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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM62282
Volume:
10 |
5 |
May 2026
Pages:
1-4
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Computer Science and Engineering
Collage of Engineering and Technology Akola, Maharashtra, India
Computer Science and Engineering
Collage of Engineering and Technology Akola, Maharashtra, India
Computer Science and Engineering
Collage of Engineering and Technology Akola, Maharashtra, India
Computer Science and Engineering
Collage of Engineering and Technology Akola, Maharashtra, India
Computer Science and Engineering
Collage of Engineering and Technology Akola, Maharashtra, India
Securing enterprise terminals represents a comprehensive solution to the critical problem of credential theft and sophisticated AI-driven social engineering. The proposed expert system, SentinelAuth (AiOS), is a Zero-Trust adaptive security platform that bridges the gap between public cyber-awareness and OS-level endpoint enforcement. By integrating Face++ Biometrics for identity assurance and Isolation Forest Machine Learning for autonomous threat intelligence, the system mitigates risks like Zero-Day Phishing and rogue insider attacks. The research details a kiosk-based lockdown mechanism that ensures session integrity through real-time telemetry and decentralized cloud logging. Experimental results demonstrate a 90% reduction in SOC alert fatigue and a 98.4% accuracy in detecting anomalous network traffic. Key Words: Zero-Trust Security, Multi-factor Authentication (MFA), Isolation Forest, Biometrics, Session Management, AI-driven Threat Intelligence.
KEYWORDS
SentinelAuth successfully replaces easily bypassed browser extensions with an uncompromising OS Kernel-level firewall. The integration of 4-layer MFA and ML-driven telemetry ensures absolute Zero-Trust compliance across the workforce. Future work includes upgrading the system with Keystroke Dynamics for continuous behavioral authentication.
1) Anonymous, "Zero Trust Architecture: A Systematic Literature Review and Taxonomy," Journal of Netwoand Systems Management, 2026. 2) Anonymous, "Anomaly Detection in Computer Networks Using Isolation Forest in Data Mining," Jurnal Teknik Informatika, Vol. 18, No. 1, 2025. 3) Anonymous, "Isolation Forest-Based Anomaly Detection in IoT Smart Home Network Traffic," KEMDIKTISAINTEK, No. 10/C/C3/DT.05.00, 2025. 4) Anonymous, "Streaming Data Anomaly Detection Integrating Adaptive Isolation Forests and Self-supervised Learning," Frontiers in Physics, 2025. 5) Anonymous, "Lockbox: A Zero Trust Architecture for Secure Processing of Sensitive Cloud Workloads," Flexera 2025 State of the Cloud Report, 2025. 6) Anonymous, "Biometrics Trends for 2026: Foundation of Digital Trust in a Post-CAPTCHA World," Industry Technology Insights, 2026. 7) Anonymous, "Modern Authentication Trends: Beyond Traditional MFA in 2026," Identity Security Report, 2026. 8) Anonymous, "Online-iForest: Tracking Data Generating Processes as They Evolve Over Time," arXiv Preprint, 2025. 9) Anonymous, "Deep Kernel Defense: Operating System Level Packet Interception using PyDivert and Scapy," Applied Sciences, 2025. 10) Anonymous, "Adaptive Session Security and Zero-Trust Identity Gates for Enterprise Terminals," Research Publication Cell, 2026.
Publication Date
5/2/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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