Byzantine Resilience based on Audit Mechanism

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IEEE Transactions on Information Forensics and Security 2025年 20卷 5774-5788页

作者： Li, Chengxi Xiao, Ming Skoglund, Mikael KTH Royal Institute of Technology Division of Information Science and Engineering School of Electrical Engineering and Computer Science Stockholm 10044 Sweden

In this paper, we study the problem of distributed learning (DL) with devices transmitting sign information of the local gradients to the server under communication constraints, where the devices are susceptible to Byzantine attacks. For this problem, a sign-based gradient descent method with majority vote and stochastic 1-bit quantization (Sign-M-stochastic) has been proposed very recently. However, the Byzantine resilience of Sign-M-stochastic is inherently limited, based on the fact that all Byzantine devices and honest devices participate equally in the training process. To overcome this drawback and enhance the resilience to Byzantine attacks, inspired by the audit-based distributed detection systems, we propose a novel DL method with an audit mechanism (DL-AM). In each iteration, the sign information of the local gradients are obtained by the devices from stochastic 1-bit quantization. All devices, partitioned into groups, send the sign information to the server through multiple paths, both directly and via other devices in the same group. This approach provides the server with additional information about the identities of the devices, which enables the server to form the global model update by aggregating the sign information of different devices with varying weights. We analyze the convergence performance of the proposed method from a theoretical perspective. Finally, numerical results demonstrate the superiority of DL-AM over the baseline methods. © 2005-2012 IEEE.

关键词： Audit mechanism Byzantine resilience convergence analysis distributed learning sign information

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Integration of smart Sensors and Machine Learning Algorithms for Automated Pest Management 1

Integration of smart Sensors and Machine Learning Algorithms...

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1st International Conference on Sustainable Energy Technologies and Computational Intelligence, SETCOM 2025

作者： Yadav, Krrish Roy, Sritama Vellore Institute of Technology School of Computer Science and Engineering Chennai India Vellore Institute of Technology School of Electronics Engineering Chennai600127 India

ISBN: (纸本)9798331520540

This paper presents a new IoT-based approach for agricultural pest control, incorporating machine learning techniques. Traditional pest monitoring methods are labor-intensive and often result in the overuse of pesticides. The proposed system solves this problem by predicting pest populations using environmental data collected via IoT sensors. We use random forest regression and random search cross-validation to predict pests and identify important factors. The system calculates the amount of pesticides based on forecasts, helping farmers optimize use and reduce environmental impact. The experimental results demonstrate the effectiveness of the system in terms of accurate prediction and optimal pesticide application, and thereby providing a scalable and cost-effective solution for sustainable agriculture. © 2025 IEEE.

关键词： Smart agriculture

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Momentum-based Single-Node Injection Attack with Neighbor Suppression Loss 5

Momentum-based Single-Node Injection Attack with Neighbor Su...

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5th International Academic Exchange Conference on science and technology Innovation, IAECST 2023

作者： Shan, Zhiqiang Ding, Yuxin Computer Science and Technology Harbin Institute of Technology Shenzhen Guangdong Nanshan China

ISBN: (纸本)9798350357738

Graph neural networks have been widely used in various fields, but their security has always been of concern. Graph node injection attacks can efficiently attack and evaluate the robustness of graph neural networks. However, current node injection attack methods rarely consider the characteristic of graph data: nodes are mutually correlated rather than independent. This may reduce the success rate of single node attacks against black-box graph neural networks. To address this issue, we propose a single node injection attack method based on momentum gradient and neighbor suppression loss. Specifically, we further optimize neighboring nodes of the target node by utilizing the loss function to enhance the transferability of attacks against black-box models. Moreover, by integrating momentum update, we can stably optimize during iterations to improve the quality of adversarial example. Experimental results demonstrate that compared with the baseline method, the proposed method significantly improves the success rate of single node injection attacks against black-box graph neural networks. This research comes up with an effective approach to enhance the transferability of node injection attacks from the perspective of graph data structures. © 2023 IEEE.

关键词： Graph neural networks

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Pneumonia Detection in Chest X-Rays Using Combined Approach of Deep Learning 2

Pneumonia Detection in Chest X-Rays Using Combined Approach ...

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2nd IEEE International Conference on Networks, Multimedia and Information technology, NMITCON 2024

作者： Aditya Pai, H. Pareek, Piyush Kumar Guruprasad, M.S. Chandrappa, S. Bhargava, Krishna Mit Art Design and Technology University Mit School of Computing Pune India Nitte Meenakshi Institute of Technology Department of Artificial Intelligence and Machine Learning Bengaluru India Department of Computer Science and Engineering Dehradun India School of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350372892

A respiratory infection like pneumonia faces a serious health challenge across the globe, especially in the poor and underdeveloped countries. The pneumonia is affected by various factors like bacteria or viruses. The reason for the affection is due to higher level of pollution, poor air quality, excess of population, poor infrastructure etc. To reduce the threat from pneumonia, there is a need for early and accurate detection of the infection by using chest X-ray images as the most effective diagnostic method. The paper proposes an automated chest X-ray analysis system by using VGG16 architecture and a weighted average ensemble method to enhance diagnostic accuracy. By integrating deep transfer learning, the system overcomes data scarcity issues, achieving a remarkable 99% accuracy on a publicly available dataset. The research underscores the potential of automated systems in improving pneumonia diagnosis, highlighting the urgent need for advanced diagnostics in resource-limited settings. © 2024 IEEE.

关键词： Air quality

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Assessing Quality of Service Performance in SDN Controllers: POX vs. OpenDaylight 6

Assessing Quality of Service Performance in SDN Controllers:...

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6th International Conference on Advancements in computing, ICAC 2024

作者： Lokuliyana, Shashika Wijesiri, Pipuni Jayakody, Anuradha Abeygunawardhana, Pradeep K.W. Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798331517878

This research offers a comparative analysis of Qual-ity of Service (QoS) within Software Defined Networks (SDN) by assessing the POX and OpenDaylight controllers across various network topologies. The results show that OpenDaylight has a 32.59% higher average throughput than POX, demonstrating its superior data handling capabilities. Conversely, POX exhibits a 54.53% lower average delay and an 85.05% higher average jitter compared to OpenDaylight, highlighting its effectiveness in maintaining lower latency and variability in packet transmission times. These contrasting performances provide essential insights for network engineers in selecting the optimal SDN controller based on specific network demands, significantly influencing the overall network efficiency and stability. © 2024 IEEE.

关键词： Quality of service

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Cybersecurity: Threats, Requirements, Deployments, Techniques, System Architecture, and Future Research

Cybersecurity: Threats, Requirements, Deployments, Technique...

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2024 International Conference on Smart Devices, ICSD 2024

作者： Yadav, Ajay Karnatak, Vijay Mishra, Amit Kumar Verma, Shalini Aswal, Pallaw Singh Tripathi, Neha University Institute of Computing Chandigarh University Punjab Mohali India THDC Institute of Hydropower Engineering and Technology Dept. of Computer Science & Engineering Tehri India Graphic Era Hill University Dept. of Computer Science & Engineering Dehradun India Doon Group Of Institution Dept. of Computer Science & Engineering Rishikesh India THDC Institute of Hydropower Engineering and Technology Computer Science and Engineering Tehri India Department of Computer Science & Engineering Dehradun India

ISBN: (纸本)9798350394412

Cybersecurity safeguards computer systems, net- works, and digital information from a wide variety of cyber-attacks. Its major purpose is to protect the privacy of users' data and resources while maintaining their integrity and making them accessible in the digital world. Cybersecurity is an area that receives investment from businesses, individuals, and governments all around the world in order to secure sensitive information, key infrastructure, and digital assets. Protection of Sensitive Information Both individuals and businesses store huge amounts of sensitive information digitally, including personal data, financial records, intellectual property, and trade secrets. This information must be protected in order to prevent unauthorized access or disclosure. The protection provided by cybersecurity prevents this information from being stolen, exposed, or accessed without authorization. Cyberattacks can result in severe financial losses, including theft of funds, fraud, and the expenditures associated with recovering from a cyber incident. It is possible to prevent these types of losses by taking preventative measures. Implementing these strategies helps prevent losses of this nature. In this paper, we propose a system architecture of a generic secure system, which can be deployed for various applications, i.e., smart healthcare, Intelligent Transport Systems (ITS), smart city, etc. We discuss the threats and attacks in cyberspace. Then, we explain the requirements of cybersecurity. Further, we discuss the devastation in the absence of cyber security. We also explain the cybersecurity deployments and techniques under cybersecurity. Then, in the end, some future research directions for cybersecurity are provided. © 2024 IEEE.

关键词： Cyber attacks

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A comprehensive review and open issues on energy aware resource allocation in cloud

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International Journal of Web Engineering and technology 2023年第4期17卷 353-371页

作者： Singh, Shubham Singh, Pawan Tanwar, Sudeep Department of Computer Science and Engineering Amity University Uttar Pradesh Lucknow Campus India Department of Computer Science and Engineering Institute of Technology Nirma University India

Cloud computing is an on-demand service resource that includes applications to data centres on a pay-per-use basis. While allocating resources, the node failure causes the cloud service failures. This reduces the quality of service along with ‘extra’ energy consumption. This survey makes an evaluation on 65 papers regarding energy aware resource allocation (RA) techniques in cloud. The performances and associated highest attainments of each contribution are described in this review. In addition, the tools used for implementing the RA techniques in each paper along with type of workloads were considered. We examine a number of current or developed energy-aware RA approaches for cloud settings in this study. We also provide a thorough analysis of the various energy-conscious RA and selection strategies for cloud-based virtual machines. Lastly, the clear sketch of issues and weakness are determined that may be supportive to resolve the existing problems in this aspect. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Energy utilization

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LAME:Layout-Aware Metadata Extraction Approach for Research Articles

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computers, Materials & Continua 2022年第8期72卷 4019-4037页

作者： Jongyun Choi Hyesoo Kong Hwamook Yoon Heungseon Oh Yuchul Jung Department of Computer Engineering Kumoh National Institute of Technology(KIT)GumiKorea Korea Institute of Science and Technology Information(KISTI) DaejeonKorea School of Computer Science and Engineering Korea University of Technology and Education(KOREATECH)CheonanKorea

The volume of academic literature,such as academic conference papers and journals,has increased rapidly worldwide,and research on metadata extraction is ***,high-performing metadata extraction is still challenging due to diverse layout formats according to journal *** accommodate the diversity of the layouts of academic journals,we propose a novel LAyout-aware Metadata Extraction(LAME)framework equipped with the three characteristics(e.g.,design of automatic layout analysis,construction of a large meta-data training set,and implementation of metadata extractor).In the framework,we designed an automatic layout analysis using PDF *** on the layout analysis,a large volume of metadata-separated training data,including the title,abstract,author name,author affiliated organization,and keywords,were automatically ***,we constructed a pre-trainedmodel,Layout-Meta BERT,to extract the metadata from academic journals with varying layout *** experimental results with our metadata extractor exhibited robust performance(Macro-F1,93.27%)in metadata extraction for unseen journals with different layout formats.

关键词： Automatic layout analysis layout-MetaBERT metadata extraction research article

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