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Reduce Low-Frequency distributed Denial of Service Threats by Combining Deep and Active Learning 1

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9th international conference on Cyber security, Privacy in Communication networks, ICCS 2023

作者： Shukla, Aditya Kumar Sharma, Ashish Sengar, Sandeep Singh Department of Computer Engineering and Applications GLA University NH#2 Delhi Mathura Highway Post Ajhai Uttar Pradesh Mathura India Department of Computer Science Cardiff School of Technologies Cardiff Metropolitan University Cardiff United Kingdom

ISBN: (数字)9789819739738

ISBN: (纸本)9789819739721

This study introduces substantial contributions to the field of Low-Rate Detection of Distribution Denial of Service (DDoS) Attacks, leveraging convolutional neural networks (CNNs) with an attention mechanism and incorporating active learning with semi-labelled data. These contributions collectively enhance the accuracy, efficiency, and adaptability of DDoS detection systems. Additionally, the study introduces active learning strategies into the learning process. By actively selecting instances for manual labelling, the study reduces the burden of extensive manual labelling efforts and enhances the model’s scalability. In the dynamic realm of cybersecurity, where threats evolve rapidly, active learning ensures the model’s adaptability with minimal human intervention. Furthermore, this research addresses the challenge of scarce labelled data in real-world cybersecurity contexts. By harnessing semi-labelled data efficiently and pairing it with active learning, the study streamlines the detection and defence against DDoS assaults with low attack rates. This is particularly relevant in situations where procuring an abundance of labelled data is impractical or cost-prohibitive. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Active learning Attention mechanism CNNs Cybersecurity Low-rate DDoS detection Semi-labelled data Threat mitigation

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Clustering by Improved PSO based Jaya Algorithm for Energy Optimization of Wireless Sensor networks 5

Clustering by Improved PSO based Jaya Algorithm for Energy O...

引用

5th IEEE international conference on Electrical, computer and Communication Technologies, ICECCT 2023

作者： Malarvizhi, P. Kavithaa, G. Computer Science and Engineering Knowledge Institute of Technology Salem India Electronics and Communication Engineering Government College of Engineering Salem India

ISBN: (纸本)9781665493604

In recent years, industries have automated processes which mean the amount of human participation has decreased, resulting in the Fourth Industrial Revolution. A highly distributed self-organizing system known as a Wireless Sensor networks is employed in so many control systems such as monitoring the surroundings, automate the reporting, and detecting the event. High bandwidth needs, high power consumption, security and quality of service delivery are some of the obstacles that wireless sensor networks must overcome. Each sensor node in a wireless sensor networks has a different power consumption rate based on the non-uniformity of event detection and the interspace between the sink node and sensor node. This shortens the lifespan of the network and causes an energy difference between the sensor nodes. Particle Swarm Optimization based Jaya algorithm (PSO-J) has been experimented to lower the power consumption of the sensor node by improving the selection of cluster head. The proposed algorithm provides better results than existing clustering algorithms. © 2023 IEEE.

关键词： Sensor nodes

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User Mobility Prediction in 5G networks Using Recurrent Neural networks

User Mobility Prediction in 5G Networks Using Recurrent Neur...

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2024 IEEE international conference on Communication, Computing and Signal Processing, IICCCS 2024

作者： Shrestha, Anubhav Sharma, Vikalp Hussein, Layth Aishwarya, M. Satyanarayana, A.N. Saimanohar, T. Chandigarh Group of Colleges Chandigarh Engineering College Department of Computer Application Punjab Jhanjeri Mohali140307 India Ies College of Technology Department of Computer Science & Engineering M.P. Bhopal India The Islamic University College Of Technical Engineering Department Of Computers Techniques Engineering Najaf Iraq The Islamic University Of Al Diwaniyah College Of Technical Engineering Department Of Computers Techniques Engineering Al Diwaniyah Iraq Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Sreenidhi Institute of Science and Technology Ece Department Hyderabad India Saveetha Institute of Medical and Technical Sciences Department CSE-AI Tamilnadu Chennai India

ISBN: (纸本)9798350390759

The use of new possibilities introduced by 5G networks also creates new problems and concerns, specifically in the field of user mobility in wireless communication systems. In this paper, the Authors investigate the effectiveness of Recurrent Neural networks (RNNs) in the mobility prediction context in order to exploit the temporal component in the users movement data for improved prediction performance. To drive this process, the input datasets are obtained from the GeoLife GPS Trajectories dataset, then follow the data pre-processing steps, constructing an LSTM-based RNN model, and using Python with TensorFlow and Keras. From the analyses, we detected that the accomplishment of using LSTM and hybrid RNN-CNN is significant and higher than the traditional approaches of EN, RFM, and CL. The test results demonstrate that the LSTM model can reduce the MAE and RMSE values by 19. 49% and 14. 82%, respectively. However, the execution of these models has some issues that include compute time, instantaneous prediction that is needed in many real-world applications, and case. Such problems can be solved with the help of such approaches as edge computing and distributed processing. Besides, it is pivotal to put measures in place to maintain the confidentiality and security of user information. This paper highlights the applicative potential of RNNs in redesigning user mobility prediction in 5G networks, and thus helping toward a better ownership of the network players and assets. © 2024 IEEE.

关键词： 5G mobile communication systems

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Network Intrusion Detection Using Deep Belief Network (DBN) 2

Network Intrusion Detection Using Deep Belief Network (DBN)

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2nd international conference of Intelligent Methods, systems and Applications, IMSA 2024

作者： Elsersy, Wael Farouk Samy, Moataz Elshamy, Ahmed Faculty of Computer Science Giza Egypt

ISBN: (纸本)9798350362633

The escalating Interconnectedness of devices has given rise to a surge in cyber-security threats, particularly zero-day attacks, which pose a significant challenge to traditional Intrusion Detection systems (IDSs). This paper delves into the realm of behavior-based IDSs, leveraging Deep Neural networks (DNNs), with a specific focus on the detection of network attacks. The effectiveness of these systems is closely tied to the quality of the training Dataset, where underrepresented samples can compromise detection performance, Our research centers on the development and evaluation of Deep Belief networks (DBNs) as a robust solution for detecting cyber-attacks within networks of connected devices. The cornerstone of our investigation is the utilization of the CICIDS2017 Datasets, a comprehensive repository that facilitates both training and evaluation of our proposed DBN approach. To address the challenges posed by imbalanced Datasets, we employ various class balancing techniques, systematically evaluating their impact on detection performance. In the context of network attacks, our study pays special attention to notorious threats such as SQL injection, Cross-Site Scripting (XSS), Denial of Services (DoS), distributed Denial of Services (DDoS), and other malicious activities. These attacks, often veiled in the subtleties of network traffic, demand sophisticated detection mechanisms. The empirical evaluation involves a comparative analysis with a conventional Multi-Layer Perceptron (MLP) model and the prevailing state-of-the-art IDSs. Our proposed DBN approach demonstrates competitive and promising results, showcasing significant performance improvements in the detection of attacks that are underrepresented in the training Datasets. The findings underscore the efficacy of DBNs in tackling the intricate challenges posed by emerging and sophisticated cyber threats. This research not only contributes to the advancement of intrusion detection methodologies but also provide

关键词： Network intrusion

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Blockchain-Based Cryptocurrency Payment System Model for Business-To-Consumer E-Commerce Platforms 1

引用

international conference on. Cryptology and Network security with Machine Learning, ICCNSML 2023

作者： Pal, Prashnatita Sahana, Bikash Chandra Poray, Jayanta Bhattacharya, Rituparna Department of Electronics and Communication Engineering National Institute of Technology Patna India St. Thomas College of Engineering and Technology Kolkata Kolkata India Department of Computer Science and Engineering Techno India University Kolkata India

ISBN: (数字)9789819706419

ISBN: (纸本)9789819706402

Payment gateways are necessary for securing online transactions on e-commerce platforms, but there is still a problem with the restricted use of cryptocurrency as a payment method. Due to lengthy confirmation periods and fees, scalability concerns on blockchain networks like Bitcoin and Ethereum prevent the implementation of micropayments. With the help of a method of payment that makes use of the benefits of the Polygon distributed ledger network for quick and affordable transactions, we suggest a method of payment that gets beyond these restrictions in this article. The MetaMask electronic wallet securely manages user transaction data, enabling privacy and independence. The solution aims to encourage wider utilization of cryptocurrencies in online shopping by combining blockchain innovations with electronic wallets. The figures obtained demonstrate the advantages that retailers can have as a result. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blockchain

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Evolutionary Patterns in Modern-Era Cloud-Based Healthcare Technologies 1

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8th international conference on Information and Communication Technology for Competitive Strategies, ICTCS 2023

作者： Shrivastava, Vishal Pathak, Vibhakar Mishra, Saumya Buri, Ram Babu Sharma, Sangeeta Mishra, Chandrabhan Computer Science and Engineering Arya College of Engineering & I.T. Jaipur India

ISBN: (数字)9789819994892

ISBN: (纸本)9789819994885

distributed computing plays a pivotal role in revolutionizing the management of clinical data within the healthcare sector. This technology facilitates the global exchange of healthcare documents through electronic commerce, contributing significantly to promoting overall well-being and advancing the field of medicine. Thanks to this groundbreaking innovation, seamless communication with healthcare networks worldwide becomes a reality. In the realm of healthcare, distributed computing has existed for some time and has continued to evolve in tandem with business development. This invention introduces standardized specifications for a wide range of applications within the medical field, enabling open access to various devices. The security of data is ensured through distributed computing and efficient cloud server management, safeguarding critical information. Medical professionals can now offer guidance to their patients on maintaining their health, discussing routine medical care, and ensuring overall physical and mental well-being. Video conferencing has become an invaluable tool for doctors and therapists, fostering a sense of comfort and connection with their patients. This white paper delves into the objectives of employing distributed computing in medical services, emphasizing the awareness of its benefits, limitations, and challenges within the healthcare domain. Additionally, we explore vital recent trends and developments in health and medicinal concern. The concerned can readily acquire equipments that are IoT devised from vast list of manufacturers providing health-concern equipments. Consequently, the convergence of rapidly evolving technologies such as Big Data analytics, computational thinking, and the IoT of health concern, in conjunction with distributed computing, presents numerous means to enhance efficiency and streamline health-service. Thus, we enhance interoperability, expands resource sharing with cost reduction. © The Author(s), under exclusiv

关键词： Internet of things

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distributed Primal-Dual Interior Point Framework for Analyzing Infeasible Combined Transmission and Distribution Grid networks 58

Distributed Primal-Dual Interior Point Framework for Analyzi...

引用

58th Hawaii international conference on System Sciences, HICSS 2025

作者： Ali, Muhammad Hamza Pandey, Amritanshu University of Vermont United States

ISBN: (纸本)9780998133188

The proliferation of distributed energy resources has heightened the interactions between transmission and distribution (T&D) systems, necessitating novel analyses for the reliable operation and planning of interconnected T&D networks. A critical gap is an analysis approach that identifies and localizes the weak spots in the combined T&D networks, providing valuable information to system planners and operators. The research goal is to efficiently model and simulate infeasible (i.e. unsolvable in general settings) combined positive sequence transmission and three-phase distribution networks with a unified solution algorithm. We model the combined T&D network with the equivalent circuit formulation. To solve the overall T&D network, we build a Gauss-Jacobi-Newton (GJN) based distributed primal dual interior point optimization algorithm capable of isolating weak nodes. We validate the approach on large combined T&D networks with 70k+ T and 15k+ D nodes and demonstrate performance improvement over the alternating direction method of multipliers (ADMM) method. © 2025 IEEE computer Society. All rights reserved.

关键词： Grid computing

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A Novel Software Defined security Framework for SDN 18th

A Novel Software Defined Security Framework for SDN

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18th international conference on Risks and security of Internet and systems (CRiSIS)

作者： Basu, Srijita Raun, Neha Firdaush Ghosal, Avishek Chatterjee, Debanjan Maitra, Debarghya Mazumdar, Chandan Jadavpur Univ Ctr Distributed Comp Kolkata India Jadavpur Univ Kolkata India

ISBN: (纸本)9783031612305;9783031612312

Software Defined security (SDS) entails the security implementation of a network, based on certain applications. It can be portrayed as a virtualized abstraction of the essential security features into a single software layer. SDS can be designed for traditional physical, virtualized, NFVs (Network Function Virtualization) and SDN (Software Defined Networking) based networks. This paper aims at developing an SDS framework for ONOS based SDN systems. Though most of the existing controllers like RYU, Floodlight, POX and ODL provide a framework for designing SDN applications and REST APIs, ONOS (Open Network Operating System) is comparatively more flexible. The novelty in considering the "SDS on SDN" design lies in the uniformity and scalability of the system. Moreover, a data plane device can now act in a polymorphic manner. The required security rules are provided into the SDS framework that in turn modifies the corresponding flow rules and the control plane forwards the same to the dataplane devices. Thus, a data plane device can have the functionalities of a firewall, IDS, IPS, AAA, etc. depending upon the triggered flow rule. Dependency on a particular security appliance orVNFand the necessity of maintaining multiple instances of the same is eliminated in the proposed system. The experimental setup comprises of a hybrid network topology of virtual mininet switches and HP Aruba switches. The performance analysis of the system in terms of throughput, bandwidth, and RTT latency shows a considerably low overhead thereby proving the effectiveness of the scheme.

关键词： Application Controller Firewall security

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Virtual Private Network Blockchain-based Dynamic Access Control Solution for Inter-organisational Large Scale IoT networks 1

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17th international conference on Risks and security of Internet and systems (CRiSIS)

作者： Trabelsi, Rahma Fersi, Ghofrane Jmaiel, Mohamed Univ Sfax Natl Sch Engineers Sfax ReDCAD Lab BP 1173 Sfax 3038 Tunisia Digital Res Ctr Sfax BP 275 Sfax 3021 Tunisia

ISBN: (数字)9783031311086

ISBN: (纸本)9783031311079;9783031311086

Access control management in IoT environment faces big challenges. Unfortunately, it is hard to implement current access control standards on smart objects due to the complexity of access control solutions and the limited capacities of IoT devices. The problem becomes harder when these IoT devices belong to different organisations and need to interact together frequently. In the last few years, blockchain technology has been widely used in inter-organisational access control solutions for IoT. In fact, this technology can ensure an efficient and distributed access control. However, the existing solutions require lot of time and resources. In this paper, we provide a solution for a secure access control management in inter-organisational IoT networks based on blockchain and Virtual Private Network (VPN) technology. To optimize the resources and the time needed for access control, the IoT devices that belong to different organisations and cooperate frequently are added to the same VPN. The access control is ensured per VPN using blockchain. The experimental results of our proposed approach have shown the efficiency of our proposed approach in offering a secure, real-time response, decentralized, scalable and lightweight access control solution.

关键词： IoT security Access control Blockchain Virtual Private Network

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Harnessing Machine Learning for Enhanced distributed Computing in Wireless Network systems

Harnessing Machine Learning for Enhanced Distributed Computi...

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2024 international conference on Communication, computer Sciences and Engineering, IC3SE 2024

作者： Rashmi, K. Anandhi, R.J. Singh, Navdeep Kumar, V. Surya Pavan Gupta, Krashnkant Albawi, Ali Institute Of Aeronautical Engineering Department Of Computer Science And Engineering Telangana Hyderabad India New Horizon College Of Engineering Department Of Information Science Engineering Bangalore India Lovely Professional University Phagwara India Mlr Institute Of Technology Department Of CSE-AI&ML Telangana Hyderabad India Amity University Greater Noida Department Of Electronics & Communication Engineering India College Of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq

ISBN: (纸本)9798350366846

A complete wireless network system for flexible resource sharing, spectrum management, security, and cross-layer optimization is described in this paper. Five algorithms comprise the system. These are ADS, QoS-ML, CLO, and DSM. Wireless networks adapt and grow, and these applications solve issues. Real-time resource allocation using predictive models enhances network performance, latency, and efficiency with the PRA algorithm. DSM uses adaptive spectrum utilization to reduce interference. ADS uses machine learning to detect unusual activity and implement flexible safety measures to make networks safer. QoS-ML improves routing options using real-time QoS data to ensure network-wide QoS. CLO alters layer connections, utilizes metrics across layers, and is continually searching for network improvements. A detailed analysis of the research examined each program's distinct qualities and how they function together. The discussion focused on how well the framework performed in various settings and was adaptable. In the conclusion, the algorithms' strengths and potential in distributed computing environments were highlighted. The recommended technique outperformed others in speed, latency, security, energy efficiency, scalability, and customer satisfaction. Performance trends, parameter distributions, and trade-offs were shown, making the structure more dependable. By offering a full, adaptive, and successful method, this study advances wireless network management. Optimizations, scalability, and real-world applications might be studied to ensure the system works in various conditions. In challenging and changing situations, the proposed architecture supports wireless network expansion. © 2024 IEEE.

关键词： Machine learning

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