Detect

Natural language privacy policies have become a de facto standard to address expectations of notice and choice on the Web. Yet, there is ample evidence that users generally do not read these policies and that those who occasionally do struggle to understand what they read. Initiatives aimed at addressing this problem through the development of machine implementable standards or other solutions that require website operators to adhere to more stringent requirements have run into obstacles, with many website operators showing reluctance to commit to anything more than what they currently do.

The goal of the project is to provide a secure foundation for a transportation system that increasingly relies on the cooperation, connectedness, and automation of vehicles to achieve increases in safety, efficiency, and capacity. The financial losses attributable to congestion in America's transportation infrastructure are more than $1 trillion annually and the parallel loss of life in vehicle collisions is 40,000 deaths per year.

As the use of Web applications has increased, malicious content and cyber attacks are rapidly increasing in both their frequency and their sophistication. For unwary users and their organizations, social media sites such as Tumblr, Facebook, MySpace, Twitter, and LinkedIn pose a variety of serious security risks and threats. Recent studies show that social media sites are more in use for delivering malware than were previously popular methods of email delivery. Because of this, many organizations are looking for ways to implement effective security policies.

The security and integrity of elections is paramount in the furtherance of democracy. However, enhanced security often comes at the cost of making voting systems significantly more difficult for voters to use. With input from stakeholders in the voting process (most notably Travis County, Texas), we are constructing a prototype voting system and investigating how to design such a system so that it is significantly more secure than current solutions, without making it harder to participate in the election process.

This research explores a new approach to securing systems that are based on crowd computations, where the operator polls the opinions of crowds--arbitrary users of the system--to provide a variety of recommendation services. Examples include services like Yelp, YouTube, Twitter, and TripAdvisor. However, today's services are known to suffer from multiple identity (Sybil) attacks, where an attacker creates many identities to subvert the system (e.g., make their business appear to be more popular on Yelp).