TTP

Mobile devices and embedded systems have become ubiquitous in our society. Such systems use ARM processors, which differ greatly from the traditional x86 processors found in larger computing devices. As devices become smaller, there is a growing demand for virtualization, which provides benefits such as energy efficiency and the ability to use the device in multiple operational modes.

As society becomes more dependent on cyber infrastructure, the security of networks and information technologies has become a growing concern. Individuals, businesses, and governmental organizations are now common victims of cyber-attacks that seek to steal private data, gain remote control over remote systems, and cause harm to networks and systems through other malicious means. Additionally, critical infrastructures such as smart power grids and communication networks are facing an increasing number of cyber-based threats.

Network attacks are increasingly complex and fast-evolving. A single attack may use multiple reconnaissance, exploit, and obfuscation techniques. This project investigates how to extract critical attack attributes, synthesize novel attack sequences, and reveal potential threats to critical assets in a timely manner. The project uses machine learning techniques to simultaneously identify new attack types and observed events that could identify those attacks.

The cybercriminal community is inarguably more organized, better resourced and more motivated than ever to perpetrate massive-scale computer infections across the Internet. The malware distribution systems that they control and operate are characterized by their use of highly specialized suppliers and commoditized malware services.

The proliferation and increasing sophistication of censorship warrants continuing efforts to develop tools to evade it. Yet, designing effective mechanisms for censorship resistance ultimately depends on accurate models of the capabilities of censors, as well as how those capabilities will likely evolve. In contrast to more established disciplines within security, censorship resistance is relatively nascent, not yet having solid foundations for understanding censor capabilities or evaluating the effectiveness of evasion technologies.