RecGuard: An efficient privacy preservation blockchain-based system for online social network users

Frimpong, Samuel Akwasi; Han, Mangui; Boahen, Edward Kwadwo; Sosu, Rexford Nii Ayitey; Hanson, Isaac; Larbi-Siaw, Otu; Senkyire, Isaac Baffour

doi:10.1016/j.bcra.2022.100111

Cited by 10 publications

(3 citation statements)

References 35 publications

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“…The process involves the identification of deviations that lead to potential attacks, abnormalities, and fraudulent activities. Irregularities can be identified using graph-based methods, behavioral analysis, ML, and statistical techniques 103 . Statistical approaches utilize statistical techniques to identify abnormalities in transaction patterns, network behavior, or consensus parameters.…”

Section: Anomaly Detectionmentioning

confidence: 99%

Blockchain security enhancement: an approach towards hybrid consensus algorithms and machine learning techniques

Venkatesan,

Rahayu

2024

Sci Rep

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In this paper, we propose hybrid consensus algorithms that combine machine learning (ML) techniques to address the challenges and vulnerabilities in blockchain networks. Consensus Protocols make ensuring agreement among the applicants in the distributed systems difficult. However, existing mechanisms are more vulnerable to cyber-attacks. Previous studies extensively explore the influence of cyber attacks and highlight the necessity for effective preventive measures. This research presents the integration of ML techniques with the proposed hybrid consensus algorithms and advantages over predicting cyber-attacks, anomaly detection, and feature extraction. Our hybrid approaches leverage and optimize the proposed consensus protocols' security, trust, and robustness. However, this research also explores the various ML techniques with hybrid consensus algorithms, such as Delegated Proof of Stake Work (DPoSW), Proof of Stake and Work (PoSW), Proof of CASBFT (PoCASBFT), Delegated Byzantine Proof of Stake (DBPoS) for security enhancement and intelligent decision making in consensus protocols. Here, we also demonstrate the effectiveness of the proposed methodology within the decentralized networks using the ProximaX blockchain platform. This study shows that the proposed research framework is an energy-efficient mechanism that maintains security and adapts to dynamic conditions. It also integrates privacy-enhancing features, robust consensus mechanisms, and ML approaches to detect and prevent security threats. Furthermore, the practical implementation of these ML-based hybrid consensus models faces significant challenges, such as scalability, latency, throughput, resource requirements, and potential adversarial attacks. These challenges must be addressed to ensure the successful implementation of the blockchain network for real-world scenarios.

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Section: Anomaly Detectionmentioning

confidence: 99%

Blockchain security enhancement: an approach towards hybrid consensus algorithms and machine learning techniques

Venkatesan,

Rahayu

2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Economic Perspective In today's world, many internet service providers offer their services for free in exchange for user data through various IEEE Internet of Things Journal Manuscript ID: IoT-36643-2024 channels and devices [43], [45], [47]. However, this can lead to privacy violations, and users may unknowingly sacrifice their privacy for convenience [46]. Data brokerage businesses have emerged, facilitating the exchange of personal data for a price [43], [48], but "pay-for-privacy" models further erode data owners' privacy rights [9], [45].…”

Section: ) Potential Solutions For Challenges Identified Frommentioning

confidence: 99%

“…Additionally, every involved business must also be held accountable for compliance [61]. While experts still recommend using blockchain with smart contracts to create a decentralised IoT data marketplace, enabling policy-setting for accessing, storing, and sharing/transferring IoT data [45], [46], [52], [55], [58], [59], [68], [70], [71], [72], [73], however, it is essential to implement additional privacy-enhancing measures such as anonymisation, encryption, and differential privacy [9], [42], [48], [52], [62], [66], [68], [71], [74], [75], among others, to reinforce privacy protection. Data security measures, such as intrusion detection and threat analytics [45], [71], should also be made mandatory to overcome the privacy mechanism shortfalls in blockchain adoption.…”

Section: ) Potential Solutions For Challenges Identified Frommentioning

confidence: 99%