Smart Cybersecurity Intrusion Detection & Prevention System Using Ai (securityhub)

• Author(s):

  Proff. Jaypal Gedam | Mr. Sujal Ramteke | Mr. Atharva Sable | Mr. Swayam Wankhede | Mr. Aman Hirole

• Keywords:

  Edge Computing, Raspberry Pi 5, Hailo-8L, Suricata, Keycloak, Face Recognition, Intrusion Detection System (IDS), IoT Security, ArcFace.

• Abstract:

  This Project Examines The Combination Of Network-level Security And Physical Biometric Verification Within A Unified, Hardware-accelerated Edge Environment. Conventional Security Setups Frequently Struggle With Operational Slowdowns, Primarily Caused By High-latency Cloud Dependencies And The Large Bandwidth Needs Of Remote Data Handling. To Fix These Issues, We Present A Localized Security Hub Designed For The Raspberry Pi 5 And The Hailo-8L AI Accelerator. This Setup Allows For The Simultaneous Running Of Deep Packet Inspection Through Suricata And Real-time Facial Recognition Using The ArcFace Model. By Integrating Keycloak As A Centralized Identity Provider, The System Ensures A Unified Security Environment Where Network Access Rules Are Assigned Based On Biometrically Verified Roles. This Research Shows That Enterprise-level Security—capable Of Managing Both Digital Threats And Physical Breaches—is Possible On A Low-power, Single-board Device. Our Results Show That Using The Dedicated PCIe Gen 3 Interface On Raspberry Pi 5 For AI Tasks Significantly Improves Speed While Protecting Data Privacy. Ultimately, This Method Offers A Sturdy, Small Scale Budget-friendly Alternative To Traditional Isolated And Expensive Security Tools, Creating A Reliable Zero-Trust Environment At The Network Edge.

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Other Details

• Paper id:

  IJSARTV12I4105053

• Published in:

  Volume: 12 Issue: 4 April 2026

• Publication Date:

  2026-04-17

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