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1,238 results ¡ page 16 of 52
Xianghui Meng, LingâLing Zhu
No abstract is available for this record.
Chandan Kumar, Prakash Chittora
No abstract is available for this record.
Hema Shekhawat, Daya Gupta
No abstract is available for this record.
Kunal Bhatia, Anirudh Khanna, Ishu Sharma
The disaster recovery mechanism is employed in various industries but in critical infrastructure scenarios, the process should be reliable and resilient. This research paper proposes a novel framework for disaster recovery methods for as Supervisory control and data acquisition systems using communication channels created by blockchain technology. The permission blockchain technology is integrated with as Supervisory control and data acquisition devices for configuring the data and event-sharing techniques. The research work presents the process of configuring and implementing the disaster recovery process of risk assessment, backup creation and event logging. Further, the events in the critical infrastructure are controlled by smart contract automation as part of the multichain blockchain. The consensus for fault tolerance is achieved by keeping 90% of the nodes operational in the network. The proposed solution is simulated by creating a private communication channel among as Supervisory control and data acquisition devices and the performance is evaluated with successful execution rate and average time of block confirmation by the disaster recovery process. The mining diversity, number of required active nodes, creation of stream and creation of distributed ledger is controlled by single administrative node in the proposed architecture which can be configured according to the requirements of the SCADA network architecture.
Anirudh RH, V Darshan, Kohav Dey, S Phaneesh ¡ 5 authors
The decentralized internet, often termed as Web3, is envisioned as the future of the online world. It holds the promise of addressing the centralization and censorship issues prevalent in todayâs web landscape. Yet, a significant hurdle faced by Web3 is its reliance on centralized servers provided by major entities like AWS and Azure. The vulnerability of this reliance becomes apparent when these servers encounter downtime or other disruptions, potentially causing widespread issues. This paper focuses on the crucial necessity of decentralizing Web3âs infrastructure to bolster its resilience against such outages. To accomplish this objective, we introduce an innovative RPC (Remote Procedure Call) relay protocol tailored specifically for Web3. This protocol not only caters to the requirements of Network as a Service (NaaS) platforms but also introduces incentives to motivate network nodes to function as relays. Our research and development efforts focus on two fundamental aspects: first, the technical implementation of the RPC relay protocol, and second, the incentivization mechanisms that reward network nodes for participating as relays. By enabling a more decentralized and robust infrastructure, we aim to enhance the reliability and stability of Web3 services.
Mohamed Vall Ould Mohamed, Almoataz Y. Abdelaziz, Farag K. AboâElyousr
No abstract is available for this record.
Peng Zhang, Peilin Wu, Yuhong Liu, Ye Chen ¡ 7 authors
The rapid expansion of transactive energy has transformed traditional electricity consumers into producers, engaging in local energy trading. In the context of distributed energy transactions, blockchain technology has been increasingly applied to facilitate transaction transparency and reliability. However, due to the challenges in collecting accurate energy transmission data from power lines, most existing studies on the blockchain-based transactive energy market are still vulnerable to security attacks, such as malicious users misreporting energy prices, refusing to pay or refusing to transmit energy. Therefore, based on the co-simulation platform PEMT-CoSim and a blockchain, we establish a blockchain-based, reputation-aware secure transactive energy market (STEM) by introducing a reputation scheme to evaluate the trustworthiness of all prosumers and designing reputation-aware, multi-round double auction and energy transmission algorithms to detect and penalize malicious attacks. Furthermore, we run comprehensive experiments for different use cases. The results show that even with malicious participants, the proposed system can guarantee the interests of the honest participants and improve the robustness and effectiveness of the energy market.
Saqib Rasool, Afshan Saleem, Muhammad Ikram ul Haq, Rune Hylsberg Jacobsen
In response to the critical need for environmentally sustainable practices, green energy certificates have emerged as a key mechanism to prevent greenwashing and ensure the authenticity of renewable energy sources. While incorporating blockchain technology has significantly enhanced the trans-parency and verifiability of these certificates, it has also intro-duced a trade-off in terms of increased operational costs due to the added control mechanisms of the blockchain. This challenge led to recent advancements in the state-of-the-art blockchain-based framework for verifiable green energy certificates, integrating trustworthy registries to balance trust and operational efficiency to enhance feasibility for real-world deployments. Our paper extended the same framework to elevate the trust factor without incurring additional operational costs of blockchain. At the heart of our proposed solution is integrating Self-Sovereign Identity (SSI), a technology that bolsters the system's reliability and empowers users/devices with control over their digital identities. By harmonizing the strengths of the Distributed Ledger Technologies (DLT) of IOTA with the public blockchain of Concordium, our framework maintains the integrity and transparency of the green energy certification process. It propels the system towards zero-trust security by distributing trust from a few centralized registries to many decentralized prosumer meters.
Muhammad Faheem, Mahmoud Ahmad AlâKhasawneh, Arfat Ahmad Khan, Syed Hamid Hussain Madni
Blockchain-based reliable, resilient, and secure communication for Distributed Energy Resources (DERs) is essential in Smart Grid (SG). The Solana blockchain, due to its high stability, scalability, and throughput, along with low latency, is envisioned to enhance the reliability, resilience, and security of DERs in SGs. This paper presents big datasets focusing on SQL Injection, Spoofing, and Man-in-the-Middle (MitM) cyberattacks, which have been collected from Solana blockchain-based Industrial Wireless Sensor Networks (IWSNs) for events monitoring and control in DERs. The datasets provided include both raw (unprocessed) and refined (processed) data, which highlight distinct trends in cyberattacks in DERs. These distinctive patterns demonstrate problems like superfluous mass data generation, transmitting invalid packets, sending deceptive data packets, heavily using network bandwidth, rerouting, causing memory overflow, overheads, and creating high latency. These issues result in ineffective real-time events monitoring and control of DERs in SGs. The thorough nature of these datasets is expected to play a crucial role in identifying and mitigating a wide range of cyberattacks across different smart grid applications.
Paraskevas Koukaras, Konstantinos D. Afentoulis, Paschalis A. Gkaidatzis, Aristeidis Mystakidis ¡ 7 authors
This research, conducted throughout the years 2022 and 2023, examines the role of blockchain technology in optimizing Demand Response (DR) within Smart Grids (SGs). It critically assesses a range of blockchain architectures, evaluating their impact on enhancing DRâs efficiency, security, and consumer engagement. Concurrently, it addresses challenges like scalability, interoperability, and regulatory complexities inherent in merging blockchain with existing energy systems. By integrating theoretical and practical viewpoints, it reveals the potential of blockchain technology to revolutionize Demand Response (DR). Findings affirm that integrating blockchain technology into SGs effectively enhances the efficiency and security of DR, and empirical data illustrate substantial improvements in both cases. Furthermore, key challenges include scalability and interoperability, and also identifying opportunities to enhance consumer engagement and foster system transparency in the adoption of blockchain within DR and SGs. Finally, this work emphasizes the necessity for further investigation to address development hurdles and enhance the effectiveness of blockchain technology in sustainable energy management in SGs.
Randhir Kumar, Ahamed Aljuhani, Danish Javeed, Prabhat Kumar ¡ 6 authors
Data-driven modeling using Artificial Intelligence (AI) is envisioned as a key enabling technology for Zero Touch Network (ZTN) management. Specifically, AI has shown huge potential for automating and modeling the threat detection mechanism of complicated wireless systems. The current data-driven AI systems, however, lack transparency and accountability in their decisions, and assuring the reliability and trustworthiness of the data collected from participating entities is an important obstacle to threat detection and decision-making. To this end, we integrate smart contracts with eXplainable AI (XAI) to design a robust cybersecurity framework for ZTN. The proposed framework uses a blockchain and smart contract-enabled access control and authentication mechanism to ensure trust among the participating entities. Additionally, with the collected data, we designed Digital Twins (DTs) for simulating the attack detection operation in the ZTN environment. Specifically, to provide a platform for analysis and the development of an Intrusion Detection System (IDS), the DTs are equipped with a variety of process-aware attack scenarios. A Self Attention-based Long Short Term Memory (SALSTM) network is used to evaluate the attack detection capabilities of the proposed framework. Furthermore, the explainability of the proposed AI-based IDS is achieved using the SHapley Additive exPlanations (SHAP) tool. The experimental results using N-BaIoT and a self-generated DTs dataset confirm the superiority of the proposed framework over some baseline and state-of-the-art techniques. ⢠A new robust cybersecurity framework for ZTN is proposed by integrating smart contracts with eXplainable AI. ⢠To ensure secure communication, a novel blockchain-enabled key establishment and access control mechanism is proposed that authenticates the participating entities in ZTN. The temper-proof property of blockchain ensures high integrity of the data enrichment and builds trust between the participating entities of blockchain network. A smart contract enabled Proof-of-Authority (PoA) consensus mechanism is used to verify and validate the transactions or data. ⢠The authenticated data from smart contract and blockchain-enabled authentication scheme is used to design DT for simulating the attack detection operation in ZTN environment. In particular, the DT is set up with a range of process aware attack scenarios to provide a platform for study and the creation of Intrusion Detection System (IDS). To assess the proposed frameworkâs ability to identify attacks, a Self Attention-based Long Short Term Memory (SALSTM) network is deployed. Additionally, utilizing the SHapley Additive exPlanations (SHAP) tool, the proposed AI-based IDS is made explainable. ⢠Through experiments using an actual DT simulated dataset and state-of-the-art intrusion dataset (N-BaIoT) is used to evaluate the proposed framework. The outcomes are compared with some baseline and state-of-the-art techniques to show the effectiveness of the proposed cybersecurity framework.
Prabhat Kumar, Danish Javeed, Randhir Kumar, A.K.M. Najmul Islam
Summary Artificial Intelligence (AI) based cyber threat detection tools are widely used to process and analyze a large amount of data for improved intrusion detection performance. However, these models are often considered as black box by the cybersecurity experts due to their inability to comprehend or interpret the reasoning behind the decisions. Moreover, AIâbased threat hunting is dataâdriven and is usually modeled using the data provided by multiple cloud vendors. This is another critical challenge, as a malicious cloud can provide false information (i.e., insider attacks) and can degrade the threatâhunting capability. In this paper, we present a blockchainâenabled eXplainable AI (XAI) for enhancing the decisionâmaking capability of cyber threat detection in the context of Smart Healthcare Systems. Specifically, first, we use blockchain to validate and store data between multiple cloud vendors by implementing a Clique ProofâofâAuthority (CâPoA) consensus. Second, a novel deep learningâbased threatâhunting model is built by combining Parallel Stacked Long Short Term Memory (PSLSTM) networks with a multiâhead attention mechanism for improved attack detection. The extensive experiment confirms its potential to be used as an enhanced decision support system by cybersecurity analysts.
Muhammad Aurangzeb, Yifei Wang, Sheeraz Iqbal, Ausnain Naveed ¡ 7 authors
Smart grids are getting important in todayâs power management, so with that, smart grid technologies are increasingly important too. There have been a lot of concerns about smart grid technologies being hacked, and as a result, some deep black box adversarial attacks have been conducted and presented. We propose a new experimental methodology for benchmarking smart grid security with black box attacks. Additionally, concerning the type of smart grids, Smart Power Grids, deep black box adversarial attacks which can be crafted using virtually no knowledge about the target due to the inherent complexity of content available in cryptographic libraries like SecLib or Bouncy Castle how it affects security of cyber-physical power systems. We identify potential impacts of deep black box attacks on Smart Power Grids as implemented by the Department of Energy in 1996, we evaluate existing protection methods, and we find out the pitfalls thereof. With the aim of overcoming the aforementioned drawbacks, we initiate a study on deep black box adversarial attacks against Smart Power Grids showing that statistically significant effects against a national Smart Power Grid are achievable with absolute security. We also probe detection of cyber security attacks on Smart Power Grids. We illustrate landscape of smart grids with numerous cyber threats and demonstrate the limitations of traditional security practices. We show the importance of machine learning to detect attacks and the unlikelihood of identification of dependable and efficient detection schemes. We describe quantum voting ensemble models as one of the most powerful techniques in the detection of cyber security attacks. Finally, we propose an experimental setup and evaluation criteria to detect cyber security attacks in smart grids using quantum voting ensemble models. Then, we talk about private data storage in blockchain based smart grid infrastructure. We give an introduction of block chain and its essentiality in smart grids. We discuss privacy issues in block chain based smart grids. We acknowledge the strength of privacy safeguards, but on the same wavelength, we realize their weaknesses. Next, we propose a quantum resistant encryption technique that enhances the privacy of smart grids. We propose quantum voting ensemble models as one of the most promising techniques to address the issue of private data storage in block chains. As a result, we provide a comparison between the proposed models and traditional approaches to privacy protection in smart grids based on an experimental performance review. Then, we propose a unified strategy to improve smart grid cyber security by incorporating deep black box attacks with quantum voting ensemble models. Finally, we disclose several benefits of such integration and perform an experimental evaluation to investigate the effectiveness of the unified approach. The results of our study identify security gaps in smart grids and propose state-of-the-art mechanisms to address them. The challenges of smart grids system require the amalgamation of blockchain, quantum voting ensemble models and deep black box adversarial attacks. We achieve this objective proposing a unified strategy. The results of this study will equally be helpful for future research and smart grid cyber security implementations.
Charithri Yapa, Chamitha de Alwis, Madhusanka Liyanage, Janaka Ekanayake
Blockchain has become the technology enabler in delivering modern Smart Grid 2.0 functionalities. Many services including Peer-to-Peer energy trading, distribution network management, financial settlements, and energy data management are catered through blockchain-enabled platforms. However, areas such as service quality-based pricing strategies, supplyâdemand balancing in distribution system to attain enhanced reliability and consumption-oriented rewarding mechanisms need improving in order to achieve the full benefits of the envisaged grid architecture. In response, this study proposes a novel Blockchain-as-a-Service for Energy Trading (BaaSET) platform, which offers reputation-based services, executed through smart contracts for smart grid applications. Reputation-based grid operations are automatically executed through smart contracts deployed onto a blockchain. The reputation is estimated using power quality and reliability indices, obtained through grid measurements. Further, tests have been conducted to evaluate the associated latency and the implementation cost of the proposed blockchainized service architecture. Test results signify the performance to be comparatively better considering the state-of-the-art. The results further suggest alternatives to improve the scalability of the architecture, to cater the increasing number of stakeholders in the SG 2.0 environment.
Jorge Medina, Roberto RojasâCessa
No abstract is available for this record.
Jagdish Pimple
The rapid development of physical device-based data collection in emerging technology needs smart, secure, and intelligent transmission. Cyber physical systems compete with the requirement of intelligent transmission of data. In cyber physical systems, security is a very challenging task due to the heterogeneous connections of devices in real time. This paper proposes a novel methodology for cyber-attack finding in cyber physical systems. The proposed system employed a DNN-deep neural network for the categorization of normal and attack data. The employed deep neural network design for 4 hidden layers for the detection of anomalies. For the secured transmission, we employed the blockchain process in Ethereum. The process of Ethereum generates blocks of blockchain with headers and transmits data over the cyberworld to the physical world with the alteration of data. For the authentication of the projected algorithm tested on two real-time datasets, such as NSL-KDD15 and CIDDS_001. The working of proposed algorithm is very promising in compression of existing algorithms of deep learning like RNN-recurrent neural networks, DBN, and DNN.
Godwin C. Okwuibe, Thomas Brenner, Muhammad Yahya, Peter Tzscheutschler ¡ 5 authors
Abstract Blockchainâbased local energy markets have been proposed in recent years to provide a market platform for local prosumers and consumers to exchange their energy in a secured, transparent and tamperâproof manner. However, there are still some challenges regarding the scalability of blockchain to handle high computational models/algorithms/contracts as this may result in the extension of the block size of the blockchain network and very high gas costs. Also, there is still the problem of transparency as regards General Data Protection Regulation because the full visibility of data in the blockchain may collide with privacy in some settings. A framework is presented that combines the onâchain features of blockchain with trusted execution environments to develop a transparent, tamperâresistant, low operation cost, scalable and resilient hybrid model architecture for local electricity trading. The model architecture was simulated in German community case scenarios for a varying number of prosumers and consumers to show its applicability. The simulation results show that the model was able to solve the scalability problem of blockchain for the local energy market application as the market model is run in a trusted environment where the integrity of the model can be verified by the participants.
Muhammad Faheem, Heidi Kuusniemi, Bahaa Eltahawy, Muhammad Shoaib Bhutta ¡ 5 authors
Abstract Energy is a crucial need in today's world for powering homes, businesses, transportation, and industrial processes. Fossil fuels, such as oil, coal, and natural gas, have been the primary sources of energy for decades. However, there is growing recognition of the negative environmental impact of fossil fuels and the need to transition to cleaner and more sustainable sources of energy. Distributed Energy Resources , such as wind and solar offer several benefits including, reducing energy costs, increasing resiliency, and decreasing carbon emissions. However, the integration of () into the grid requires advanced communication and secure control strategies to ensure a stable and reliable grid operations. In this regard, a blockchainâbased industrial wireless sensor network can provide secure and resilience data transmission to facilitate intelligent integration, monitoring, and control of in the smart grid. In this research, a smart contracts framework in Solana called Advanced Solana Blockchain () is proposed for in the smart grid. The proposed scheme enables resilient and secure realâtime control and monitoring of in smart grids. The performance evaluations and security analysis illustrated that this scheme is secure, reliable, and suitable in terms of lightweight data sharing between in smart grids.
Ali Shahidinejad, Jemal Abawajy, Shamsul Huda
The Internet of Things (IoT) has advanced smart grid (SG) infrastructure by providing smart meters (SMs) with enhanced capabilities such as the ability to leverage the Internet platform for bidirectional information exchange. Cryptographic keys are necessary for securely exchanging sensitive information between SMs and energy providers. To manage these keys, a secure key management protocol (KMP) with little overhead and influence on the SGâs overall performance is necessary. Although various KMPs are available for IoT-enabled SG environments, exiting solutions have several flaws in terms of certificate revocation, security requirements, and overall SG performance. To address these challenges, this paper proposes a blockchain-based computationally-efficient and highly-secure KMP for IoT-enabled SG environments. We show that, compared to existing solutions, the proposed KMP has better SM side efficiency with improved security and more properties such as perfect forward secrecy, conditional anonymity, and simple SM revocation.
Shaik Anjimoon, Rakesh Chandrashekar, Navdeep Singh, Ashish Parmar ¡ 6 authors
This proceeding volume has been retracted from the publication because we found some solid reasons to believe that it has infringed our integrity criteria and now presents a risk for our journal and scholarly science in general. Different types of malpractice are involved, in particular citation manipulation and inappropriate references. We are extremely concerned by such malpractice which considerably impacts the image of our title and our Publisherâs reputation. For further details, please refer to our publishing ethics policies . If you have any questions, please contact us at contact@webofconferences.org See the retraction notice E3S Web of Conferences 505, 00001 (2024), https://doi.org/10.1051/e3sconf/202450500001
Nabil Tazi Chibi, Omar Ait Oualhaj, Wassim Fassi Fihri, Hassan El Ghazi
Smart Grids (SGs) rely on advanced technologies, generating significant data traffic across the network, which plays a crucial role in various tasks such as electricity consumption billing, actuator activation, resource optimization, and network monitoring. This paper presents a new approach that integrates Machine Learning (ML), Blockchain Technology (BT), and Markov Decision Process (MDP) to improve the security of SG networks while ensuring accurate storage of events reported by various network devices through BT. The enhanced version of the Proof of Work (PoW) consensus mechanism ensures data integrity by preventing tampering and establishing the reliability of known and unknown attack detection. The proposed versions of PoW, namely GPoW 1.0 and GPoW 2.0, aim to make the consensus process more environmentally friendly.
M. Anwar, Noshina Tariq, Muhammad Ashraf, Syed Atif Moqurrab ¡ 7 authors
Cybersecurity challenges pose a significant threat to Healthcare Cyber Physical Systems (CPS) because they heavily rely on wireless communication. Particularly, jamming attacks can severely disrupt the integrity of these CPS networks. This research introduces a decentralized system to address this issue. Therefore, this paper suggested a system that leverages trust and blockchain technology to detect jamming attacks in healthcare CPS effectively. It proposes a layered model to improve CPS networksâ lifetime and performance. In smart healthcare environments, it ensures secure and reliable communication between sensor nodes, wearable sensors, medical devices, and monitoring systems. Results show that the suggested approach outperforms the baseline model in identifying and minimizing jamming assaults, with an average percentage difference of 15.71% more detection rate, 20.21% less packet loss rates, 16.65% less node-level energy consumption, reduced network latency of 8.29%, and 9.63% more network throughput.
Maheswari Raja, P. Saranya, Sharath Kumar Jagannathan, Gulhan Bizel
No abstract is available for this record.
Yan Li, Yan Li, Yuying Gong, Mingbo Wu ¡ 7 authors
Abstract Blockchain technology is demonstrating vast potential in the realm of distributed energy transactions. This article employs the Ethereum platform to architect an energy trading settlement framework. By incorporating whitelists, authorization mechanisms, and dedicated energy tokens, transactions are rendered more secure and reliable, ensuring the openness, transparency, traceability, and immutability of transaction information. The proposed transaction settlement mechanism automatically updates users' energy imbalances and levies corresponding charges, thereby ensuring strict adherence to transaction contracts. Furthermore, during the settlement phase, smart contracts are employed to autonomously evaluate the creditworthiness of transaction parties, with results recorded on the blockchain. As the credit levels of the entities across the entire network increase, the block generation time for distributed energy trading blockchains becomes shorter, with the block generation time predominantly influenced by the credit rating of the highest-rated entity in the network. Hence, through smart contract design based on energy trading, blockchain technology is utilized to enhance the transparency and security of transaction settlement and clearing. Future research could focus on improving blockchain scalability, integrating emerging technologies, to advance the effectiveness and adoption of blockchain-based energy trading systems.