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Impacts of High Denisty Cloud Computing on Data Protection and security Management for 6G Networking 2

Impacts of High Denisty Cloud Computing on Data Protection a...

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2nd international conference on Disruptive Technologies, ICDT 2024

作者： Mallikarjunaradhya, Vinay Yennapusa, Haritha Palle, Ranadeep Reddy Suganyadevi, K. Gupta, Nidhi Legal Tech Platform Thomson Reuters Toronto Canada University of Central Missouri Department of Computer Science AustinTX United States University of Houston Department of Computer Science AustinTX United States Sri Eshwar College of Engineering Department of Ece Tamil Nadu Coimbatore India G.L. Bajaj Institute of Technology and Management Department of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350371055

Data protection and security management in the 6G era is a key challenge due to the emergence of high density cloud computing. The availability of high density cloud computing technologies creates a platform for massive data storage, processing, and analytics capabilities at a scale that has never been seen before. High density cloud computing facilitates the deployment of complex distributed systems consisting of hundreds or thousands of nodes in a single deployment. This can have a significant impact on data protection and security management as it increases the potential threat to the system from malicious actors. To protect data in this environment, organizations must adopt more advanced security practices such as access control, encryption, and defensive layers to protect against malicious actors. The use of encryption can provide a layer of security by making it difficult for outsiders to access information without authorization. Access control can also prevent unauthorized users from accessing certain parts of the system, while defensive layers can help detect and block malicious attacks. The results of this study showed that high density cloud computing can potentially improve the efficiency and performance of data protection and security management in 6G networks. © 2024 IEEE.

关键词： 6G Networking Cloud Data Storage Data Protection Network Reliability Network security security Management

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IoV Cyber Defense: Advancing DDoS Attack Detection with Gini Index in Tree Models 4

IoV Cyber Defense: Advancing DDoS Attack Detection with Gini...

引用

4th international conference on Emerging Trends in networks and computer Communications, ETNCC 2024

作者： Dilshad, Muhammad Almas, Bushra Tariq, Noshina Jazri, Husin Bin Alwakid, Ghadah Naif Khan, Jan Sher Kumar, Pranav Kumar, Rahul Institute of Information Technology QuaidiAzam University Islamabad Pakistan Air University Department of Avionic Engineering Islamabad Pakistan School of Computer Science Taylor's University Subang Jaya Malaysia Jouf University Department of Computer Sciences Sakaka Saudi Arabia Lovely Professional University Division of Research and Development Phagwara144411 India KKR and KSR institute of technology and sciences Andhra Pradesh Guntur India

ISBN: (纸本)9798350353266

In today's ever-changing world of cybersecurity, where smart devices and the Internet of Vehicles (IoV) are everywhere, it is crucial to have a strong defense against attacks. This paper introduces an intelligent way to detect the distributed Denial of Service (DDoS) attacks, a severe threat that can disrupt access to essential resources. Traditional methods to handle such attacks include intrusion detection systems (IDS). However, we need new and creative solutions to increasingly complex data. Our proposed strategy is an Artificial Intelligence (AI)-based technique that uses a Decision Tree (Dt) algorithm with feature selection using the Gini index. The proposed DDoS detection system has depicted an impressive accuracy of 99.4% while tested with the CIC-DDoS2019 dataset, surpassing baseline and previous benchmarks like Random Forest and XGBoost. Our improved Gini index method smartly selects 39 essential security features from a pool of 88, cutting down on unnecessary data and preventing over-fitting. This approach efficiently demonstrates its practical use in real-world network security situations, especially IoVs. © 2024 IEEE.

关键词： Network intrusion

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Comparing the Supersonic Cloud Computing Model to Enhance the Networking and security in Traditional Data Centers 2

Comparing the Supersonic Cloud Computing Model to Enhance th...

引用

2nd international conference on Disruptive Technologies, ICDT 2024

作者： Palle, Ranadeep Reddy Mallikarjunaradhya, Vinay Yennapusa, Haritha Suganyadevi, K. Gupta, Nidhi University of Houston Department of Computer Science AustinTX United States Thomson Reuters Legal Tech Platform Toronto Canada University of Central Missouri Department of Computer Science AustinTX United States Sri Eshwar College of Engineering Department of Ece Tamil Nadu Coimbatore India G.L. Bajaj Institute of Technology and Management Department of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350371055

The Comparing the supersonic cloud computing model to enhance the networking and security in Traditional Data Centers study aimed to analyse the differences between traditional data centers and cloud computing models. The researchers' findings demonstrate that the supersonic cloud model consists of a number of services and functions that can improve network and security performance across all levels of the data center. Furthermore, the supersonic model offers more options for load balancing through routing protocols and more secure network access. In addition, the supersonic model allows for more flexibility in the resources used, such as virtual servers and storage systems. Lastly, the supersonic model allows for greater scalability through the use of distributed simultaneous networks. These benefits pave the way to the eventual goal of improving existing data center operation and security. The objective of this study was to assess the potential of supersonic cloud computing model (SCC) to improve the networking and security in traditional data centers. The findings indicated that SCC improved the network efficiency by 10.4%, reduced network latency by 11 %, and improved packet delivery rates by 8.6%. The security was also improved, with overall firewall rules increased by 12 %, and 5% fewer security violations. Overall, SCC showed promising performance in improving the networking and security of traditional data centers. © 2024 IEEE.

关键词： Data Centers Infrastructure Scalability Service Level Agreements Supersonic

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Improving Prediction Accuracy in IoT Network security Against DDoS Attacks by Combining RIPPER and KNN Algorithms 8

Improving Prediction Accuracy in IoT Network Security Agains...

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8th international conference on Electrical, Telecommunication and computer Engineering, ELTICOM 2024

作者： Juliansyah, Handrino Sihombing, Poltak Fahmi, Fahmi Universitas Sumatera Utara Faculty of Computer Science and Information Technology North Sumatera Medan Indonesia Universitas Sumatera Utara Faculty of Engineering Electrical Engineering Dept North Sumatera Medan Indonesia

ISBN: (纸本)9798331531249

The Internet of Things (IoT) is a network of linked devices comprising interconnected devices that communicate through internet, integrating sensors, software and other technologies. As the number of connected devices grows, ensuring IoT security has become increasingly critical, with cyber threats and other related risks arising. A prevalent threat is the distributed Denial of Service (DDoS) attack, which seeks to incapacitate server systems by overwhelming the network with excessive traffic. This study explores machine learning approach to improve intrusion detection systems (IDS) performance, such as accuracy in identifying and mitigating DDoS attacks. Specifically, it employs a hybrid approach combining the well-known RIPPER algorithm or Repeated Incremental Pruning to Produce Error Reduction and the K-Nearest Neighbors (KNN) algorithm as detection models. The study utilizes the Network security Layer-Knowledge Discovery in Database (NSL-KDD) dataset, which contains 41 features for classifying DDoS attacks. To optimize the model's performance, the data underwent preprocessing to eliminate irrelevant and redundant features while retaining essential information. The classification results demonstrate a peak accuracy of 97.32% with k=6 and an average accuracy of 96.30% across 15 trials with varying k values from 1 to 15. These findings highlight the effectiveness of the RIPPER-KNN approach in improving the prediction accuracy of DDoS attack detection in IoT networks. © 2024 IEEE.

关键词： Denial-of-service attack

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12th and 13th international conference on Cloud Computing and Services Science, CLOSER 2022 and CLOSER 2023

12th and 13th International Conference on Cloud Computing an...

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12th and 13th international conference on Cloud Computing and Services Science, CLOSER 2022 and CLOSER 2023

ISBN: (纸本)9783031681646

The proceedings contain 10 papers. The special focus in this conference is on Cloud Computing and Services Science. The topics include: Evaluating Microservices Communication Relationships for Scheduling Containers on Kubernetes Clusters;security Evaluation in Software-Defined networks;a distributed Tool for Monitoring and Benchmarking a National Federated Cloud;metamodel and Formalization to Model, Transform, Deploy, and Execute Quantum Workflows;Edge AI Deployment and Stream-Based Time Series Classification Within ARTHUR;misconfiguration of Cluster and IoT systems Recovery: Extended Experiments;orchestrating Microservices-Based Applications in the Cloud-to-Edge Continuum;fog-Robotics Infrastructures Simulation-Based Sizing Approach.

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Cryptographic Ledger for Cyber security in Smart Grid 2

Cryptographic Ledger for Cyber Security in Smart Grid

引用

2nd international conference on Edge Computing and Applications, ICECAA 2023

作者： Elanchezhiyan, E. Kalaiselvi, K. Banumathy, D. Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Networking and Communications Tamilnadu Kattankulathur603203 India Paavai Engineering College Department of Computer Science and Engineering Tamilnadu Namakkal637018 India

ISBN: (纸本)9798350347579

In addition to the physical security of energy networks, cyber security is essential to protecting these systems as well. Cyber threats can stem from malicious hackers who have infiltrated the networks to gain unauthorized access to sensitive data, or from vulnerabilities within the systems themselves. It is increasingly important that smart grid companies invest in cyber security solutions, such as strong passwords, two-factor authentication, encryption, and regular software updates, to counteract these threats. Additionally, it is beneficial for organizations to create incident response plans that are tailored to their specific needs, and which define the chain of command and actions to take in the case of an incident. To details the usage of smart grids in various domains and places in an effective way and explains the efficient way of consuming power for smart ventilators by monitoring and providing cyber security against cyber-attacks. The distributed power from various regions is collected from the less predominant places and supplied to the smart ventilators through smart inverters. © 2023 IEEE.

关键词： Cybersecurity

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Blockchain-Based Virtual Skin System for Metaverse: Design and Implementation 15

Blockchain-Based Virtual Skin System for Metaverse: Design a...

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15th international conference on Cyber-Enabled distributed Computing and Knowledge Discovery, CyberC 2023

作者： Meng, Debin Li, Jinbo Wang, Mingyu Wang, Guanghui Henan University School of Software Kaifeng China Henan International Joint Laboratory of Intelligent Network Theory and Key Technology Kaifeng China

ISBN: (纸本)9798350308693

The virtual skin system is an enabling component for the applications and services in the Metaverse. Traditional virtual skin systems are usually designed with a unified style, which can still be improved to meet customized demands. By extending the scope of existing virtual skin systems, we propose a Blockchain-based Virtual Skin (BVS) system for effective virtual skin management to enhance customization, security, and trust for Metaverse applications and services. In particular, functional modules are designed for the BVS system, including the virtual skin creation, registration, storage, and transaction processes. The blockchain networks and smart contracts are also presented. Furthermore, the proposed BVS system is implemented using the Hyperledger Fabric platform. The performance of the BVS system is evaluated by conducting experiments. It is illustrative that the BVS system has advantages of high security, efficiency, and low cost compared with traditional virtual skin systems. © 2023 IEEE.

关键词： Smart contract

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Octopus: Experiences with a Hybrid Event-Driven Architecture for distributed Scientific Computing

Octopus: Experiences with a Hybrid Event-Driven Architecture...

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2024 Workshops of the international conference for High Performance Computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Pan, Haochen Chard, Ryan Zhou, Sicheng Kamatar, Alok Vescovi, Rafael Hayot-Sasson, Valerie Bauer, Andre Gonthier, Maxime Chard, Kyle Foster, Ian Southern University of Science and Technology Department of Computer Science China Illinois Institute of Technology Department of Computer Science ChicagoIL United States University of Chicago Department of Computer Science ChicagoIL United States Argonne National Laboratory Data Science and Learning Division LemontIL United States

ISBN: (纸本)9798350355543

Scientific research increasingly relies on distributed computational resources, storage systems, networks, and instruments, ranging from HPC and cloud systems to edge devices. Event-driven architecture (EDA) benefits applications targeting distributed research infrastructures by enabling the organization, communication, processing, reliability, and security of events generated from many sources. To support the development of scientific EDA, we introduce Octopus, a hybrid, cloud-to-edge event fabric designed to link many local event producers and consumers with cloud-hosted brokers, and to provide a fabric for developing resilient applications. Octopus can be scaled to meet demand, permits the deployment of highly available Triggers for automatic event processing, and enforces fine-grained access control. We identify requirements in self-driving laboratories, scientific data automation, online task scheduling, epidemic modeling, and dynamic workflow management use cases, and present results demonstrating Octopus' ability to meet those requirements. Octopus supports producing and consuming events at a rate of over 4.2 M and 9.6 M events per second, respectively, from distributed clients. © 2024 IEEE.

关键词： Event-driven architecture research automation scientific computing

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Feature Selection Using COA with Modified Feedforward Neural Network for Prediction of Attacks in Cyber-security 2

Feature Selection Using COA with Modified Feedforward Neural...

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2nd international conference on distributed Computing and Optimization Techniques, ICDCOT 2024

作者： Vallabhaneni, Rohith Nagamani, H.S. Harshitha, P. Sumanth, S. University of the Cumberlands United States Govt. Smt Vhd Central Institute of Home Science Department of Computer Science Bengaluru India Nitte Meenakshi Institute of Technology Department of Aiml Bengaluru India Government College for Women Department of Computer Science and Applictaions Kolar India

ISBN: (纸本)9798350382952

Research on network intrusion detection, prediction, and mitigation systems has been ongoing due to the exponential rise in cyber-attacks in recent times. The prediction of future network invasions is still an open research subject, despite the abundance of intrusion detection systems. Current solutions need feature selection and engineering since they use statistical and/or shallow machine learning techniques to do the job. This study begins with pre-processing the BotNet dataset with feature encoding and scaling. The next step is to use the Coot Optimisation Algorithm (COA) to pick the most significant characteristics. The next step is for the FeedForward Neural Network (FFNN) model to do the classification. ETLBO is used to determine the model's weight appropriately. Using the adaptive weight approach with the Kent chaotic map improves the ideal performance of the standard TLBO. The projected technique aims to circumvent the primary problems with the original TLBO by not using the local optimum and by maintaining an equilibrium between the search methods. When compared to current methods, the experimental analysis reveals that the suggested model attained a precision of 96.76% and an accuracy of 97.56%. © 2024 IEEE.

关键词： Feedforward neural networks

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Blockchain-Based Central Bank Digital Currencies: A Comprehensive Survey 13th

Blockchain-Based Central Bank Digital Currencies: A Comprehe...

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13th international conference on computer Engineering and networks (CENet)

作者： Chen, Shuo Liu, Zhiwei Xu, Xiang Gao, Haoyu Hong Lei Liu, Chao Hainan Univ Sch Cyberspace Secur Haikou 570228 Hainan Peoples R China Oxford Hainan Blockchain Res Inst Chengmai 571924 Peoples R China Blockhouse Technol Ltd Oxford OX2 6XJ England SSC Holding Co Ltd Chengmai 571924 Peoples R China

ISBN: (纸本)9789819992492;9789819992478;9789819992461

In this information age, real currency is transitioning to digital currency. Blockchain technology has introduced smart contracts and distributed ledger technology, leading to new research directions in various fields including finance, the Internet of Things, and energy. Central Bank Digital Currency (CBDC) based on blockchain has been incorporated into the technical choices of central banks in various countries. This paper examines the current research and implementation of central bank digital currency by various central banks worldwide. It provides an overview of CBDC's definition, operational status, and technical characteristics. Additionally, this paper highlights the challenges and issues associated with CBDC systems in the current environment. These problems include security issues, performance issues, privacy protection issues, and legal issues. In this regard, some literature has proposed solutions, which are analyzed and summarized in this paper. We classify and summarize the existing problems and propose effective solutions, including using fragmentation technology to increase transaction throughput and implementing corresponding regulatory measures to strengthen supervision.

关键词： Central bank digital currency Blockchain Smart contract distributed ledge technology

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