A way to check whether calculations have been tampered with could make cloud computing more reliable, and boost privacy.

It is now common for all kinds of data—from personal photos to business documents—to be stored on third-party servers. But despite increased use of outside commodity “cloud computing” equipment, confidence that a third-party service is using your data appropriately is still based more on old-fashioned trust than on technology. As digital break-ins at Twitter and LinkedIn in recent months show, even the biggest services aren’t immune to attack, and this is a big challenge to companies looking to outsource calculations related to sensitive data.

Samsung has made some bold claims about its “5G” technology, but experts await published confirmation.

When Samsung announced two weeks ago that it had prototyped a new wireless technology that could transmit data far faster, many researchers were skeptical because the high-frequency signal is easily blocked and would be hard to work in moving handsets (see “Crazy-Fast Wireless Tested in New York”).

Happy? Sad? A startup called Beyond Verbal has developed technology that can understand how you’re feeling just by listening to your voice.

Yuval Mor might make it possible for your stereo to set the mood automatically, simply by listening to the sound of your voice.

MS Thesis Defense

A Multilayer Framework to Catch Data Exfiltration

Puneet Sharma

10:30am Wednesday, 5 June 2013, 325b ITE, UMBC

Data exfilteration is the unauthorized leakage of confidential data from a particular system. It is a specific form of intrusion that is particularly hard to catch due to the most common cause: an insider entity who is responsible for the leak. That entity could be a person employed in the organization or a malicious hardware component bought from an unreliable third party. Catching such intrusions, therefore, can be extremely difficult. We describe a framework comprising multiple parameters that are constantly monitored in a system. These parameters can cover the entire stack of the computer architecture, from the hardware up to the application layer. Malicious behavior is detected by different modules monitoring these parameters and an aggregated attack alert is produced if multiple modules detect malicious activity within a short period of time. A more distributed and comprehensive monitoring framework should ensure that designing an attack becomes extremely difficult since an attack must go through multiple detectors present in the system without raising any alarms.

Committee: Drs. Anupam Joshi (chair), Tim Finin, Chintan Patel