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Boeing Taps Georgia Tech to Research Cybersecurity in the Military

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Boeing has awarded a School of Computer Science (SCS) team $750,000 for military cybersecurity research. The project, Diversity and Integrity for Cyber Resilience of Legacy Industrial Control, is led by SCS Assistant Professor Taesoo Kim and involves Georgia Tech, Boeing, the Office of Naval Research, and Iowa State University.

Cyberattacks frequently target industrial control and combat systems (ICCS). The safety and success of combat operations depends on these systems being resilient to attack. Past measures safeguarded ICCS from random or physical failures, but cyberattack security is only just being broached.

The Boeing team will work on three solutions to protect ICCS from cyberattacks. These include:

  • Control flow integrity that guarantees information stays on the authorized execution path
     
  • Automated diversity to generate variations of software elements, ensuring they do not have similar vulnerabilities, which sustains the security of the entire system because the attacker has to compromise all variants to succeed
     
  • Performance monitoring unit anomaly detection, using processor hardware to detect anomalies in program execution that were generated by attacks

These tools have been used previously in cybersecurity studies, but haven’t been applied to ICCS until this project. An integration framework will be used to manage how these components interact.

“It aims at transitioning the well-established foundation of security techniques that we have been developing at Georgia Tech into the real-world systems, perhaps eventually the airplane (or drone),” said Kim. “We are so excited about this opportunity.”

Research described in this news release is supported by the Department of Defense/Naval Air Warfare Center, under prime contract award N68335-17-C-0208 issued to The Boeing Company. The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.

 

 

 

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  • Workflow Status:Published
  • Created By:Tess Malone
  • Created:12/15/2017
  • Modified By:Tess Malone
  • Modified:12/18/2017

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