APAN59

The Security Working Group was formed with APAN for the objectives:
- To raise the security awareness and knowledge within APAN community.
- To cooperate with other international security efforts to raise security awareness, capabilities and interoperation globally.

Presentations during these sessions will have a security focus to further the objectives above, and paper summaries will be included in the final schedule description.

Title: Preparing for Post-Quantum Cryptography
Presenter:Jon Lau - Director, CISO Office & Scientific IT, A*STAR
Abstract:
The rapid advancements in quantum computing pose a significant challenge to existing cryptographic systems, necessitating a proactive shift towards quantum-safe security measures. This talk shares briefly the evolving quantum threat landscape, the release of NIST’s Post-Quantum Cryptography (PQC) standards, the critical need for crypto agility in adapting to these changes and the urgency of quantum readiness. This talk will have a brief on Quantum Key Distribution (QKD) and Singapore’s national efforts on Quantum Computing. It also offers an opportunity for attendees to voice the possibility to share and collaborate.

Title: Sharing Session: Collaborating with international partners for real-time detection of malicious TLS traffic using machine learning classifiers
Presenter: Shankar Karuppayah - Associate Professor, Universiti Sains Malaysia
Abstract:
The SOI Asia's CBR2 project focuses on the real-time detection of malicious TLS traffic using machine learning classifiers. In collaboration with multiple academic institutions, this research aims to enhance Network Intrusion Detection Systems (NIDS) by improving the detection accuracy of encrypted malicious traffic, automating dataset generation, and ensuring scalability for large-scale network monitoring. The project involved developing experimental setups, analyzing large-scale network traffic, and benchmarking various machine learning models to assess detection accuracy. This presentation will be focusing on a sharing key issues faced by the project during execution.

Title: NetSec Neural Network
Presenter: Rupam Barui, Senior Undergraduate, National Forensic Sciences University, Delhi Campus
Abstract:
This project addresses the growing complexity of network attacks by leveraging AI to enhance prediction and prevention of breaches. Traditional methods struggle with real-time anomalies and advanced threats, but AI improves security by learning patterns and automating responses. The system predicts network traffic patterns using neural networks, detects anomalies in real-time, and offers a scalable, automated solution. It features a user-friendly web application and interactive data visualization via Streamlit, aiming to improve traffic management, mitigate threats, and secure critical infrastructure.