Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Alesia Chernikova"'
Publikováno v:
Applied Network Science, Vol 8, Iss 1, Pp 1-43 (2023)
Abstract Self-propagating malware (SPM) is responsible for large financial losses and major data breaches with devastating social impacts that cannot be understated. Well-known campaigns such as WannaCry and Colonial Pipeline have been able to propag
Externí odkaz:
https://doaj.org/article/e88104c4a9624d8eb27711fcb00459a7
Autor:
Alesia Chernikova, Nicolò Gozzi, Simona Boboila, Priyanka Angadi, John Loughner, Matthew Wilden, Nicola Perra, Tina Eliassi-Rad, Alina Oprea
Publikováno v:
Computer Security – ESORICS 2022 ISBN: 9783031171390
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e253e24d797cf2e9900c521e333a6ed1
https://doi.org/10.1007/978-3-031-17140-6_26
https://doi.org/10.1007/978-3-031-17140-6_26
Publikováno v:
IEEE Symposium on Security and Privacy Workshops
Deep Neural Networks (DNNs) have tremendous potential in advancing the vision for self-driving cars. However, the security of DNN models in this context leads to major safety implications and needs to be better understood. We consider the case study
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f4b52fc7af106d39fa145d5a265e4c78
https://doi.org/10.1109/spw.2019.00033
https://doi.org/10.1109/spw.2019.00033
Autor:
Alesia Chernikova, Alina Oprea
As advances in Deep Neural Networks (DNNs) demonstrate unprecedented levels of performance in many critical applications, their vulnerability to attacks is still an open question. We consider evasion attacks at testing time against Deep Learning in c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61bb9b6ae2afc072ba5256cc0d7e454c