The threat of offensive ai to organizations

Y Mirsky, A Demontis, J Kotak, R Shankar, D Gelei… - Computers & …, 2023 - Elsevier
AI has provided us with the ability to automate tasks, extract information from vast amounts of
data, and synthesize media that is nearly indistinguishable from the real thing. However …

Machine learning strategies for time series forecasting

G Bontempi, S Ben Taieb, YA Le Borgne - … 15-21, 2012, Tutorial Lectures 2, 2013 - Springer
The increasing availability of large amounts of historical data and the need of performing
accurate forecasting of future behavior in several scientific and applied domains demands …

A machine learning approach against a masked AES: Reaching the limit of side-channel attacks with a learning model

L Lerman, G Bontempi, O Markowitch - Journal of Cryptographic …, 2015 - Springer
Side-channel attacks challenge the security of cryptographic devices. A widespread
countermeasure against these attacks is the masking approach. Masking combines …

X-DeepSCA: Cross-device deep learning side channel attack

D Das, A Golder, J Danial, S Ghosh… - Proceedings of the 56th …, 2019 - dl.acm.org
This article, for the first time, demonstrates Cross-device Deep Learning Side-Channel
Attack (X-DeepSCA), achieving an accuracy of> 99.9%, even in presence of significantly …

Neural network based attack on a masked implementation of AES

R Gilmore, N Hanley, M O'Neill - 2015 IEEE International …, 2015 - ieeexplore.ieee.org
Masked implementations of cryptographic algorithms are often used in commercial
embedded cryptographic devices to increase their resistance to side channel attacks. In this …

Applications of machine learning techniques in side-channel attacks: a survey

B Hettwer, S Gehrer, T Güneysu - Journal of Cryptographic Engineering, 2020 - Springer
With increasing expansion of the Internet of Things, embedded devices equipped with
cryptographic modules become an important factor to protect sensitive data. Even though …

Machine learning for hardware security: Opportunities and risks

R Elnaggar, K Chakrabarty - Journal of Electronic Testing, 2018 - Springer
Recently, machine learning algorithms have been utilized by system defenders and
attackers to secure and attack hardware, respectively. In this work, we investigate the impact …

Practical approaches toward deep-learning-based cross-device power side-channel attack

A Golder, D Das, J Danial, S Ghosh… - … Transactions on Very …, 2019 - ieeexplore.ieee.org
Power side-channel analysis (SCA) has been of immense interest to most embedded
designers to evaluate the physical security of the system. This work presents profiling-based …

Profiled side-channel analysis in the efficient attacker framework

S Picek, A Heuser, G Perin, S Guilley - International Conference on Smart …, 2021 - Springer
Profiled side-channel attacks represent the most powerful category of side-channel attacks.
There, the attacker has access to a clone device to profile its leaking behavior. Additionally …

Profiling power analysis attack based on multi-layer perceptron network

Z Martinasek, L Malina, K Trasy - Computational Problems in Science and …, 2015 - Springer
In 2013, an innovative method of power analysis was presented in Martinasek and Zeman
(Radioengineering 22 (2), IF 0.687, 2013) and Martinasek et al.(Smart Card Research and …