Cyber Security for Energy Assets

Rattikorn Hewett
Thursday, October 8, 2015 - 3:40pm
Hach Hall Atrium
Event Type: 

Cyber Security for Energy Assets

Date/Time: October 8, 3:40 pm
Location: Hach Hall Atrium


Cyber threats to energy delivery systems can impact public safety, national security and economy. Because most early system designs did not anticipate the security threats posed by advances in computers and communication networks, and the Internet, the energy sector is faced with an unprecedented challenge in protecting systems against cyber threats. This talk will describe our recent work to address this challenge including our experience with the Intel/McAfee’s Security Fabric Technology, which has been implemented for a Synchrophaser network in a smart grid and tested on a scaled wind farm technology facility at Texas Tech University, as part of the Department of Energy demonstration project. The aim is to enhance security endpoints of legacy systems. Unfortunately, networks are among the most common means of cyber attacks, as they are unavoidably vulnerable.  As long as they are in service, attackers can exploit their vulnerabilities(i.e., errors in service software and configurations). This talk will then discuss a principled and practical approach to automated network security modeling and intelligent analysis by using knowledge about network vulnerabilities that can be detected by commercial scanners. The models represent possible attacks in terms of chains of vulnerability exploits. Because the number of network states can grow exponentially in the size of the network, the problem of how to automatically and efficiently generating the models is crucial and challenging for security network modeling. Furthermore, in practice, the resulting models are likely to be huge and therefore the problem of how to analyze the attack models effectively and efficiently is necessary. These are the two fundamental problems addressed in this talk along with our proposed solutions.


Rattikorn Hewett is currently a Professor and Chair of the department of Computer Science at Texas Tech University.  Hewett has a Ph.d. in Computer Science from Iowa State University, an M.Eng. Sc. in Computer Science from the University of New South Wales, and a B.A. Honors degree in Pure Mathematics and Statistics from Flinders University, Australia. After her Ph.D. research informal language theories under the supervision of Professsor Slutski,she was a postdoctoral fellow at Stanford University where she started her Artificial Intelligence (AI) research.  Hewett was a recipient of an NSF Research Initiation Award, and a two times winner of the scholarships from the Australian government. Her applied research in AI covers four areas:  Cyber security (network security, access control, vulnerability risk analysis, software security, and Internet crimes), Data Science (machine learning, social network analysis, Big data analytics and bioinformatics),Automated Software/System Engineering (large-scale software testing/design, web services and cyber-physical systems), and Intelligent controls & reasoning (model-based reasoning, blackboard control architectures, real-time monitoring and diagnosis). NSF, DARPA, DOE, EPRI, Florida State, Texas State, Boeing and IBM were among sponsors of these projects.  She has published over 100 peer-reviewed technical articles and has served on several journal editorial boards, and numerous conference program committees.

Colloquia Lecture Rattikorn Hewett.pdf