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World’s Largest Unclassified SPIE Conference: Spying & Surveillance Tech

Apr 30, 20126 mins
Data and Information SecurityEnterprise ApplicationsMicrosoft

SPIE hosted the world's largest unclassified conference for spying, defense, homeland security and surveillance technology. Many presentations in the Cyber Sensing track focused on surveillance of social media. From to drones with an electronic nose to sniff out targets to datamining social media for situational awareness, here's an overview of cutting edge and emerging security technology talks that caught my privacy-focused eye.

The world’s largest unclassified conference for spying, defense, homeland security and surveillance technology was held at the Baltimore Convention Center last week. SPIE, the international society for optics and photonics, hosted the week-long Defense, Security and Sensing conference and exhibition featuring “research from top tier institutions, and premiere new technology solutions.” Over 6,700 people attended the 2,450 presentations, 540 exhibitors and various courses [PDF] of emerging technologies “for intelligence, surveillance, reconnaissance, and situational awareness.” One such track was Cyber Sensing 2012. This track included numerous interesting talks, several of which focused on surveillance of social media. 

Think before you tweet? Trust and microblogging: a proposed framework for assessing trust in Twitter introduced “a model by which to base future automation of trust assessment.” The government says you have no right to anonymous speech on Twitter and it was recently decided that your tweets can be used against you in a court of law. But what if you are having a bad day, can the emotion behind your tweet also be data-mined and potentially stored away to be used against you? According to the abstract of Anomaly detection for internet surveillance:

Many threats in the real world can be related to activity of persons on the internet. Internet surveillance aims to predict and prevent attacks and to assist in finding suspects based on information from the web. However, the amount of data on the internet rapidly increases and it is time consuming for humans to monitor many websites. In this paper, we present a novel method to automatically monitor trends and find anomalies on the internet. The system was tested on Twitter data. The results showed that it can successfully recognize abnormal changes in activity or emotion.

Consider this Cyber Sensing presentation as a potential canary in a coal mine warning. According to Coalmine: an experience in building a system for social media analytics:

Social media networks make up a large percentage of the content available on the Internet and most of the time users spend online today is in interacting with them. All of the seemingly small pieces of information added by billions of people result in a enormous rapidly changing dataset. Searching, correlating, and understanding billions of individual posts is a significant technical problem; even the data from a single site such as Twitter can be difficult to manage. In this paper, we present Coalmine a social network data-mining system.

Meme hunters? How memes affect cybersecurity, defense, or homeland security I’m not sure but tracking memes was also presented at SPIE Cyber Sensing 2012. According to the abstract for Tracking fine-grained topics in microblogs:

A critical component of technical microblog research is identifying units of information (termed “memes”) as they propagate through the microblog space. Heretofore, most research has avoided answering the general solution to this problem in favor of simple solutions that can only detect a small subset of these memes, and extract only a subset of messages relevant to the detected memes. In this paper, we introduce a methodology of tracking messages relating to a meme that addresses the key challenges, and present empirical results from real microblog data.

Cyberspace is the “new battlefield,” so “Operational advantages of using cyber electronic warfare in the battlefield” focused on the feasibility of integrating cyber warfare logic into conventional electronic warfare measures. Cyber Electronic Warfare operational advantages included effecting “adversary air defense systems, communication networks and information systems.”

Previously I wrote about drones coming to police stations near you soon, so a drone with an e-nose to sniff out the target practically jumped out at me: Bio-inspired visual and olfactory receptor system for elusive target detection. According to the abstract, the paper presented:

an integration technique for bio-inspired visual and olfactory receptor systems to search for elusive targets in various environments where the targets cannot be seen obviously by either sensory data. Bio-inspired visual system is based on a modeling of extended visual pathway which consists of saccadic eye movements and visual pathway (vertebrate retina, lateral geniculate nucleus and visual cortex) to enable powerful target detections of noisy, partial, and incomplete visual data. Olfactory receptor algorithm, namely spatial invariant independent component analysis, that was developed based on data of olfactory receptors — electronic nose (e-nose) of Caltech, is adopted to enable the odorant target detection in an unknown environment. The integration of two systems is a vital approach and establishes a corner stone for effective and low cost development of miniaturized UAVs or fly robots for future DOD and NASA missions.

Other courses, presentations and exhibits featuring cutting edge and emerging technology that caught my eye included a talk from the Evolutionary and Bio-inspired Computation track. The abstract for “Multi-attributed network discovery: learning suspicious patterns in social network data” states, “As more sensors enter the field, the growing quantity of data promises to enable faster detection of suspects and targets.” This presentation described “the problem of identifying suspects within large networks of individuals, places, and events, and present a range of solutions for the automated detection and discovery of suspicious patterns within networks containing millions of nodes.”

Mobile Multimedia/Image Processing, Security, and Applications 2012 was another track. “Surveillance systems become powerful” and the “processing of personal related and sensitive information threatens privacy.” The talk “Privacy-aware access control for video data in intelligent surveillance systems” proposed “an architecture for Instance Oriented Access Control that enforces the separation of data between different surveillance tasks and access to raw video.”

Several presentations were cancelled but still looked intriguing such as was “Web-based geospatial information extraction” and “Locating and tracking of explosive threats using wireless sensors and networks.” The latter by Missouri University of Science and Technology was supposed to report on “15 projects bundled in a cooperative agreement program to research, develop and transition technologies critical in thrust areas: human system integration, chemical/biological sensors and detection, RF detection and localization, embedded systems and networking, and security.”

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ms smith

Ms. Smith (not her real name) is a freelance writer and programmer with a special and somewhat personal interest in IT privacy and security issues. She focuses on the unique challenges of maintaining privacy and security, both for individuals and enterprises. She has worked as a journalist and has also penned many technical papers and guides covering various technologies. Smith is herself a self-described privacy and security freak.