Zobrazeno 1 - 10
of 142
pro vyhledávání: '"Stjepan Picek"'
Publikováno v:
SoftwareX, Vol 27, Iss , Pp 101640- (2024)
Metaheuristics have been shown to be efficient techniques for addressing a wide range of complex optimization problems. Developing flexible, reliable, and efficient frameworks for evolutionary computation metaheuristics is of great importance. With t
Externí odkaz:
https://doaj.org/article/3c883ba203ca431dafa867639183cd01
Publikováno v:
Algorithms, Vol 17, Iss 2, p 67 (2024)
The automated design of dispatching rules (DRs) with genetic programming (GP) has become an important research direction in recent years. One of the most important decisions in applying GP to generate DRs is determining the features of the scheduling
Externí odkaz:
https://doaj.org/article/2394a5d4ef49493daaae143533e686b2
Publikováno v:
IEEE Access, Vol 11, Pp 43511-43519 (2023)
One of the Round 3 Finalists in the NIST post-quantum cryptography call is the Classic McEliece cryptosystem. Although it is one of the most secure cryptosystems, the large size of its public key remains a practical limitation. In this work, we propo
Externí odkaz:
https://doaj.org/article/6a759b55621a4b8a8791ff8c7beaeb26
Publikováno v:
IEEE Access, Vol 11, Pp 284-299 (2023)
The choice of activation functions can significantly impact the performance of neural networks. Due to an ever-increasing number of new activation functions being proposed in the literature, selecting the appropriate activation function becomes even
Externí odkaz:
https://doaj.org/article/7046f84b639944bf888889a4ef864be7
Publikováno v:
SoftwareX, Vol 22, Iss , Pp 101387- (2023)
Outsourced training and crowdsourced datasets lead to a new threat for deep learning models: the backdoor attack. In this attack, the adversary inserts a secret functionality in a model, activated through malicious inputs. Backdoor attacks represent
Externí odkaz:
https://doaj.org/article/31f6c9090b13447fbafcf9f679cc0ac3
Publikováno v:
Transactions on Cryptographic Hardware and Embedded Systems, Vol 2022, Iss 4 (2022)
One of the main promoted advantages of deep learning in profiling sidechannel analysis is the possibility of skipping the feature engineering process. Despite that, most recent publications consider feature selection as the attacked interval from the
Externí odkaz:
https://doaj.org/article/db765d5ec658446cb6fe53c89f8e7124
Publikováno v:
Mathematics, Vol 11, Iss 15, p 3265 (2023)
The deep learning-based side-channel analysis gave some of the most prominent side-channel attacks against protected targets in the past few years. To this end, the research community’s focus has been on creating the following: (1) powerful multila
Externí odkaz:
https://doaj.org/article/b1f9736f4d514e7dbca977ab048707f3
Publikováno v:
Transactions on Cryptographic Hardware and Embedded Systems, Vol 2022, Iss 3 (2022)
In the last decade, machine learning-based side-channel attacks have become a standard option when investigating profiling side-channel attacks. At the same time, the previous state-of-the-art technique, template attack, started losing its importance
Externí odkaz:
https://doaj.org/article/8e535aff0286414c84e7d7d18c08c7d4
Publikováno v:
Algorithms, Vol 16, Iss 3, p 127 (2023)
The adoption of deep neural networks for profiling side-channel attacks opened new perspectives for leakage detection. Recent publications showed that cryptographic implementations featuring different countermeasures could be broken without feature s
Externí odkaz:
https://doaj.org/article/4cdf94a0fbaa48d7b9bfd5457c276b18
Publikováno v:
IEEE Access, Vol 9, Pp 12044-12054 (2021)
The current navigation systems used in many autonomous mobile robotic applications, like unmanned vehicles, are always equipped with various sensors to get accurate navigation results. The key point is to fuse the information from different sensors e
Externí odkaz:
https://doaj.org/article/0af70aeec9eb46ed9aea509f32a6a630