Make Some Noise. Unleashing the Power of Convolutional Neural Networks for Profiled Side-channel Analysis

Autor: Jaehun Kim, Stjepan Picek, Annelie Heuser, Shivam Bhasin, Alan Hanjalic

Publikováno v: Transactions on Cryptographic Hardware and Embedded Systems, Vol 2019, Iss 3 (2019)

Profiled side-channel analysis based on deep learning, and more precisely Convolutional Neural Networks, is a paradigm showing significant potential. The results, although scarce for now, suggest that such techniques are even able to break cryptograp

Externí odkaz: https://doaj.org/article/cbc4a11c56534e53bbfb66676aee867f

Traditional Machine Learning Methods for Side-Channel Analysis

Autor: Alan Jovic, Dirmanto Jap, Louiza Papachristodoulou, Annelie Heuser

Publikováno v: Security and Artificial Intelligence ISBN: 9783030987947

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c482df8bbb85e3c3cbf89099754b5f80
https://doi.org/10.1007/978-3-030-98795-4_2

Obfuscation Revealed: Leveraging Electromagnetic Signals for Obfuscated Malware Classification

Autor: Duy-Phuc Pham, Damien Marion, Matthieu Mastio, Annelie Heuser

Publikováno v: ACSAC 2021-Annual Computer Security Applications Conference
ACSAC 2021-Annual Computer Security Applications Conference, Dec 2021, Virtual Event, France. pp.1-14, ⟨10.1145/3485832.3485894⟩

International audience; The Internet of Things (IoT) is constituted of devices that are exponentially growing in number and in complexity. They use numerous customized firmware and hardware, without taking into consideration security issues, which ma

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77e573fb6aed75ef153a4138092dbaa9
https://hal.archives-ouvertes.fr/hal-03374399/document

Train or Adapt a Deeply Learned Profile?

Autor: Christophe Genevey-Metat, Annelie Heuser, Benoît Gérard

Publikováno v: LATINCRYPT 2021-7th International Conference on Cryptology and Information Security in Latin America
LATINCRYPT 2021-7th International Conference on Cryptology and Information Security in Latin America, Oct 2021, Bogota, Colombia. ⟨10.1007/978-3-030-88238-9_11⟩
Progress in Cryptology – LATINCRYPT 2021 ISBN: 9783030882372
LATINCRYPT

International audience; In recent years, many papers have shown that deep learning can be beneficial for profiled side-channel analysis. However, to obtain good performance with deep learning, an evaluator or an attacker face the issue of data. Due t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8f379d3305d7003abef361eae1a752f
https://hal.inria.fr/hal-03458681

Accurate and Robust Malware Analysis through Similarity of External Calls Dependency Graphs (ECDG)

Autor: Lamine Noureddine, Annelie Heuser, Olivier Zendra, Cassius Puodzius

Publikováno v: IWCC 2021-10th International Workshop on Cyber Crime (held in conjunction with ARES 2021)
ARES 2021-The 16th International Conference on Availability, Reliability and Security
ARES 2021-The 16th International Conference on Availability, Reliability and Security, Aug 2021, Virtual, Austria. pp.1-12, ⟨10.1145/3465481.3470115⟩
ARES

This paper received the Best Paper Award for IWCC 2021; International audience; Malware is a primary concern in cybersecurity, being one of the attacker's favorite cyberweapons. Over time, malware evolves not only in complexity but also in diversity

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7820e0ee967de2aa9c8e6a1bb141af0c
https://hal.science/hal-03328395