Fim Intelligent File Integrity Monitoring System With Ransomware Detection

Abstract

File Integrity Monitoring Has Become An Essential Component Of Modern Cybersecurity Systems As Organizations Increasingly Rely On Digital Infrastructure To Store And Process Critical Data. Unauthorized Modification Of Files And Ransomware Attacks Can Lead To Severe Data Loss, Operational Disruption, And Financial Damage. Traditional File Monitoring Systems Primarily Focus On Detecting File Changes But Often Fail To Analyzebehavioral Patterns Associated With Malicious Activities. This Paper Presents An Intelligent File Integrity Monitoring System With Integrated Ransomware Detection Capabilities Designed To Improve Host-based Security Monitoring. The Proposed System Continuously Monitors File System Activities Such As File Creation, Modification, And Deletion In Real Time. A Behavioral Profiling Mechanismalong With A Hybrid Risk Scoring Model Is Applied To Analyze Abnormal Activity Patterns And Classify Potential Threats. To Detect Possible Ransomware Encryption Behavior, Entropy-based Analysis Is Performed On Modified Files. The Framework Also Incorporates Directory Traversal Detection And Multi File-type Monitoring To Identify Suspicious File Access Patterns That Commonly Occur During Ransomware Attacks. When Abnormal Activity Is Detected, Automated Response Mechanisms Including Email Alerts And File Quarantine Are Triggered To Mitigate Potential Damage. The System Also Provides A Graphical Dashboard For Real-time Monitoring And Generates Structured Security Reports For Forensic Analysis. Experimental Testing Demonstrates That The Proposed Monitoring System Effectively Detects Abnormal File Behavior And Enhances The Ability To Identify Potential Ransomware Activities In Host-based Environments.

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