Our world is instrumented with countless sensors. While many are outside of our direct control, there is an incredible amount of publicly available information being generated and gathered all the time. While much of this data goes by unnoticed or ignored it contains fascinating insight into the behavior and trends that we see throughout society. The trick is being able to identify and isolate the useful patterns in this data and separate it from all the noise.
Previously, we looked at using sites such as Craigslist to provide a wealth of wonderfully categorized information and then used that to answer questions such as "What job categories are trending upward?", "What cities show the most (or the least) promise for technology careers?", and "What relationship is there between the number of bikes for sale and the number of prostitution ads?" After achieving initial success looking at a single source of data, the challenge becomes to generate more meaningful results by combining separate data sources that each views the world in a different way. Now we look across multiple, disparate sources of such data and attempt to build models based on the trends and relationships found therein.
The initial inspiration for this work was a fantastic talk at DC13, "Meme Mining for Fun and Profit". It also builds upon a similar talk I presented at DC18. And once again seeks to inspire others to explore the exploitation of such publicly available sensor systems.
Daniel Burroughs first became interested in computer security shortly after getting a 300 baud modem to connect his C64 to the outside world. After getting kicked off his favorite BBS for "accidently" breaking into it, he decided that he needed to get smarter about such things. Since that time he has moved on to bigger and (somewhat) better things. These have included work in virtual reality systems at the Institute for Simulation and Training at the University of Central Florida, high speed hardware motion control software for laser engraving systems, parallel and distributed simulation research at Dartmouth College, distributed intrusion detection and analysis at the Institute for Security Technology Studies, and the development of a state-wide data sharing system for law enforcement agencies in Florida. Daniel was an associate professor of engineering at the University of Central Florida for 10 years prior to his current position as the Associate Technology Director for the Center for Law Enforcement Technology, Training, & Research. He also is a co-founder of Hoverfly Technologies, an aerial robotics company, and serves on the board of directors for Familab – a hackerspace located in Orlando. He is also the proud owner of two DefCon leather jackets won at Hacker Jeopardy at DEF CON 8 & 9 (as well as few hangovers from trying to win more).