International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Blockchain-Powered Insider Threat Detection through Log Analysis |
|---|---|
| ABSTRACT | Because malicious activity is frequently carried out by users with authorized access privileges, insider threats present a serious cybersecurity risk that is challenging to identify with conventional security measures. The centralized log management used by traditional insider threat detection systems is susceptible to manipulation and lacks reliable auditability. This study suggests a blockchain-powered insider threat detection system that combines decentralized and unchangeable alert storage with rule-based log analysis to overcome these drawbacks. To find suspect activity such persistent unsuccessful login attempts, unauthorized resource access, unusual login timings, and privilege escalation, system and application logs are examined. When security alerts are detected, Ganache-deployed smart contracts use the SHA-256 method to cryptographically hash them and record them on a private Ethereum blockchain. This guarantees transparent audit trails, non-repudiation, and data integrity. Blockchain-verified alarm visualization, automated analysis, and safe log submission are all supported by a Flask-based web interface. The suggested method provides tamper-proof and reliable alert management while successfully identifying insider threats with little processing overhead, according to experimental evaluation. The platform provides a scalable basis for upcoming real-time and machine-learning-based expansions while improving insider threat monitoring's transparency and dependability |
| AUTHOR | SAKSHI N M, SANJANA G P, SNEHA M K, MANJUNATH K G UG Students, Dept. of CSE, Jain Institute of Technology, Davangere, Karnataka, India Assistant Professor, Dept. of CSE, Jain Institute of Technology, Davangere, Karnataka, India |
| VOLUME | 177 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1312124 |
| pdf/124_Blockchain-Powered Insider Threat Detection through Log Analysis.pdf | |
| KEYWORDS | |
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