Research project

Research in the lab is focused on cognitive radio and dynamic spectrum access networks, wireless security, text mining, social networks, and mage/video steganography and steganalysis

SpiderRadio Wireless Research

 

IP Geolocation:

Planet lab measurement data for IP geolocation: <http://www.ece.stevens-tech.edu/~mouli/ipgeodata.tar.gz> used in "Network measurement based modeling and optimization for IP geolocation" and "Estimation of missing RTTs in computer networks: Matrix completion vs compressed sensing".

Video Stegagnography and Steganalysis: YouTube Stego


 
YouTube has become a very important social phenomenon by functioning as a popular portal for video content. It has become ubiquitous and the medium of choice for disseminating user generated video content. Because of its wide popularity, it is important to ask if this medium can be used to communicate secret messages to a wide audience around the globe. We ask and answer the question: is it possible to convey hidden message though this medium. Considering that the videos uploaded to YouTube undergo format conversion as well as compression and that the embedder has no control over or knowledge of the parameters involved in the process, this is a tough challenge.
SpiderRadio Cognitive Network: Dynamic Spectrum Access Network Prototype


 
With recent proliferation in wireless services and increase in the number of end-users, wireless industry is fast moving toward a new wireless networking model where wireless service providers are finding it difficult to satisfy users and increase revenue with just the spectrum statically allocated. Spectrum usage being both space and time dependent, a static allocation often leads to low spectrum utilization and "artificial scarcity" of spectrum. This results in significant amount of "white space" (unused band) available in several spectral bands that could be exploited by both licensed and unlicensed services.
Twitter is growing into a major social networking platform. Currently, there are several million Twitter users generating huge amounts of text data every minute. Therefore, developing tools to sample Twitter data, analyzing the collected data and drawing conclusions are major challenges.

Text Analystics: detecting deception from text information


 
Deception is falsification of information. Detecting deception from text is a challenging problem. Deceptive text content, for example, may be found in social networking sites, emails scams, email phishing, blogs, chat rooms, etc. Our approach uses a combination of psychology, linguistics and statistical analysis to detect deception. Try it! We do not capture any personal information. The text your enter will be stored for further research.