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Integration of Blockchain in computer Networking: Overview, Applications, and Future Perspectives for Software-defined Networking (SDN), Network security, and Protocols 10

Integration of Blockchain in Computer Networking: Overview, ...

引用

10th international conference on Software Defined systems, SDS 2023

作者： Hossain Faruk, Md Jobair Cheng, Jerry Q. New York Institute of Technology Department of Computer Science United States

ISBN: (纸本)9798350382235

The rapid advancement and increasing complexity of computer networks have created a need for robust, secure, and scalable solutions in order to manage and protect network resources. Blockchain, an emerging distributed ledger technology, offers enhanced security, transparency, and privacy preservation. As a result, Blockchain is regarded as a promising solution to network challenges. However, limited research has been conducted in this area so far which highlights the necessity for further in-vestigation and exploration. This paper presents a comprehensive study of blockchain integration in computer networking, focusing on its potential applications, benefits, and future perspectives in Software-defined Networking (SDN), network security, and networking protocols. We identify that blockchain's tamper-proof nature could significantly improve network security by mitigating risks associated with centralized control and single points of failure. The integration of blockchain in computer networking has the potential to increase trust and transparency among network participants, as it allows for secure, verifiable, and auditable transactions and communication. Blockchain also can streamline the management of Software-defined Networking (SDN) by enabling decentralized and automated network control, resource allocation, and orchestration. Additionally, We also find that utilizing blockchain can address network challenges, such as mitigating DDoS attacks, enhancing intrusion detection and prevention, and securing routing protocols. Meanwhile, we also identify potential limitations of blockchain integration in computer networking, such as scalability challenges arising from the growing size of the distributed ledger and increasing network traffic. We emphasize the need for further research in optimizing consensus mechanisms, enhancing scalability and privacy preservation techniques interoperability, and facilitating standardization of networking protocols and practices. © 2023

关键词： Network security

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Enhancing Intrusion Detection in Smart Grids: A Machine Learning-based Defense Against DDoS Attacks with Imbalance-Aware Optimization 3

Enhancing Intrusion Detection in Smart Grids: A Machine Lear...

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3rd international conference on Electronics and Renewable systems, ICEARS 2025

作者： Mahaveerakannan, R. Kumar, T. Rajesh Balamanigandan, R. Vasarao, Parnandi Srinu Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai602105 India Swarnandhra College of Engineering and Technology Department of Computer Science and Engineering West Godavari District Andhra Pradesh Narsapur India

ISBN: (纸本)9798331509675

The presence of numerous bidirectional communication devices connecting customers to the grid makes smart grid networks particularly vulnerable to network attacks. As an instance of a network attack that could impact the smart grid, a distributed denial of service (DDoS) attack occurs when a compromised grid communiqué devices or nodes send a flood of false data or requests to the smart grid network. This can cause problems with smart meters, data servers, and the state estimator, which in turn affects the services that end users receive. The problem of protecting the network from distributed denial of service (DDoS) attacks is best addressed by methods that rely on machine learning. One major drawback of using machine learning-based approaches is that models need to be retrained every time new types of attacks appear. Despite the fact that DDoS attack detection has long relied on Intrusion Detection systems (IDS), previous research has been limited due to a number of factors. Actually, it is highly discouraged to interfere with the regular functioning of the smart grid. to suggest using reconstructive deep learning methods to identify DDoS attacks efficiently and with minimal downtime in order to tackle this difficulty. In order to identify typical attacks on a communication network, this research introduces a shallow neural network with just 110 artificial neurones triggered by ReLU. to suggest a better attack-sharing loss function to handle unbalanced learning, which will allow for the training of such tiny neural networks. A Lungs Performance-based Optimisation (LPO) was devised using the suggested model to hone the parameters. In smart grid settings, our suggested approach improves the scalability and dependability of IDS and provides useful insights for building strong IDS based on machine learning. This enables organisations to strengthen their defences against harmful cyber-attacks and proactively reduce security risks. © 2025 IEEE.

关键词： Network intrusion

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Design and Comprehensive Review on Number of Different States of the Art Works Related to Botnet Attack Detection

Design and Comprehensive Review on Number of Different State...

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2024 MIT Art, Design and Technology School of Computing international conference, MITADTSoCiCon 2024

作者： Bobade, Sandip Y. Apare, Ravindra S. Borhade, Ravindra H. SMT. Kashibai Navale College of Engineering SPPU Computer Engineering Dept Pune India Trinity College of Engineering and Research SPPU IT Department Pune India College of Engineering SPPU STES Smt. Kashibai Navale Department of Computer Engineering Pune India

ISBN: (纸本)9798350362879

The Internet of Things is a novel example for communication which use the internet to connect a extensive range of common place things. A new age of clever gadgets that are effortlessly integrated into our day-To-day lives has arrived as a outcome of its rapid proliferation. Intelligent homes, intelligent offices, smart utilities, intelligent healthcare, intelligent farming, intelligent transportation, intelligent villages, and more have all seen creative uses spurred by this game-changing technology. These applications have the ability to significantly improve our quality of life by enabling proactive, self-governing systems that don't require constant human interaction. Additionally, IoT applications and devices have been smoothly incorporated into key infrastructures, which include transportation networks, healthcare facilities, nuclear power plants, water treatment centres, and power plants. Their integration into these crucial areas has resulted in enhanced functioning and accessibility. capabilities for remote management enable. However, at the same time as IoT has becoming widely adopted, major cyber security flaws have also been exposed. These weaknesses include passwords that are hardcoded and security setups that aren't up to par. The systemic problems can be attributed to IoT providers' past disregard for strong security protocols. Numerous research projects have proposed machine learning centred methods to detect threats like malware networks and distributed Denial of Service (DDoS) assaults in response to these security challenges. Interestingly, these methods have demonstrated that applying optimization algorithms can significantly increase machine learning accuracy. Still, there is a constant search for more sophisticated methods, driven by the need to overcome the limitations that come with making mistakes. © 2024 IEEE.

关键词： Internet of things

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Industrial Network Protocol security Enhancement Using Programmable Switches 14

Industrial Network Protocol Security Enhancement Using Progr...

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14th IEEE international conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2023

作者： Hu, Zheng Lin, Hui Waind, Luke Qu, Yanfeng Chen, Gong Jin, Dong University of Arkansas Computer Science and Computer Engineering FayettevilleAR United States The University of Rhode Island Electrical Computer and Biomedical Engineering KingstonRI United States Illinois Institute of Technology Computer Science ChicagoIL United States

ISBN: (纸本)9781665455541

There has been a growing concern regarding the security of industrial network protocols in Supervisory Control and Data Acquisition (SCADA) systems. These protocols are vulnerable to a plethora of security threats, including man-in-the-middle attacks, denial-of-service attacks, malformed packets, and other forms of abuse that exploit the vulnerabilities in protocol specifications. One of the widely used protocols is the distributed Network Protocol 3 (DNP3), making it a crucial target for security enhancement efforts. In this paper, we explore programmable networks for security enhancement of SCADA systems, in particular, P4 switches that can be programmed to perform specified operations at the data plane level. We identify security needs and gaps in existing cyberattacks on DNP3-based SCADA systems and then explore various techniques on the P4 switches, such as packet header and payload inspection, filtering, hashing, and encryption, to combat security threats specific to the DNP3 protocol. We demonstrate that using programmable switches to improve DNP3 security can effectively detect, mitigate, and prevent various forms of attacks with three case studies that are specific to DNP3-based SCADA systems, including Length Overflow Attack (malformed packet), Event Buffer Flooding Attack (denial-of-service), and Config Corrupt Attack (man-in-the-middle attack). © 2023 IEEE.

关键词： Network security

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A Short Survey of AI-driven Load Distribution for Electronic Health Record Management with Recent Deployed Techniques, Research Gaps and Challenges 5

A Short Survey of AI-driven Load Distribution for Electronic...

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5th international conference on Smart Electronics and Communication, ICOSEC 2024

作者： Suryanarayanaraju, S. Naik, M.Chandra Jagan Mohan, R.N.V. Giet University Department of Computer Science & Engineering Odisha Gunupur765022 India Department of Computer Science & Engineering Chinamiram534204 India

ISBN: (纸本)9798331504403

With the arrival of Artificial Intelligence (AI), the Internet of Things (IoT), machine learning, and deep learning methodologies, data-driven medical applications have appeared as a promising solution for implementing scalable and robust prognostic and diagnostic approaches with the utilization of medical data. These technologies attained a lot of interest from academia and industry and led to insightful advancements in healthcare systems. The AI-driven techniques related to medical applications still face several issues including privacy, security, and Quality-of-Service (QoS) standards. The complex machine learning models are effectively trained via Federated Learning (FL) in a distributed manner, this advanced technique has become an attractive research area, especially in processing healthcare data at the network edge in a decentralized way to address security concerns and preserve privacy of the information. The availability of FL in the medical domain has several benefits, but it has not been explored to its extent. Existing review works related to FL mainly concentrated on the importance of FL in diverse applications, but no brief or comprehensive survey exists on the distribution of Electronic Health Records (EHR). Thus, this review work focuses on various techniques of AI-driven load distribution for federated networks on EHR. For this purpose, a detailed literature survey is conducted on AI-driven load distribution framework for federated networks on EHR from the previous decades. The AI techniques employed for disease detection are analyzed and categorized. The dataset details, performance metrics, and simulation tools are gathered and listed for a better understanding of the process. Subsequently, the research gaps on the conventional AI-driven load distribution framework for federated networks on EHR are provided to facilitate future work. © 2024 IEEE.

关键词： Electronic health record

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XMeta-OS: A Conceptual Framework for Unified Resource Management in distributed Edge-Cloud Environments 3rd

XMeta-OS: A Conceptual Framework for Unified Resource Manag...

引用

3rd international conference on Advances in Computing Research, ACR 2025

作者： Zacharioudakis, Eleftherios Kakoulli, Elena Evripidou, Salomi Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos Pafos Cyprus National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9783031876462

This paper introduces XMeta-OS, a meta-operating system specially designed with Linux as its foundation to unify and optimize resource management for the distributed edge-cloud when dynamic use of GPU resources is possible. This approach offer a new GPU abstraction layer and dynamic edge-cloud allocation model that offer enhanced flexibility and resource utilization over existing systems like Kubernetes and OpenStack. By using likely sensitive data, the model applied cloud-pushed deployment model. XMeta-OS manages computer resources in real-time. Therefore, fulfilling high performance various needs. It allocates CPU and GPU in real-time to workloads requiring massive parallel processing, such as machine learning, scientific simulations, real-time data analytics, and transportation tasks. Fabrication in the laboratory of an edge-cloud environment can help to assess the scalability, fault tolerance and efficiency of the system. It showcases the overall architectural design of XMeta-OS. Changes to the kernel and security solutions for safe and effective distribution are suggested. This article presents the design of the XMeta-OS. The future of XMeta-OS entails usage and testing with which we see latency, energy, computation and other such measurements in labs. XMeta-OS is a solution to cost performance, emerging application, large-scale edge-cloud deployments, and distributed GPU-enabled infrastructures. Meta-Operating System in Edge-Cloud Continuum for dynamic resource management of GPU. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cluster computing

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DDoS-Net: Classifying DDoS Attacks in Wireless Sensor networks with Hybrid Deep Learning 6

DDoS-Net: Classifying DDoS Attacks in Wireless Sensor Networ...

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6th international conference on Electrical Engineering and Information and Communication Technology, ICEEICT 2024

作者： Reza, Farhana Brac University Department of Computer Science and Engineering Dhaka1212 Bangladesh

ISBN: (纸本)9798350385779

With the ubiquitous deployment of Wireless Sensor networks (WSNs) in diverse applications, ensuring their security against cyber threats is imperative. One significant challenge is the susceptibility of WSNs to distributed Denial of Service (DDoS) attacks, necessitating effective countermeasures. This research addresses the critical issue of DDoS attacks in WSNs, recognizing the diverse and imbalanced nature of WSN data. The imbalance poses challenges for intrusion detection systems, and existing solutions often fall short in providing comprehensive protection. The study introduces DDoS-Net, a hybrid Deep Learning (DL) model that integrates Long Short-Term Memory (LSTM) and Multi-Layer Perceptron (MLP) architectures. DDoS-Net is designed to handle data imbalance effectively and incorporates thorough feature analysis to enhance the model's detection capabilities. Evaluation on the WSN-BFSF dataset demonstrates the exceptional performance of DDoS-Net. The model achieves an accuracy of 98.12%, precision of 98.16%, recall of 98.12%, and an impressive f1-score of 0.98 in minimal epochs. These results surpass existing state-of-the-art models, showcasing the efficacy of the proposed DL approach in countering DDoS threats in WSNs. © 2024 IEEE.

关键词： Wireless sensor networks

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QoS Based Hybrid Swarm Intelligent Intrusion Detection System for Network security 14

QoS Based Hybrid Swarm Intelligent Intrusion Detection Syste...

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14th international conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Karthikeyan, N. Bhargav, Jajjara Kavitha, M.S. Karthik, S. Sns College of Technology Department of Computer-Science and Engineering Coimbatore India

ISBN: (纸本)9798350335095

The proliferation of Internet usage and the wide range of military applications have prompted scholars to consider the development of intelligent systems that can aid users and applications in obtaining services by providing the necessary quality of service in networks. Certain intelligent techniques are suitable for ensuring security in communication within distributed environments, including but not limited to mobile technology, e-commerce, communication, and managing networks. Multicast routing techniques can assist modern applications utilizing highly efficient data networks in fulfilling QoS requirements. The objective of this methodology is to reduce the network burden during a multicast session. To achieve this objective, it is crucial to minimize the overall expense of the multicast tree or the expenses associated with the links that constitute the multicast tree. We describe a unique approach that leverages Artificial Bee Colony (ABC) operators in conjunction with the Genetic Algorithm (GA) in order to alleviate the restrictions that are caused by the techniques that are currently in use. In addition to this, identification is used across a variety of communication nodes in order to determine the presence of people within the premises. As a consequence of this, security precautions have been taken. © 2023 IEEE.

关键词： Genetic algorithms

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Ensuring Confidentiality and Integrity of Electronic Health Records in Blockchain Through Multi-Attribute Access Control

Ensuring Confidentiality and Integrity of Electronic Health ...

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international Health Informatics conference, IHIC 2023

作者： Mahapatro, Smita Basha, Syed Muzamil Department of Computer Science and Engineering REVA University Bengaluru560064 India

ISBN: (纸本)9789819771899

The digitalization of traditional healthcare data, such as Electronic Health Records (EHR), presents significant challenges for healthcare organizations. Sharing and storing EHRs can be difficult, and accessing the information can be time consuming and sometimes inaccurate due to limited access. To address these issues, this article suggests a permission-based blockchain-based system for sharing healthcare data. This system uses multiple attribute encryption based on cipher text to protect data privacy and authenticate healthcare information. Additionally, it integrates blockchain technology (also knownas distributedLedgerTechnology) with an RSAcryptosystem for added security. The proposed system employs a multi-attribute access control mechanism along with an RSA cryptosystem to achieve strong data security. The ultimate goal of this technology is to create a single platform that stores and distributes health information using a distributed Ledger-based approach. This eliminates the need for printed healthcare reports, streamlining the entire medical business onto one secure platform. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electronic health record

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Decentralized Metaverse: Towards a Secure, Autonomous, and Inclusive Virtual World

Decentralized Metaverse: Towards a Secure, Autonomous, and I...

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2023 IEEE international conference on Electrical, computer and Energy Technologies, ICECET 2023

作者： Alsamhi, Saeed Hamood Hawbani, Ammar Kumar, Santosh Porwol, Lukasz Curry, Edward Insight Centre for Data Analytics University of Galway Galway Ireland School of Computer Science Shenyang Aerospace University Shenyang China Computer Science and Engineering Iiit Naya Raipur Chhattisgarh India

ISBN: (纸本)9798350327816

The metaverse is a universal and immersive virtual world, which are components of cyber-physical-social systems (CPSS). The traditional centralized approach to building a metaverse poses risks to user privacy, security, and autonomy. A growing movement towards a decentralized metaverse, built on blockchain and distributed networks, has emerged as a response. This paper presents a conceptual framework for building a de-centralized metaverse emphasising security, user autonomy, and inclusivity within situation-aware CPSS. Drawing on literature from blockchain, virtual worlds, and decentralized systems, we explore the technical and regulatory challenges that must be addressed to create a more secure, autonomous, and inclusive virtual world. Our framework highlights the importance of community-driven governance and transparent data management for building a decentralized metaverse that empowers users and promotes collaboration. © 2023 IEEE.

关键词： Blockchain Cyber-Physical-Social systems Decentralization Metaverse Situation Awareness

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