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Enhanced DDoS Defense in SDN: Double-Layered Strategy with Blockchain Integration 13

Enhanced DDoS Defense in SDN: Double-Layered Strategy with B...

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13th IEEE international conference on Communications, Circuits and Systems (ICCCAS)

作者： Tian, Jialin Shu, Zhaogang Chen, Shuwu Xie, Haihui Liu, Xiaolong Qiu, Caiyu Fujian Agr & Forestry Univ Comp & Informat Coll Fuzhou Peoples R China

ISBN: (纸本)9798350386288;9798350386271

With the development of technologies such as cloud computing, big data, and the internet of things (IoT), Software-Defined Networking (SDN) has emerged as a novel network architecture in today's internet era. It can separate the control plane from the data plane, allowing rapid packet forwarding in the internet through a centralized controller. However, SDN environments are vulnerable to traditional distributed Denial of Service (DDoS) attacks. this paper proposes a new dual layer strategy to try to mitigate the question. First, by using blockchain technology and smart contract in the northbound interface to store the flow tables required for SDN networks, security is increased. then, we use the Token Bucket algorithm and Time Window algorithm to build the first-tier strategy to defend against obvious DDoS attacks. To detect unobvious DDoS attacks, we design the second-tier strategy that uses a composite data feature correlation coefficient calculation method and the Isolation Forest algorithm to perform binary classification on data, thereby identifying abnormal traffic. We use the currently publicly available DDoS dataset CIC-DDoS2019 for experimental verification. the results show that using this strategy in SDN networks results in an average deviation of data Round-Rip Time (RTT) approximately 38.86% lower than in the original SDN networks without this strategy. Additionally, the accuracy of DDoS attack identification reaches 91.29%. this means that with the implementation of this strategy, DDoS attacks can be effectively identified without compromising the stability of data transmission in SDN network environments.

关键词： Software Defined Networks distributed Denial of Service Blockchain Machine learning

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Intelligent DWC Reservation and Trip Planning of CAEV and UAV for 6G ITS 20

Intelligent DWC Reservation and Trip Planning of CAEV and UA...

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20th IEEE international Wireless Communications and Mobile computing (IEEE IWCMC) - Green and Intelligent Communications

作者： Shaikh, Palwasha Waheed Mouftah, Hussein T. Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON Canada

ISBN: (纸本)9798350361261;9798350361278

In the 6G era, addressing charging challenges for electric vehicles is paramount. this paper focuses on mitigating concerns for both Connected Autonomous Electric Vehicles (CAEVs) and Unmanned Aerial Vehicles (UAVs). CAEV users face range anxiety, while UAV operators contend with limited battery sizes. the paper introduces a dynamic wireless charging (DWC) reservation and trip planning system, powered by 6G, vital for future smart cities. It provides a literature review on CAEV and UAV charge scheduling, proposing a novel system design tailored for 6G-enabled Intelligent Transportation Systems (ITS), where UAVs serve CAEVs. Notably, for vehicle-to-vehicle DWC and communication, laser technology is utilized, ensuring reliability and efficiency. A dynamic arrival handling protocol addresses unpredictable vehicle arrivals. Simulation results showcase the system's efficiency, optimizing charging and reducing wait times. With the impending 6G era, the paper aims to advance charging infrastructure for intelligent, flexible, and harmonized electric vehicle charging operations.

关键词： Connected Autonomous Electric Vehicle Unmanned Aerial Vehicle CAEV and UAV Charging Dynamic Wireless Charging Intelligent Transportation System internet of things 6G

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Privacy computing technology in the context of energy internet 5

Privacy computing technology in the context of energy Intern...

引用

5th international conference on Communications, Information System and Computer Engineering, CISCE 2023

作者： Gong, Yue Chen, Cuiyun Liu, Zhiyu The First Research Institute of the Ministry of Public Security of P.R.C Beijing China

ISBN: (纸本)9798350326796

the power system and other energy systems are constantly cross-integrated, and a new development direction of multi-subject collaboration is gradually formed. Starting from the typical mode of energy internet collaborative optimization, this paper puts forward a preliminary technical scheme for energy internet collaborative optimization considering privacy protection. Aiming at the scenario without a third party, this paper proposes a secure multi-party interactive computing scheme based on the principle of secret sharing, and analyzes the specific characteristics of the scheme when applied to a small number of subject scenarios based on the fully distributed application architecture. Finally, from the aspects of data privacy and computing security, the proposed scheme protects the rights and interests of data owners, reduces the risk of data leakage in energy internet collaborative optimization computing, and realizes reliable privacy protection. © 2023 IEEE.

关键词： Data privacy

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Application Research of Vertical Federated Learning technology in Banking Risk Control Model Strategy 21

Application Research of Vertical Federated Learning Technolo...

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21st IEEE international Symposium on Parallel and distributed Processing with Applications, 13th IEEE international conference on Big Data and Cloud computing, 16th IEEE international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Luo, Yong Lu, Zhi Yin, Xiaofei Lu, Songfeng Weng, Yiting Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan China China Minsheng Banking Corp. Ltd. Beijing China Shenzhen Huazhong University of Science and Technology Research Institute Wuhan China Shu Lun Pan Beijing China

ISBN: (纸本)9798350329223

this study centers on the application of vertical federated learning technology in the context of internet banking loans, with a particular focus on innovations in data privacy protection, risk control model algorithms, and secure multi-party computation. Currently, banking risk control strategies mainly rely on traditional data processing technologies, which often fall short in protecting user privacy and ensuring data usage efficiency. We adopt vertical federated learning technology, offering an innovative solution for the internet banking loan scenario. Firstly, regarding data privacy protection, we propose a differential privacy mechanism to safeguard user-sensitive data. Secondly, we innovatively apply risk control model algorithms, facilitating collaborative modeling across multiple internet loan platforms through federated learning. Furthermore, we introduce secure multi-party computation technology to ensure the secure transmission of data and confidentiality of computation processes during federated learning. through empirical experiments on real internet loan datasets, we validate the effectiveness and feasibility of our proposed methods. After implementing our risk control model, the credit approval rate increased from 3.44% to 18.2%, with a single-day high reaching 25.53%. the average loan amount increased by 7,700 yuan, and the average interest rate slightly declined by 0.48%, marking a significant improvement and breakthrough compared to traditional risk control models. this study offers innovative solutions for data privacy protection and risk control in the internet loan scenario, providing safer and more reliable services for financial institutions and users. Moreover, our methods possess high practicality and promotional value. the potential widespread impact on the industry is profound. © 2023 IEEE.

关键词： Risk management

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Intrusion Detection at the Edge computing: A Deep Learning Approach Using the UNSW-NB15 Dataset 14

Intrusion Detection at the Edge Computing: A Deep Learning A...

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14th IEEE international conference on Communication Systems and Network Technologies, CSNT 2025

作者： Kumar, Vipin Kumar, Vivek Bhadauria, Abhay Pratap Singh Dixit, Jay Kumar, Amit Haridwar India Department of Computer Engineering & Applications GLA University UP Mathura India

ISBN: (纸本)9798331531935

Edge computing has transformed technology by enabling seamless connections between IoT devices, but it also introduces significant security challenges. EC is crucial for providing minimal latency processing and reducing the load on centralized servers, ensuring timely and scalable intrusion detection for IoT environments. the findings underscore the potential of combining edge computing, IoT, and deep learning to address evolving security challenges in distributed systems. To mitigate these risks, efficient models for detecting malicious activities are crucial. this study investigates the application of edge computing, internet of things (IoT), and deep learning to improve the performance of Intrusion Detection Systems (IDS). By leveraging the UNSW-NB15 dataset, the research assesses the capability of deep learning models to identify and mitigate cyber threats effectively. the results demonstrate better performance, showing their suitability for real-time security applications. these findings highlight the potential of intelligent intrusion detection systems powered by robust datasets and deep learning for addressing evolving security threats in edge computing environments. © 2025 IEEE.

关键词： Edge computing

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Prototype of Iot-Based Keyless Security System For Motorcycle 6

Prototype of Iot-Based Keyless Security System For Motorcycl...

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6th international conference on Information and Communications technology, ICOIACT 2023

作者： Saputra, Adika Akbar Suryani, Vera Rakhmatsyah, Andrian Telkom University School of Computing Bandung Indonesia

ISBN: (纸本)9798350315639

Today the motorcycle theft cases in Indonesia are in a very high rate and it has been continuing to increase in every year. For this, there is a need for a security system for motorcycle to minimize the risk of motorcycle theft. this study aims to design and create an internet of things (IoT)-based security system for the motorcycle that can be controlled through smartphone purposely to reduce the rate of motorcycle thefts. the system was created using Arduino microcontroller. From the results of the implementation, it produced a device that has a number of features including turning on, turning off, and motorcycle starter using application. Another one is the function of tracking to trace the position of the motorcycle. the third feature is to turn off the function of motorcycle socket and the fourth feature is to control the switch engine of motorcycle. the results of the testing in the parameters of maximum distance of Bluetooth connection, delay proses, test of GPS connectivity and test of voice command, showed that it could create a system that can be used well as an anti-theft device for motorcycle. © 2023 IEEE.

关键词： Smartphones

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Ant Colony Optimization Based Multi-Hop Wireless Transmission for Enhanced Network Reliability 6

Ant Colony Optimization Based Multi-Hop Wireless Transmissio...

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6th IEEE international conference on Artificial Intelligence in Engineering and technology, IICAIET 2024

作者： Lim, Kit Guan Bin Sakimin, Mohd Fikry Fazri Wei, Longxin Tan, Min Keng Yang, Soo Siang Teo, Kenneth Tze Kin Universiti Malaysia Sabah Modelling Simulation & Computing Laboratory Faculty of Engineering Kota Kinabalu Malaysia Fujian Polytechnic of Information Technology Faculty of The Internet of Things and Artificial Intelligence Fuzhou China

ISBN: (纸本)9798350389692

Wireless multi-hop transmission is a new technology that has been used for data transfer in no internet connectivity and electricity area. Wireless sensor networks are being created for many different purposes, both for everyday civilian uses and military applications. Multi-hop transmissions are popular with challenges like shape of terrain, low data transfer rate and loss connectivity easily when it comes to design. the main problem is current control for routing in multi-hop wireless sensor networks works as what it has been initialized and the nodes only communicate with preset nodes. Malfunction of a single transceiver can cause connection losses and decrease network reliability. this report will explore the optimization of multi-hop wireless communication by implementing ACO in omnidirectional transceiver. the aim is to develop wireless sensor network model, compute control strategy for routing in random topology, to optimize wireless transmission by implementing artificial intelligence and analyze the performance of proposed algorithm. To achieved these goals, a simulation has been designed in MATLAB to represent the real situation virtually. Several parameters such as number of nodes, area size and transmission range must be considered in the simulation to get optimum result. Conventional routing protocol such as Distance-Vector is used as a comparison to ACO control strategy with the help of Euclidean distance formula. this project focus on optimizing routing strategy from source node to target node without considering pathloss and line of sight. then, the results are performance comparison of Distance-Vector, Randomized Multi-Path and Ant Colony Optimization in 100 iterations. After simulation, Ant Colony Optimization does improve Distance-Vector by increasing network lifetime with 1st 'dead node' appear at 100th iteration but still maintaining as least average hops path as possible. the number of hops and 'dead node' for a single complete transmission fro

关键词： MATLAB

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Blockchain-based Intrusion Detection Scheme for Cloud-computing 6

Blockchain-based Intrusion Detection Scheme for Cloud-comput...

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2021 6th international conference on Information Science, Computer technology and Transportation, ISCTT 2021

作者： Guo, Wei Xie, Linjiang Hang, Feilu Lv, Yao Luo, Zhenyu Information Center Yunnan Power Grid Co. Ltd. Kunming China

ISBN: (纸本)9783800757282

With the rapid development of cloud computing technology, more and more businesses are based on cloud services. In this context, people should pay more attention to the security issues of cloud computing platform. Because cloud computing has a higher degree of network virtualization, more flexibility and higher scalability, the traditional intrusion detection technology cannot effectively meet the needs of security protection. For the characteristics of cloud computing environment, this paper proposes a blockchain-based collaborative distributed intrusion detection scheme to solve the trust defects of existing distributed systems. Finally achieve the purpose of realizing effective, avoiding single point fault, quality assurance, scalable intrusion detection scheme. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Cloud computing

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A Kubernetes-Powered Personalized Federated Learning Platform for Resource-Constrained internet of Medical things

A Kubernetes-Powered Personalized Federated Learning Platfor...

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20th IEEE international Wireless Communications and Mobile computing (IEEE IWCMC) - Green and Intelligent Communications

作者： Lin, Meng-Hsuan Yang, Shun-Ren Chiang, Hsin-Yin Chang, Chu-Chun Lin, Phone Natl Tsing Hua Univ Dept Comp Sci Inst Info Sys & App Hsinchu Taiwan Natl Tsing Hua Univ Inst Commun Engn Hsinchu Taiwan Cephalgo SAS 8 Rue Veaux F-67000 Strasbourg France Natl Taiwan Univ Dept Comp Sci & Info Engn Grad Inst Biomed Elec & Bioinform Grad Inst Net & MMInst Med Device & Imaging Taipei Taiwan Natl Taiwan Univ IoT Res Ctr Taipei Taiwan

ISBN: (纸本)9798350361261;9798350361278

Federated Learning (FL) is a distributed machine learning scheme that trains a global model across multiple end devices while protecting user privacy by keeping data locally, which has been shown to be useful for smart healthcare. By integrating virtualized container technology into edge platforms, flexible computing resources can be made available to internet of Medical things (IoMT) devices, enabling their participation in FL. Some studies have utilized the advantages of Kubernetes (K8s) for fast container deployment, offering general FL platforms for developers to rapidly deploy models. However, there are currently no FL development platforms suitable for smart healthcare, which exhibits unique challenges of personalized medical data and large-sized models for resource-limited IoMT devices. In this paper, we propose a Kubernetes-powered personalized FL (PFL) platform for resource-constrained IoMT. this platform, which incorporates personalized strategies to capture individual features and model compression mechanisms to reduce model size, allows model developers to formulate PFL training tasks for healthcare users to acquire personalized and compressed models, deployable on their devices. Via establishing a real testbed and deploying a demonstrating training task, our experiments verify the platform's ability to support the development of personalized and compressed models.

关键词： internet of Medical things (IoMT) Kubernetes model compression Personalized Federated Learning (PFL) service platform

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HessianAuth: An ECC-based distributed and Efficient Authentication Mechanism for 6LoWPAN Networked IoT Devices 23

HessianAuth: An ECC-based Distributed and Efficient Authenti...

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24th international conference on distributed computing and Networking (ICDCN)

作者： Dey, Debasmita Chandra, Saket Ghosh, Nirnay Indian Inst Engn Sci & Technol Dept Comp Sci & Technol Sibpur India Singapore Univ Technol & Design Singapore 487372 Singapore

ISBN: (纸本)9781450397964

internet of things (IoT) constitutes an ecosystem of networked resource-constrained devices that mandates light-weighted security solutions. In most IoT applications, co-located and proximal devices are connected in 6LoWPAN networks and use the IEEE 802.15 standard for local interactions via device-to-device (D2D) communication. the resource-limited 6LoWPAN networked devices need an efficient authentication mechanism to validate requesters' identities such that less resources and time are required. In this paper, we propose a novel Elliptic Curve Cryptography (ECC)-based distributed authentication scheme called HessianAuth to achieve efficiencies in resource usage and latency as well as security. We simulated a 6LoWPAN network to support a D2D communication scenario and implemented the proposed authentication mechanism using the Cooja network simulator. We have considered AES-CBC and standard Weierstrass curve-based ECC as the benchmarks and carried out performance analysis with respect to CPU cycles and delay. Further, we carry out a security analysis of HessianAuth using a state-of-the-art tool called AVISPA and demonstrate that the former is secure against man-in-the-middle and replay attacks.

关键词： internet of things Elliptic curve cryptography Hessian curves AES-CBC Authentication Digital signature D2D communication

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