Derek G. Tsui

Andres Molina-Markham, Luis Robaina, Sean Steinle et al.

Open-ended learning (OEL) -- which emphasizes training agents that achieve broad capability over narrow competency -- is emerging as a paradigm to develop artificial intelligence (AI) agents to achieve robustness and generalization. However, despite promising results that demonstrate the benefits of OEL, applying OEL to develop autonomous agents for real-world cybersecurity applications remains a challenge. We propose a training approach, inspired by OEL, to develop autonomous network defenders. Our results demonstrate that like in other domains, OEL principles can translate into more robust and generalizable agents for cyber defense. To apply OEL to network defense, it is necessary to address several technical challenges. Most importantly, it is critical to provide a task representation approach over a broad universe of tasks that maintains a consistent interface over goals, rewards and action spaces. This way, the learning agent can train with varying network conditions, attacker behaviors, and defender goals while being able to build on previously gained knowledge. With our tools and results, we aim to fundamentally impact research that applies AI to solve cybersecurity problems. Specifically, as researchers develop gyms and benchmarks for cyber defense, it is paramount that they consider diverse tasks with consistent representations, such as those we propose in our work.

Xing Jin, Tongbo Luo, Derek G. Tsui et al.

HTML5-based mobile apps become more and more popular, mostly because they are much easier to be ported across different mobile platforms than native apps. HTML5-based apps are implemented using the standard web technologies, including HTML5, JavaScript and CSS; they depend on some middlewares, such as PhoneGap, to interact with the underlying OS. Knowing that JavaScript is subject to code injection attacks, we have conducted a systematic study on HTML5-based mobile apps, trying to evaluate whether it is safe to rely on the web technologies for mobile app development. Our discoveries are quite surprising. We found out that if HTML5-based mobile apps become popular--it seems to go that direction based on the current projection--many of the things that we normally do today may become dangerous, including reading from 2D barcodes, scanning Wi-Fi access points, playing MP4 videos, pairing with Bluetooth devices, etc. This paper describes how HTML5-based apps can become vulnerable, how attackers can exploit their vulnerabilities through a variety of channels, and what damage can be achieved by the attackers. In addition to demonstrating the attacks through example apps, we have studied 186 PhoneGap plugins, used by apps to achieve a variety of functionalities, and we found that 11 are vulnerable. We also found two real HTML5-based apps that are vulnerable to the attacks.