scholarly journals A Distributed Security SDN Cluster Architecture for Smart Grid Based on Blockchain Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Ao Xiong ◽  
Hongkang Tian ◽  
Wenchen He ◽  
Jie Zhang ◽  
Huiping Meng ◽  
...  
Keyword(s):  
Smart Grid ◽  
Single Point ◽  
Cluster Structure ◽  
Cluster Head ◽  
Detection Algorithm ◽  
Attack Detection ◽  
Security And Privacy ◽  
Network Attack ◽  
Blockchain Technology ◽  
Distributed Security

This paper proposes a smart grid distributed security architecture based on blockchain technology and SDN cluster structure, referred to as ClusterBlock model, which combines the advantages of two emerging technologies, blockchain and SDN. The blockchain technology allows for distributed peer-to-peer networks, where the network can ensure the trusted interaction of untrusted nodes in the network. At the same time, this article adopts the design of an SDN controller distributed cluster to avoid single point of failure and balance the load between equipment and the controller. A cluster head was selected in each SDN cluster, and it was used as a blockchain node to construct an SDN cluster head blockchain. By combining blockchain technology, the security and privacy of the SDN communication network can be enhanced. At the same time, this paper designs a distributed control strategy and network attack detection algorithm based on blockchain consensus and introduces the Jaccard similarity coefficient to detect the network attacks. Finally, this paper evaluates the ClusterBlock model and the existing model based on the OpenFlow protocol through simulation experiments and compares the security performance. The evaluation results show that the ClusterBlock model has more stable bandwidth and stronger security performance in the face of DDoS attacks of the same scale.

scholarly journals Survey on Blockchain for Smart Grid Management, Control, and Operation

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 193
Author(s):  
Yohannes T. Aklilu ◽  
Jianguo Ding
Keyword(s):  
Smart Grid ◽  
Energy Demand ◽  
High Energy ◽  
Management Control ◽  
Security And Privacy ◽  
Future Research ◽  
Comprehensive Overview ◽  
Blockchain Technology ◽  
Future Research Directions ◽  
Grid Management

Power generation, distribution, transmission, and consumption face ongoing challenges such as smart grid management, control, and operation, resulting from high energy demand, the diversity of energy sources, and environmental or regulatory issues. This paper provides a comprehensive overview of blockchain-based solutions for smart grid management, control, and operations. We systematically summarize existing work on the use and implementation of blockchain technology in various smart grid domains. The paper compares related reviews and highlights the challenges in the management, control, and operation for a blockchain-based smart grid as well as future research directions in the five categories: collaboration among stakeholders; data analysis and data management; control of grid imbalances; decentralization of grid management and operations; and security and privacy. All these aspects have not been covered in previous reviews.

scholarly journals Network attack detection and visual payload labeling technology based on Seq2Seq architecture with attention mechanism

2020 ◽  
Vol 16 (4) ◽  
pp. 155014772091701
Author(s):  
Fan Shi ◽  
Pengcheng Zhu ◽  
Xiangyu Zhou ◽  
Bintao Yuan ◽  
Yong Fang
Keyword(s):  
Web Applications ◽  
Detection Algorithm ◽  
Attack Detection ◽  
Attention Mechanism ◽  
Detection Methods ◽  
The Internet ◽  
World Population ◽  
Network Attack ◽  
Education Medical ◽  
Iot Devices

In recent years, Internet of things (IoT) devices are playing an important role in business, education, medical as well as in other fields. Devices connected to the Internet is much more than the number of world population. However, it may face all kinds of attacks from the Internet easily for its accessibility. As we all know, most attacks against IoT devices are based on Web applications. So protecting the security of Web services can effectively improve the situation of IoT ecosystem. Conventional Web attack detection methods highly rely on samples, and artificial intelligence detection results are uninterpretable. Hence, this article introduced a supervised detection algorithm based on benign samples. Seq2Seq algorithm is been chosen and applied to detect malicious web requests. Meanwhile, the attention mechanism is introduced to label the attack payload and highlight labeling abnormal characters. The results of experiments show that on the premise of training a benign sample, the precision of proposed model is 97.02%, and the recall is 97.60%. It explains that the model can detect Web attack requests effectively. Simultaneously, the model can label attack payload visually and make the model “interpretable.”

scholarly journals Blockchain in Smart Grids: A Review on Different Use Cases

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4862 ◽  
Author(s):  
Tejasvi Alladi ◽  
Vinay Chamola ◽  
Joel J. P. C. Rodrigues ◽  
Sergei A. Kozlov
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Distribution Systems ◽  
Security And Privacy ◽  
Privacy And Security ◽  
Energy Trading ◽  
Blockchain Technology ◽  
Efficient Data ◽  
Privacy Issues ◽  
The Internet Of Things

With the integration of Wireless Sensor Networks and the Internet of Things, the smart grid is being projected as a solution for the challenges regarding electricity supply in the future. However, security and privacy issues in the consumption and trading of electricity data pose serious challenges in the adoption of the smart grid. To address these challenges, blockchain technology is being researched for applicability in the smart grid. In this paper, important application areas of blockchain in the smart grid are discussed. One use case of each area is discussed in detail, suggesting a suitable blockchain architecture, a sample block structure and the potential blockchain technicalities employed in it. The blockchain can be used for peer-to-peer energy trading, where a credit-based payment scheme can enhance the energy trading process. Efficient data aggregation schemes based on the blockchain technology can be used to overcome the challenges related to privacy and security in the grid. Energy distribution systems can also use blockchain to remotely control energy flow to a particular area by monitoring the usage statistics of that area. Further, blockchain-based frameworks can also help in the diagnosis and maintenance of smart grid equipment. We also discuss several commercial implementations of blockchain in the smart grid. Finally, various challenges to be addressed for integrating these two technologies are discussed.

scholarly journals Bi-Directional Mutual Energy Trade between Smart Grid and Energy Districts Using Renewable Energy Credits

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3088
Author(s):  
Sana Rehman ◽  
Bilal Khan ◽  
Jawad Arif ◽  
Zahid Ullah ◽  
Abdullah J. Aljuhani ◽  
...  
Keyword(s):  
Smart Grid ◽  
Graphical Analysis ◽  
Third Party ◽  
Security And Privacy ◽  
Central Authority ◽  
Energy Trading ◽  
Blockchain Technology ◽  
Energy Trade ◽  
Decentralized Energy ◽  
And Control

A central authority, in a conventional centralized energy trading market, superintends energy and financial transactions. The central authority manages and controls transparent energy trading between producer and consumer, imposes a penalty in case of contract violation, and disburses numerous rewards. However, the management and control through the third party pose a significant threat to the security and privacy of consumers’/producers’ (participants) profiles. The energy transactions between participants involving central authority utilize users’ time, money, and impose a computational burden over the central controlling authority. The Blockchain-based decentralized energy transaction concept, bypassing the central authority, is proposed in Smart Grid (SG) by researchers. Blockchain technology braces the concept of Peer-to-Peer (P2P) energy transactions. This work encompasses the SolarCoin-based digital currency blockchain model for SG incorporating RE. Energy transactions from Prosumer (P) to Prosumer, Energy District to Energy District, and Energy District to SG are thoroughly investigated and analyzed in this work. A robust demand-side optimized model is proposed using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to maximize Prosumer Energy Surplus (PES), Grid revenue (GR), percentage energy transactions accomplished, and decreased Prosumer Energy Cost (PEC). Real-time averaged energy data of Australia are employed, and a piece-wise energy price mechanism is implemented in this work. The graphical analysis and tabular statistics manifest the efficacy of the proposed model.

scholarly journals Blockchain Platforms and Access Control Classification for IoT Systems

Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1663
Author(s):  
Adam Ibrahim Abdi ◽  
Fathy Elbouraey Eassa ◽  
Kamal Jambi ◽  
Khalid Almarhabi ◽  
Abdullah Saad AL-Malaise AL-Ghamdi
Keyword(s):  
Access Control ◽  
Single Point ◽  
Security And Privacy ◽  
Future Research ◽  
Control Mechanisms ◽  
Privacy And Security ◽  
Security Issues ◽  
Massive Growth ◽  
Blockchain Technology ◽  
Comparison Table

The Internet of Things paradigm is growing rapidly. In fact, controlling this massive growth of IoT globally raises new security and privacy issues. The traditional access control mechanisms provide security to IoT systems such as DAC (discretionary access control) and mandatory access control (MAC). However, these mechanisms are based on central authority management, which raises some issues such as absence of scalability, single point of failure, and lack of privacy. Recently, the decentralized and immutable nature of blockchain technology integrated with access control can help to overcome privacy and security issues in the IoT. This paper presents a review of different access control mechanisms in IoT systems. We present a comparison table of reviewed access control mechanisms. The mechanisms’ scalability, distribution, security, user-centric, privacy and policy enforcing are compared. In addition, we provide access control classifications. Finally, we highlight challenges and future research directions in developing decentralized access control mechanisms for IoT systems.

scholarly journals Fusion Chain: A Decentralized Lightweight Blockchain for IoT Security and Privacy

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 391
Author(s):  
Dongjun Na ◽  
Sejin Park
Keyword(s):  
Data Privacy ◽  
Single Point ◽  
Consensus Algorithm ◽  
Security And Privacy ◽  
Public Key ◽  
Byzantine Fault Tolerance ◽  
Blockchain Technology ◽  
Private Data ◽  
Security Problem ◽  
Iot Devices

As the use of internet of things (IoT) devices increases, the importance of security has increased, because personal and private data such as biometrics, images, photos, and voices can be collected. However, there is a possibility of data leakage or manipulation by monopolizing the authority of the data, since such data are stored in a central server by the centralized structure of IoT devices. Furthermore, such a structure has a potential security problem, caused by an attack on the server due to single point vulnerability. Blockchain’s, through their decentralized structure, effectively solve the single point vulnerability, and their consensus algorithm allows network participants to verify data without any monopolizing. Therefore, blockchain technology becomes an effective solution for solving the security problem of the IoT’s centralized method. However, current blockchain technology is not suitable for IoT devices. Blockchain technology requires large storage space for the endless append-only block storing, and high CPU processing power for performing consensus algorithms, while its opened block access policy exposes private data to the public. In this paper, we propose a decentralized lightweight blockchain, named Fusion Chain, to support IoT devices. First, it solves the storage size issue of the blockchain by using the interplanetary file system (IPFS). Second, it does not require high computational power by using the practical Byzantine fault tolerance (PBFT) consensus algorithm. Third, data privacy is ensured by allowing only authorized users to access data through public key encryption using PKI. Fusion Chain was implemented from scratch written using Node.js and golang. The results show that the proposed Fusion Chain is suitable for IoT devices. According to our experiments, the size of the blockchain dramatically decreased, and only 6% of CPU on an ARM core, and 49 MB of memory, is used on average for the consensus process. It also effectively protects privacy data by using a public key infrastructure (PKI).

scholarly journals DDosTC: A Transformer-Based Network Attack Detection Hybrid Mechanism in SDN

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5047
Author(s):  
Haomin Wang ◽  
Wei Li
Keyword(s):  
Neural Network ◽  
Denial Of Service ◽  
Detection Algorithm ◽  
Attack Detection ◽  
Target System ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Optimal Model ◽  
Network Attack ◽  
Average Accuracy

Software-defined networking (SDN) has emerged in recent years as a form of Internet architecture. Its scalability, dynamics, and programmability simplify the traditional Internet structure. This architecture realizes centralized management by separating the control plane and the data-forwarding plane of the network. However, due to this feature, SDN is more vulnerable to attacks than traditional networks and can cause the entire network to collapse. DDoS attacks, also known as distributed denial-of-service attacks, are the most aggressive of all attacks. These attacks generate many packets (or requests) and ultimately overwhelm the target system, causing it to crash. In this article, we designed a hybrid neural network DDosTC structure, combining efficient and scalable transformers and a convolutional neural network (CNN) to detect distributed denial-of-service (DDoS) attacks on SDN, tested on the latest dataset, CICDDoS2019. For better verification, several experiments were conducted by dividing the dataset and comparisons were made with the latest deep learning detection algorithm applied in the field of DDoS intrusion detection. The experimental results show that the average AUC of DDosTC is 2.52% higher than the current optimal model and that DDosTC is more successful than the current optimal model in terms of average accuracy, average recall, and F1 score.

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