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7.883 Call For Paper

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Author(s):

Sabeena S | Jayasri D | Pooja Sri S | Gowtham D
Keywords:

IoT Security, Asset Monitoring, Anomaly Detection, Vulnerability Assessment, NetworkScanning, Data Visualization
Abstract:
The Rapid Rise Of Smart Infrastructure Has Brought With It A Surge In Connected IoT Devices Across Offices, Industries, And Public Spaces. This Connectivity Improves Efficiency, But It Also Widens The Door For Misuse, Cyberattacks, And Overlooked Asset Depreciation. Conventional Asset Tracking Systems Largely Focus On Inventory Counts, Rarely Linking Security Status With Asset Health. Our Work Introduces An IoT Scanner For Securing Connected Assets In Smart Systems — A Python–Django Framework That Ties Together Asset Flow Monitoring, Vulnerability Scanning, And Anomaly Detection. It Identifies Devices On The Network Through Active And Passive Scans, Profiles Their Security Posture, And Flags Abnormal Behaviour. Depreciation Is Automatically Computed At Set Intervals, And A Plotlybased Dashboard Presents Security Status, Anomalies, And Value Trends In One View. In Controlled Smart Office And Industrial IoT Setups, The System Reached 96% Accuracy In Vulnerability Detection And 94% In Anomaly Recognition, Exceeding The Performance Of Standard Scanners. The Proposed Approach Delivers A Practical, Scalable Means Of Protecting Modern Connected Environments While Supporting Smarter Asset Management.