Visible to the public Biblio

Filters: Author is Rahul Telang  [Clear All Filters]
2016-12-08
Alain Forget, Sarah Pearman, Jeremy Thomas, Alessandro Acquisti, Nicolas Christin, Lorrie Cranor, Serge Egelman, Marian Harbach, Rahul Telang.  2016.  Do or Do Not, There Is No Try: User Engagement May Not Improve Security Outcomes. Proceedings of the Twelfth Symposium on Usable Privacy and Security (SOUPS 2016).

Computer security problems often occur when there are disconnects between users’ understanding of their role in computer security and what is expected of them. To help users make good security decisions more easily, we need insights into the challenges they face in their daily computer usage. We built and deployed the Security Behavior Observatory (SBO) to collect data on user behavior and machine configurations from participants’ home computers. Combining SBO data with user interviews, this paper presents a qualitative study comparing users’ attitudes, behaviors, and understanding of computer security to the actual states of their computers. Qualitative inductive thematic analysis of the interviews produced “engagement” as the overarching theme, whereby participants with greater engagement in computer security and maintenance did not necessarily have more secure computer states. Thus, user engagement alone may not be predictive of computer security. We identify several other themes that inform future directions for better design and research into security interventions. Our findings emphasize the need for better understanding of how users’ computers get infected, so that we can more effectively design user-centered mitigations.

2016-12-06
Alain Forget, Saranga Komanduri, Alessandro Acquisti, Nicolas Christin, Lorrie Cranor, Rahul Telang.  2014.  Security Behavior Observatory: Infrastructure for Longterm Monitoring of Client Machines.

Much of the data researchers usually collect about users’ privacy and security behavior comes from short-term studies and focuses on specific, narrow activities. We present a design architecture for the Security Behavior Observatory (SBO), a client-server infrastructure designed to collect a wide array of data on user and computer behavior from a panel of hundreds of participants over several years. The SBO infrastructure had to be carefully designed to fulfill several requirements. First, the SBO must scale with the desired length, breadth, and depth of data collection. Second, we must take extraordinary care to ensure the security and privacy of the collected data, which will inevitably include intimate details about our participants’ behavior. Third, the SBO must serve our research interests, which will inevitably change over the course of the study, as collected data is analyzed, interpreted, and suggest further lines of inquiry. We describe in detail the SBO infrastructure, its secure data collection methods, the benefits of our design and implementation, as well as the hurdles and tradeoffs to consider when designing such a data collection system. 

Alain Forget, Saranga Komanduri, Alessandro Acquisti, Nicolas Christin, Lorrie Cranor, Rahul Telang.  2014.  Building the security behavior observatory: an infrastructure for long-term monitoring of client machines. HotSoS '14 Proceedings of the 2014 Symposium and Bootcamp on the Science of Security.

We present an architecture for the Security Behavior Observatory (SBO), a client-server infrastructure designed to collect a wide array of data on user and computer behavior from hundreds of participants over several years. The SBO infrastructure had to be carefully designed to fulfill several requirements. First, the SBO must scale with the desired length, breadth, and depth of data collection. Second, we must take extraordinary care to ensure the security of the collected data, which will inevitably include intimate participant behavioral data. Third, the SBO must serve our research interests, which will inevitably change as collected data is analyzed and interpreted. This short paper summarizes some of our design and implementation benefits and discusses a few hurdles and trade-offs to consider when designing such a data collection system.