| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | July 23, 2011 |
| Latest Amendment Date: | May 6, 2013 |
| Award Number: | 1115839 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Deborah Shands
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | August 1, 2011 |
| End Date: | July 31, 2015 (Estimated) |
| Total Intended Award Amount: | $429,558.00 |
| Total Awarded Amount to Date: | $437,558.00 |
| Funds Obligated to Date: |
FY 2013 = $8,000.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
300 TURNER ST NW BLACKSBURG VA US 24060-3359 (540)231-5281 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
300 TURNER ST NW BLACKSBURG VA US 24060-3359 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
Special Projects - CNS, TRUSTWORTHY COMPUTING |
| Primary Program Source: |
01001112DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
This project develops new and promising techniques in the area of side-channel attacks and their corresponding countermeasures. In a side-channel attack, an attacker captures the implementation effects of cryptography, such as power consumption and execution time. A distinctive feature of a side-channel analysis (SCA) attack is that it can reveal a small part of the secret-key. Hence, side-channel attacks avoid the brute-force complexity of cryptanalysis. Using novel side-channel estimation techniques based on Bayesian statistics, the project develops more powerful side-channel attacks. The development of novel side-channel analysis techniques is crucial in order to obtain the best possible countermeasures. The project also develops novel software-oriented countermeasures that more flexible and general than traditional hardware-oriented side-channel countermeasures. The efficiency of side-channel attacks and side-channel countermeasures are evaluated using hardware and software prototyping. The project combines advanced statistical techniques with advanced computer engineering, building synergy between Statistics and Computer Engineering. In the field of Statistics, the Bayesian matching technique can be used for variable selection, a technique that is applicable to related problems in biostatistics, machine learning, data mining, genomics, and other areas with high dimensional data. Project results will be disseminated by distributing open-source prototype implementations, measurement data, and in open publications. A formal training program within the Laboratory for Interdisciplinary Statistical Analysis (LISA) at Virginia Tech is developed to distribute the results of this project to students.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
A secure embedded system is a small integrated computer that makes part of an electronically operated system. Secure embedded systems can be found, for example, in electronic door locks, in ATM machines, or in high-safety industrial control networks. Secure embedded systems provide information security and encryption technologies such that sensitive data, such as door lock combinations, can be safely transmitted without the risk of being eavesdropped or hacked.
However, secure embedded systems are subject to tampering by adversaries, and side-channel attacks present a recent yet serious threat to the integrity of the operation of such systems. In a side-channel attack, an adversary resides in proximity of the secure embedded system, and captures its power dissipationor electromagnetic radiation. This side-channel leakage contains informationcorrelated to the internal secret used by the embedded system. The objective of the side-channel attack is to extract this secret.
In this project, a statistician (PI) and a computer engineer (co-PI) colaborated to design novel techniques for side-channel analysis, with the objective of developing better, stronger countermeasures. The project, run over three years, involved 6 students and produced 17 scientific, peer-reviewed publications. The project produced several useful and constructive techniques in the field of side-channel analysis.
One result included a technique to program a cryptographic algorithm into an embedded system in a manner that it does not produce harmful side-channel leakage. The technique is useful because it can be applied to any existing embedded system, and because it does not require the construction of new, specialized hardware - which would be expensive. Another result is a compiler technique that a software programmer would use to test if a given embedded program is free from side-channel leakage or not. This technique is quite useful because it can be applied by software designers who are non-experts in side-channel analysis.
Finally, this project lead to novel insights into the behavior of side-channel leakage in secure embedded system. One of the ongoing efforts is to investigate the application of side-channel leakage countermeasure techniques into techniques that apply to the construction of better, more secure microprocessors.
Last Modified: 08/27/2015
Modified by: Patrick Schaumont
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