Security

To uncover vulnerabilities before attackers exploit them. To fortify systems against evolving threats. To innovate defenses for a safer digital future. Because security isn’t optional—it’s essential. We research to protect, prevent, and pioneer resilience in an interconnected world.

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Modelling

To simulate complex systems before they fail. To optimize performance, predict risks, and design resilient architectures. Because accurate models save time, money, and lives. We innovate to turn theoretical precision into real-world solutions for industries, climates, and technologies.

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Networking

To build faster, smarter, and unhackable connections. To enable seamless communication across global infrastructures. Because the future rely on reliable data flow. We pioneer protocols that scale, adapt, and defend against tomorrow’s bandwidth and security issues.

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Enhanced backdoor resilience in cross-platform systems using zero trust based software defined perimeter architecture powered with SnortML IDS/IPS

Backdoor attacks pose serious security risks in modern network environments, particularly on Windows and Linux-based Operating Systems (OSs) in server systems, often serving as entry points for advanced persistent threats (APTs). Traditional Intrusion Detection and Prevention Systems (IDS/IPS) face challenges in detecting these evolving threats due to their dependence on signature-based detection methods. This paper

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Brute-force attack mitigation on remote access services via software-defined perimeter

Remote Access Services (RAS)—including protocols such as Remote Desktop Protocol (RDP), Secure Shell (SSH), Virtual Network Computing (VNC), Telnet, File Transfer Protocol (FTP), and Secure File Transfer Protocol (SFTP)—are essential to modern network infrastructures, particularly with the rise of remote work and cloud adoption. However, their exposure significantly increases the risk of brute-force attacks (BFA),

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Influence of Access Points’ Height and High Signal Relation in WLAN Fingerprinting-Based Indoor Positioning Systems’ Accuracy

Wireless Local Area Network (WLAN) Fingerprinting-based Indoor Positioning Systems (IPS) offer several key advantages over other indoor positioning technologies, including cost-effectiveness with high accuracy and passive tracking of entities’ location without Global Positioning System (GPS) dependence. However, achieving a satisfactory accuracy performance of the WLAN fingerprinting-based IPS is still challenging, as it is affected by

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