Iraqi Paradigm E-Voting System Based on Hyperledger Fabric Blockchain Platform

Saeed, Shatha H.; Hadi, Suha Mohammed; Hamad, Ali H.

doi:10.18280/isi.270506

Cited by 4 publications

(4 citation statements)

References 20 publications

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“…The findings show that the proposed IDS through XGBoost records lower false alarm rates for each and every attack than the RF, LR, and false alarm rates. This demonstrates that, when compared to other models, the model obtains the best DR [27,28].…”

Section: Figure 6 Performance Comparison Of Provision_pt_737ementioning

confidence: 72%

Implementation of Blockchain with Machine Learning Intrusion Detection System for Defending IoT Botnet and Cloud Networks

Siddamsetti¹,

Srivenkatesh²

2022

ISI

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Significant research has been done on combining intrusion detection and blockchain to increase data privacy and find both current and future threats. This research suggests a machine blockchain framework (MBF) in order to provide distributed intrusion detection with security and blockchain with privacy with the help of smart contracts in IoT networks. An XGBoost algorithm was implemented to work with sequential network data and the intrusion detection approach is explored using the N-BaIoT dataset. In order to protect the network against known malware threats (Mirai, Gafgyt, or Bashlite), the IoT malware attack prediction model created in this study offers a deterrent strategy based on the network traffic statistics. On the other hand, the models need to be taught to recognize new varieties of malware. In this work, we observe how different machine learning models, like Random Forest algorithm and proposed XGBoost algorithm, can accurately predict the infected malware in certain traffic instance. However, we provide a honeypot-based strategy that employs machine learning techniques for the detection of malware in this study. Using data from an IoT Botnet as a dataset helps train a machine learning model in a way that is effective and changes over time.

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Section: Figure 6 Performance Comparison Of Provision_pt_737ementioning

confidence: 72%

Implementation of Blockchain with Machine Learning Intrusion Detection System for Defending IoT Botnet and Cloud Networks

Siddamsetti¹,

Srivenkatesh²

2022

ISI

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“…The influence of electronic voting on Hyperledger Fabric's throughput and latency was scrutinized by Saeed et al [19]. Modulations of block size, timeout, and transaction rates revealed the necessity of augmenting both block size and timeout to maintain high throughput amidst high transaction volumes.…”

Section: Related Workmentioning

confidence: 99%

Evaluating the Performance of a Multi-Organizational E-Government Platform on Hyperledger Fabric with Fuzzy Logic-Enhanced Multi-Channel Connectivity

Kadhum,

Hamad

2024

ISI

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In the domain of e-government, the integration of multiple organizations is imperative for the effective delivery of public services through online platforms. This study examines a hyperledger fabric blockchain platform, which interconnects six organizations via a network of four distinct communication channels. A fuzzy logic-based mechanism has been employed to determine the optimal channel for executing transactions, contingent on client volume. A series of experiments were conducted to assess the system's performance in terms of throughput, latency, and scalability. These experiments varied parameters including transaction rates, block sizes, the number of participating organizations, and client count. It was observed that a multi-channel architecture significantly outperformed a singlechannel setup in enhancing throughput and reducing latency. The findings indicate that even with the expansion to six organizations and an increase in clients to two hundred, the deployment of a multi-channel structure only resulted in marginal throughput degradation and a modest latency increment when contrasted with a single-channel framework. Moreover, the strategic distribution of block sizes across the four channels was found to substantially bolster the scalability of the system. This facilitated the inclusion of additional clients and organizations with minimal impact on the overall system performance.

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“…HLF, in particular, is a platform that leverages open-source software and deploys permissioned distributed ledger technology (DLT) specifically designed to cater to the needs of enterprise-level applications. The platform has unique characteristics that differentiate it from other commonly utilized distributed ledger platforms [7].…”

Section: Introductionmentioning

confidence: 99%

Inter and Intra Domain DDoS Attack Mitigation for Software Defined Network Based on Hyperledger Fabric Blockchain Technology

Khorseed,

Hamad

2024

ISI

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The widespread adoption of Internet of Things devices has led to a significant rise in security concerns. Attackers can exploit the vulnerability of centralized control in softwaredefined networks (SDN) through distributed denial of service (DDoS) attacks on these networks. The concentration of control within a network introduces novel vulnerabilities and potential avenues for attacks. The present strategies employed for mitigating DDoS attacks face challenges arising from their constrained adaptability, inadequate allocation of resources, and reduced flexibility. The developing technology of blockchain offers a robust solution for cost-effective, optimized, and adaptable mitigation of inter and intra-domain SDN against DDoS attacks. This work utilizes the Hyperledger Fabric platform, a permissioned blockchain, to examine the detection of DDoS attacks using the entropy approach. The IP addresses of the victims are compiled into a blacklist, which is subsequently disseminated as transactions to generate a ledger of the blockchain over the network. Employing this method makes it unnecessary to obstruct the victim's ports. Two scenarios, namely, single and linear, have been employed to represent intradomain topology and one scenario for interdomain in the context of multicontroller environments. The experiment investigates the effects of two attack types, single attack and multi-attacker, across three different circumstances. The findings indicate that the duration of mitigation was decreased, demonstrating the efficacy of enhancing the overall network security with increased flexibility. This approach has promise for countering DDoS attacks. This work advances by using a permissioned network with an SDN to mitigate DDOS attacks and using drop packets rather than block ports. Using HLF makes setting various configurations possible, and this act can enhance performance. Results show that mitigation time in the three topologies (single, liner, and multi-controller) was 30, 21, and 48, respectively, at the victim side, while it takes 40, 43, and 60 at the controller side.

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Iraqi Paradigm E-Voting System Based on Hyperledger Fabric Blockchain Platform

Cited by 4 publications

References 20 publications

Implementation of Blockchain with Machine Learning Intrusion Detection System for Defending IoT Botnet and Cloud Networks

Implementation of Blockchain with Machine Learning Intrusion Detection System for Defending IoT Botnet and Cloud Networks

Evaluating the Performance of a Multi-Organizational E-Government Platform on Hyperledger Fabric with Fuzzy Logic-Enhanced Multi-Channel Connectivity

Inter and Intra Domain DDoS Attack Mitigation for Software Defined Network Based on Hyperledger Fabric Blockchain Technology

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