1. Background: Isolated Local Area Networks (LANs), which operate without internet connectivity, present unique cybersecurity challenges. These environments often lack effective real-time anomaly detection, malware identification, USB device control, and process monitoring. Traditional security solutions that depend on external updates, malware signatures, or Indicators of Compromise (IOCs) become obsolete, leaving networks vulnerable to advanced persistent threats, insider compromises, and zero-day attacks. As cyber threats evolve, a specialized approach to securing these high security networks is imperative. 2. Objective: This project aims to develop an AI-powered security solution tailored for air-gapped LANs. The system will focus on autonomously detecting anomalies, identifying malware, monitoring USB device usage, and ensuring comprehensive offline protection. By leveraging advanced machine learning algorithms, the solution will provide robust cybersecurity without the need for external resources. 3. Key Features (a) Autonomous Anomaly Detection: The solution must autonomously detect deviations in network behaviour, unauthorized process executions, and anomalous traffic patterns without relying on external signatures or predefined threat indicators. (b) Advanced Malware Detection: It should utilize behaviour-based techniques to identify both known and unknown malware, ensuring comprehensive protection against zero-day exploits without the need for regular signature updates. (c) USB Device Monitoring and Control: The system must provide real- time monitoring of USB device connections and enable the remote blocking of unauthorized devices to prevent data exfiltration or the introduction of malicious payloads. (d) Total Offline Operation: The solution must be self sufficient and operate entirely offline, ensuring uninterrupted protection in high-security, air-gapped environments without the need for internet access or external data feeds. 4. Advantages over Present Solutions (a) Elimination of signature dependency: By employing advanced Machine Learning techniques, the system effectively detects anomalies without needing external threat signatures or IOCs, enabling the identification of zero-day attacks and novel threats with precision. (b) Full Offline Autonomy: Unlike conventional security systems, this solution operates independently of internet connectivity, ensuring continuous protection and threat detection in even the most isolated and secure networks. (c) Immediate USB Device Control: The system offers real time USB device monitoring and the capability to remotely disable unauthorized devices, enhancing data integrity and preventing unauthorized access or data theft. (d) Comprehensive, Multi-Layered Monitoring: Beyond standard access control, the tool continuously analyzes network traffic, running processes, and hardware interactions using sophisticated AI models, providing an adaptive, multi- layered security framework that outperforms traditional solutions in isolated network environments. 5. Expected Outcomes: The implementation of this AI-driven LAN security solution is expected to enhance the overall security posture of air-gapped networks. Organizations will benefit from improved anomaly detection and malware identification, leading to quicker responses to potential threats. The system's ability to operate offline and provide real-time USB control will further mitigate risks associated with unauthorized access and data breaches, creating a robust defence against sophisticated attacks. 6. Unique Contribution: This AI-driven LAN security solution is uniquely designed to function autonomously within isolated networks, utilizing state-of-the-art machine learning algorithms such as Auto-encoders, Random Forests, and Isolation Forests for anomaly detection. It allows for proactive defence against zero-day threats and sophisticated attacks without reliance on traditional signatures or IOCs. The combination of real-time USB device control, comprehensive network monitoring, and offline capabilities provides a level of protection that is unmatched by conventional security systems, making it an essential tool for safeguarding high-security networks.