Protect

Most of the world's internet access occurs through mobile devices such as smart phones and tablets. While these devices are convenient, they also enable crimes that intersect the physical world and cyberspace. For example, a thief who steals a smartphone can gain access to a person?s sensitive email, or someone using a banking app on the train may reveal account numbers to someone looking over her shoulder. This research will study how, when, and where people use smartphones and the relationship between these usage patterns and the likelihood of being a victim of cybercrime.

This capacity building project will create Secure Programming Clinic to enhance student learning and expertise in writing robust, secure software, analogous to a writing clinic in an English department or law school. It provides continual reinforcement of the mechanisms, methods, technologies, and need for programming with security and robustness considerations throughout a student's undergraduate coursework. The clinic would augment courses, not replace them or their content.

Mobile data are one of the fastest emerging forms of personal data. Ensuring the privacy and security of these data are critical challenges for the mobile device ecosystem. Mobile applications are easy to build and distribute, and can collect a large variety of sensitive personal data. Current approaches to protecting this data rely on security and privacy by design: encouraging developers to proactively implement security and privacy features to protect sensitive data.

Safeguarding sensitive user information stored in computer systems is a fast growing concern, especially as computers are universally used everywhere from national defense to mobile phones. Malicious hackers have found unscrupulous ways to steal sensitive information largely by exploiting the vulnerabilities in existing hardware and software. Among the many forms of information leakage, covert timing channels exfiltrate secrets from a trojan process with higher security credentials to a spy process with lesser credentials by exploiting the access timing of system resources.

The objective of this project is to investigate a comprehensive image privacy recommendation system, called iPrivacy (image Privacy), which can efficiently and automatically generate proper privacy settings for newly shared photos that also considers consensus of multiple parties appearing in the same photo. Photo sharing has become very popular with the growing ubiquity of smartphones and other mobile devices.