Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Sara Tehranipoor"'
Publikováno v:
Discover Internet of Things, Vol 1, Iss 1, Pp 1-15 (2021)
Abstract Since the inception of encrypted messages thousands of years ago, mathematicians and scientists have continued to improve encryption algorithms in order to create more secure means of communication. These improvements came by means of more c
Externí odkaz:
https://doaj.org/article/32ca20a6dc714bd79581b4a14a8acc6c
Publikováno v:
IEEE Access, Vol 9, Pp 136448-136458 (2021)
The appearance of deep neural networks for Side-Channel leads to strong power analysis techniques for detecting secret information of physical cryptography implementations. Generally, deep learning techniques do not suffer the difficulties of templat
Externí odkaz:
https://doaj.org/article/e6e7f73a39d747908ef49d2f3abdecfb
Autor:
Michael Yue, Sara Tehranipoor
Publikováno v:
Sensors, Vol 21, Iss 23, p 8126 (2021)
Integrated circuit (IC) piracy and overproduction are serious issues that threaten the security and integrity of a system. Logic locking is a type of hardware obfuscation technique where additional key gates are inserted into the circuit. Only the co
Externí odkaz:
https://doaj.org/article/5a6493c8fda14d85a59d8e010c476bc0
Autor:
Hossein Sayadi, Mehrdad Aliasgari, Furkan Aydin, Seetal Potluri, Aydin Aysu, Jack Edmonds, Sara Tehranipoor
Publikováno v:
2022 IEEE 28th International Symposium on On-Line Testing and Robust System Design (IOLTS).
Publikováno v:
IEEE Access, Vol 9, Pp 136448-136458 (2021)
The appearance of deep neural networks for Side-Channel leads to strong power analysis techniques for detecting secret information of physical cryptography implementations. Generally, deep learning techniques do not suffer the difficulties of templat
Publikováno v:
2021 IEEE International Symposium on Technologies for Homeland Security (HST).
Publikováno v:
ISQED
In a recent line of works, several masking and unmasking AES design have been proposed to secure hardware implementations against power-analysis techniques. Although Machine-learning profiling techniques have been successful in security testing durin