IARPA in the News 2015
IARPA seeking information about combating insider threats in development of new program
The federal government is seeking more information about how it can combat threats from insiders who might engage in espionage, sabotage and violence as it prepares to solicit bids to develop a new program.
A Competition to Anticipate Cyber Attacks
It seems not a week goes by without another report of cyber criminals making off with hordes of stolen data. In early March, Mandarin Oriental International revealed that its credit card system had been compromised, the latest in a line of global companies that have suffered large, costly security breaches.
Worldwide, the British insurance company Lloyd’s estimates cyber attacks cost the private sector $400 billion a year. It is a symptom of our technological age that today’s smartest and most successful thieves steal numbers instead of cold, hard cash. Given the persistent threat, the private sector is working overtime to guard its data, and it is with data that businesses might enjoy a heads up the next time thieves are about to start picking the digital locks.
The Office for Anticipating Surprise, a part of the U.S. Intelligence Advanced Research Projects Activity (IARPA), has kicked off a competition to develop a system for anticipating cyber attacks. This competition is part of IARPA’s Cyber-attack Automated Unconventional Sensor Environment (CAUSE) program, which seeks to predict and prevent attacks rather than just analyze the aftermath, as many current cyber efforts do....
National security among topics slated symposium
UNM’s National Security Studies Program will kick off its annual three-day national security symposium tomorrow....
Topics for the three-day event will include national security, Guantanamo Bay detainees, the Ukrainian crisis and other military, cyber, legal and political global issues, according to a UNM press release.
“This University-wide event will focus on national security, broadly defined—ranging from human rights and privacy to cybersecurity. The speakers will include nationally and UNM recognized scholars and legal experts,” said Emile Nakhleh, a research professor at UNM and a senior adviser to the National Security Studies Program.
Gregory Treverton, chairman of the U.S. National Intelligence Council will discuss global security trends for the next two decades in a keynote speech at the symposium, according the UNM press release.
Peter Highnam, director of intelligence advanced research projects activity in the Office of the Director of National Intelligence, will also present a seminar on “Cutting Edge Research Agenda for National Security,” according to the statement.
IARPA eyes insider threat tech
The intelligence community's research arm wants to meet with researchers and companies to talk about advances in technologies that continuously monitor insider threats.
The Intelligence Advanced Research Projects Activity (IARPA) said it will host a Proposers' Day conference April 16 to discuss its Scientific Advances to Continuous Insider Threat Evaluation (SCITE) program, in anticipation of the release of a new solicitation.
Network Catastrophe: Self-Organized Patterns Reveal both the Instability and the Structure of Complex Networks
Critical events in society or biological systems can be understood as large-scale self-emergent phenomena due to deteriorating stability. We often observe peculiar patterns preceding these events, posing a question of—how to interpret the self-organized patterns to know more about the imminent crisis. We start with a very general description — of interacting population giving rise to large-scale emergent behaviors that constitute critical events. Then we pose a key question: is there a quantifiable relation between the network of interactions and the emergent patterns? Our investigation leads to a fundamental understanding to: 1. Detect the system's transition based on the principal mode of the pattern dynamics; 2. Identify its evolving structure based on the observed patterns. The main finding of this study is that while the pattern is distorted by the network of interactions, its principal mode is invariant to the distortion even when the network constantly evolves. Our analysis on real-world markets show common self-organized behavior near the critical transitions, such as housing market collapse and stock market crashes, thus detection of critical events before they are in full effect is possible.