Professor Naghmeh Karimi received a prestigious NSF CAREER award to support her research on Investigating the impact of device aging on the security of cryptographic chips.
CAREER awards are among NFS’s most prestigious awards and are intended to support early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.
Cryptographic chips implement cryptographic functions in hardware for better performance. Despite the significant performance benefits, cryptographic chips can be compromised by the adversaries via monitoring their power-consumption, tampering their logic or placing the chips under stress to generate erroneous outputs to infer sensitive data. The current protections against such attacks do not consider the aging of the devices that can cause a parametric shift of device parameters over time which can compromise device security.
Supported by this five-year award, Professor Karimi and her students will investigate the effects of device aging on the security of cryptographic devices, particularly those with protection against physical attacks, and develop solutions to ensure security when device aging comes into account. Her work will help enable the development of long-lasting security for trusted hardware platforms, and result in aging-resistant security solutions that benefit the society via devices that remain secure over their lifetime.
This site uses functional cookies and external scripts to improve your experience.
Privacy Settings and Information
This site uses functional cookies and external scripts to improve your experience. Which cookies and scripts are used and how they impact your visit is specified on the left. Your choices will not impact your visit.
NOTE: Third-party Google scripts on this website may have access to cross-site third-party cookies under the google.com domain. We, the CSEE Department, do not access, read, or write these third-party cookies, and as a result, we do not control their presence on your browser. You may block them by using a third-party cookie blocker in your browser.
If you click Accept below to accept the general cookie consent, then a “wpgdprc-consent” cookie will be stored on your browser, to record your general consent.
If you click Accept below to accept the general cookie consent, and also have Google Analytics cookies enabled (on the sidebar to the left), the CSEE Department website will store and access Google Analytics cookies on your browser. We use the data from these cookies to collect information on website usage statistics and improve user experience. If you do not wish to allow Google Analytics cookies on your browser, then either do not click Accept on the bottom bar, or disable Google Analytics on the left.
If you log in to this website, then several Wordpress cookies and session variables will be stored on your browser. Accessing the login screen constitutes your consent to have Wordpress cookies and session variables stored on your computer.
The CSEE Department website makes use of several external scripts to improve user experience. These include, but are not necessarily limited to: Google Calendar, Google Analytics, and ReCAPTCHA. If you choose to use this website, then you agree to allow these scripts to be loaded and executed.
NOTE: These settings will only apply to the browser and device you are currently using.
Enables Google Analytics.
©2023 University of Maryland Baltimore County Computer Science and Electrical Engineering Department
1000 Hilltop Circle, ITE 325, Baltimore, Maryland 21250
College of Engineering and Information Technology
| Contact Us
| Equal Opportunity
| Consumer Information