Surpriv: RFID Surveillance and Privacy

Research firm BIGresearch and Artafact LLC have “launched a new qualitative/quantitative syndicated report to track consumer awareness, attitudes and opinions about the wave of RFID applications hitting the market from Texas Instruments, VeriChip maker Applied Digital, IBM and others.”

From their press release:

The second wave of the this new study of over 8,500 adults will explore the impact the recent publicity around new RFID applications has had on awareness of RFID and consumer attitudes and opinions about it. The study will also look at the sources of information consumers use to get and stay informed about RFID. Has this recent publicity fueled or abated consumers concern for privacy?

From the first wave of the study fielded in September 2004, 72% of the respondents had never heard of RFID and had no idea what it was. Those that were aware (28%) had educated themselves via the Internet versus hearing about it from traditional mass media like television, radio and print. Over 8,000 consumers participated in the September survey.

CNET eventually (the grant, for “Surveillance, Analysis and Modeling of Chatroom Communities,” was made in September) gets around to noting that the NSF and CIA have jointly funded research on surveillance of online chatrooms.

As a CIA alum, I think it’s laudable that the CIA and NSF might be collaborating on some research, so long as it adheres to the NSF’s policies regarding open academic publication. Cross-fertilization between the Intelligence Community and the “outside world” ought to be encouraged, to fight a tendency to believe that the problems the former encounters are unique to it.

There is a fair amount of research funded by the IC directly, e.g., through ARDA, with the DOD through DARPA, or through In-Q-Tel, the CIA-sponsored venture capital organization.

Agnik, LLC, in Columbia, MD, was recently awarded two SBIRs, from DHS and the NSF, to study privacy and datamining. The NSF SBIR:

This Small Business Innovation Research (SBIR) Phase I research project will develop a collection of privacy sensitive distributed data mining algorithms for immediate applications in domains that deal with sensitive private data. Privacy is becoming a growing concern in many data monitoring and mining applications such as network intrusion detection, fraud detection, and counter-terrorism intelligence gathering among others. However, to date, there does not exist any commercial data mining system that is capable of analyzing potentially distributed multi-party data in a privacy-sensitive manner. This research will develop technology to meet this immediate need. It will develop data mining algorithms that can work without direct access to the original sensitive data. The research will particularly focus on privacy-preserving statistical computing and clustering techniques that are particularly suitable for security-related threat management applications. The algorithmic approach is based on a combination of random projection and secured multi-party computation-based techniques. Deliverables will include a collection of privacy-sensitive algorithms and a documentation of their performance along with a demonstration.

A successful completion of this project will open up many new possibilities particularly in the domain of security and threat management for counter-terrorism which are not possible today because of due concerns about the privacy of the common citizens. Privacy-preserving data mining has numerous potential applications, with enormous potential benefit for security and economic efficiency. It also has the great virtue of offering transparency to providers of information, allowing them to understand and control the revelation of sensitive features.