Call for Paper - Upcoming Issues

ForenSecure-AILSO: A Blockchain-Fuzzy Intelligence Framework for Resilient Cloud Forensics and Secure Log Management in Distributed Environments

International Journal of Electronics and Communication Engineering
© 2025 by SSRG - IJECE Journal
Volume 12 Issue 7
Year of Publication : 2025
Authors : Ragu Gnanaprakasam, Ramamoorthy Sriramulu, Poorvadevi Ramamoorthy
10.14445/23488549/IJECE-V12I7P126
pdf
How to Cite?

Ragu Gnanaprakasam, Ramamoorthy Sriramulu, Poorvadevi Ramamoorthy, "ForenSecure-AILSO: A Blockchain-Fuzzy Intelligence Framework for Resilient Cloud Forensics and Secure Log Management in Distributed Environments," SSRG International Journal of Electronics and Communication Engineering, vol. 12,  no. 7, pp. 327-345, 2025. Crossref, https://doi.org/10.14445/23488549/IJECE-V12I7P126

Abstract:

Cloud computing continues to redefine the way data is stored, processed, and accessed globally. However, as organizations use more cloud services, digital forensic investigations get more complex in these networks. Typical forensic methods still struggle to handle secure logging, key exchange, and current threat sharing in systems that change their operation with growth and shrinkage. This paper introduces ForenSecure-AILSO, a unique cloud forensics framework that uses Fuzzy Logic, CALSO, and mechanisms based on smart contracts to secure the collection of evidence. It tackles important problems in multi-cloud computing, such as log storage verification, mystery identity generation, real-time monitoring to spot risks, and matching forensic evidence. In order to keep the information secure and traceable, the log entries are cleaned, enriched, and hashed with SHA-3 on the private consortium blockchain. With a fuzzy identity engine, automatic tokens are created that are difficult to trace, while CALSO keeps session keys strong by adjusting them regularly based on how difficult they are to break. CALSO-TPR directs an anomaly detection engine to quickly spot and alert about any suspicious activity. An evaluation of six key areas, using 10 benchmark models, reveals that ForenSecure-AILSO performs better than other options, scoring an F1-score for log cleaning of 94.0%, accuracy in identifying threats of 96.5%, and a key entropy of 289 bits. The framework managed to detect 99.2% of attempts to change digital tokens and was precise with 93.5% of its subgraph matches, proving its strength and adherence to laws.

Keywords:

Cloud forensics, Blockchain, Fuzzy Logic, CALSO, Session key optimization, Forensic integrity, Anomaly detection, Evidence correlation, Threat Prediction, Smart Contracts.

References:

[1] Xiaoxu Ren et al., “Building Resilient Web 3.0 Infrastructure with Quantum Information Technologies and Blockchain: An Ambilateral View,” Proceedings of the IEEE, vol. 112, no. 11, pp. 1686-1715, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[2] A. Venkata Nagarjun, and Sujatha Rajkumar, “Design of an Anomaly Detection Framework for Delay and Privacy-Aware Blockchain-Based Cloud Deployments,” IEEE Access, vol. 12, pp. 84843-84862, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Suresh Babu Erukala et al., “A Secure End-to-End Communication Framework for Cooperative IoT Networks Using Hybrid Blockchain System,” Scientific Reports, vol. 15, pp. 1-33, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Swarnamouli Majumdar, and Anjali Awasthi, “From Vulnerability to Resilience: Securing Public Safety GPS and Location Services with Smart Radio, Blockchain, and AI-Driven Adaptability,” Electronics, vol. 14, no. 6, pp. 1-19, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[5] P. Tamilselvi et al., “Blockchain Chain Based Cloud Security Using Provable Partitioned Folding Encryption for Integrity Proofing in Cloud Environment,” SN Computer Science, vol. 5, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Rachana Y. Patil et al., “Ensuring Accountability in Digital Forensics with Proxy Re-Encryption Based Chain of Custody,” International Journal of Information Technology, vol. 16, pp. 1841-1853, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Butrus Mbimbi, David Murray, and Michael Wilson, “Preserving Whistleblower Anonymity through Zero-Knowledge Proofs and Private Blockchain: A Secure Digital Evidence Management Framework,” Blockchains, vol. 3, no. 2, pp. 1-32, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Oluwatosin Selesi-Aina, “Blockchain-Enhanced Cloud Security Frameworks: Addressing Human-Network Vulnerabilities in Public and Private Sector Systems,” Journal of Engineering Research and Reports, vol. 26, no. 11, pp. 242-263, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Iraq Ahmad Reshi, and Sahil Sholla, “Securing IoT Data: Fog Computing, Blockchain, and Tailored Privacy-Enhancing Technologies in Action,” Peer-to-Peer Networking and Applications, vol. 17, pp. 3905-3933, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Lin Xu et al., “Blockchain Localization Cloud Computing Big Data Application Evaluation Method,” Open Computer Science, vol. 13, no. 1, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Kadhim Hayawi et al., “A False Positive Resilient Distributed Trust Management Framework for Collaborative Intrusion Detection Systems,” IEEE Transactions on Services Computing, vol. 18, no. 2, pp. 513-526, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Yuntao Wang et al., “Blockchain-Envisioned UAV-Aided Disaster Relief Networks: Challenges and Solutions,” IEEE Communications Magazine, vol. 63, no. 5, pp. 214-221, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Atefeh Zareh Chahoki, Hamid Reza Shahriari, and Marco Roveri, “CryptojackingTrap: An Evasion Resilient Nature-Inspired Algorithm to Detect Cryptojacking Malware,” IEEE Transactions on Information Forensics and Security, vol. 19, pp. 7465-7477, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Sourav Kunal et al., “Securing Patient Data in the Healthcare Industry: A Blockchain-Driven Protocol with Advanced Encryption,” Journal of Education and Health Promotion, vol. 13, no. 1, pp. 1-13, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Ali Shahidinejad, Jemal Abawajy, and Shamsul Huda, “Untraceable Blockchain-Assisted Authentication and key Exchange in Medical Consortiums,” Journal of Systems Architecture, vol. 151, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Abdullah Mujawib Alashjaee, and Fahad Alqahtani, “Improving Digital Forensic Security: A Secure Storage Model with Authentication and Optimal Key Generation Based Encryption,” IEEE Access, vol. 12, pp. 29738-29747, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Ao Liu et al., “DynaShard: Secure and Adaptive Blockchain Sharding Protocol with Hybrid Consensus and Dynamic Shard Management,” IEEE Internet of Things Journal, vol. 12, no. 5, pp. 5462-5475, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Manuel J.C.S. Reis et al., “Blockchain-Enhanced Security for 5G Edge Computing in IoT,” Computation, vol. 13, no. 4, pp. 1-28, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Mritunjay Shall Peelam, and Vinay Chamola, “Enhancing Security Using Quantum Blockchain in Consumer IoT Networks,” Transactions on Consumer Electronics, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Saad Said Alqahtany, and Toqeer Ali Syed, “ForensicTransMonitor: A Comprehensive Blockchain Approach to Reinvent Digital Forensics and Evidence Management,” Information, vol. 15, no. 2, pp. 1-27, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Nan Xiao et al., “A Novel Blockchain-Based Digital Forensics Framework for Preserving Evidence and Enabling Investigation in Industrial Internet of Things,” Alexandria Engineering Journal, vol. 86, pp. 631-643, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Annas Wasim Malik et al., “Cloud Digital Forensics: Beyond Tools, Techniques, and Challenges,” Sensors, vol. 24, no. 2, pp. 1-30, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Butrus Mbimbi, David Murray, and Michael Wilson, “IoT Forensics-Based on the Integration of a Permissioned Blockchain Network,” Blockchains, vol. 2, no. 4, pp. 482-506, 2024.
[CrossRef] [Google Scholar] [Publisher Link]