Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Tomáš Pevný"'
Publikováno v:
Fusion Science and Technology
Chirping Alfven eigenmodes were observed at the COMPASS tokamak. They are believed to be driven by runaway electrons (REs), and as such, they provide a unique opportunity to study the physics of no...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f5cbc844d19fd7dfcb60415e5941a2f
https://doi.org/10.1080/15361055.2020.1820805
https://doi.org/10.1080/15361055.2020.1820805
Publikováno v:
Plasma Physics and Controlled Fusion. 64:125004
Correct and timely detection of plasma confinement regimes and edge localized modes (ELMs) is important for improving the operation of tokamaks. Existing machine learning approaches detect these regimes as a form of post-processing of experimental da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::39c1d6f2637cef7a640ccdb831bdfcab
https://doi.org/10.1088/1361-6587/ac9926
https://doi.org/10.1088/1361-6587/ac9926
Publikováno v:
AAAI
Scopus-Elsevier
Scopus-Elsevier
We study a classification problem where each feature can be acquired for a cost and the goal is to optimize a trade-off between the expected classification error and the feature cost. We revisit a former approach that has framed the problem as a sequ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b4ea3446cb6fdb940a84442e8e25aad
https://doi.org/10.1609/aaai.v33i01.33013959
https://doi.org/10.1609/aaai.v33i01.33013959
Publikováno v:
Computers & Security. 74:221-239
We propose a method to automatically group unknown binaries executed in sandbox according to their interaction with system resources (files on the filesystem, mutexes, registry keys, network communication with remote servers and error messages genera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d8a142c212c67a10ed630011ce4a90f7
https://doi.org/10.1016/j.cose.2018.01.012
https://doi.org/10.1016/j.cose.2018.01.012
Publikováno v:
Journal of Computer and System Sciences. 83:43-57
Network intrusion detection systems based on the anomaly detection paradigm have high false alarm rate making them difficult to use. To address this weakness, we propose to smooth the outputs of anomaly detectors by online Local Adaptive Multivariate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d66f554d56ef6b3ed844d33b6ccf797b
https://doi.org/10.1016/j.jcss.2016.03.007
https://doi.org/10.1016/j.jcss.2016.03.007
Publikováno v:
IH-MMSec
IH-MMSec, Jul 2019, Paris, France. ⟨10.1145/3335203.3335737⟩
IH&MMSec
IH-MMSec, Jul 2019, Paris, France. ⟨10.1145/3335203.3335737⟩
IH&MMSec
International audience; This work proposes a protocol to iteratively build a distortion function for adaptive steganography while increasing its practical security after each iteration. It relies on prior art on targeted attacks and iterative design
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea8b6d8258cb0f29765e54afde637a3b
https://hal.archives-ouvertes.fr/hal-02177259/file/main_final_HAL.pdf
https://hal.archives-ouvertes.fr/hal-02177259/file/main_final_HAL.pdf
Autor:
Martin Grill, Tomáš Pevný
Publikováno v:
Computer Networks. 107:55-63
This paper presents a novel technique of finding a convex combination of outputs of anomaly detectors maximizing the accuracy in ź-quantile of most anomalous samples. Such an approach better reflects the needs in the security domain in which subsequ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e1699150ece2f40313802b98bb144f1
https://doi.org/10.1016/j.comnet.2016.05.021
https://doi.org/10.1016/j.comnet.2016.05.021
Autor:
Tomáš Pevný
Publikováno v:
Machine Learning. 102:275-304
In supervised learning it has been shown that a collection of weak classifiers can result in a strong classifier with error rates similar to those of more sophisticated methods. In unsupervised learning, namely in anomaly detection such a paradigm ha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::590716b2c7af2d9c1a985830c7928472
https://doi.org/10.1007/s10994-015-5521-0
https://doi.org/10.1007/s10994-015-5521-0
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783319712451
ECML/PKDD (2)
ECML/PKDD (2)
We study the problem of detecting malware on client computers based on the analysis of HTTPS traffic. Here, malware has to be detected based on the host address, timestamps, and data volume information of the computer’s network traffic. We develop
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a71e307864204139f1042c0ae57e8afc
https://doi.org/10.1007/978-3-319-71246-8_5
https://doi.org/10.1007/978-3-319-71246-8_5
Publikováno v:
Similarity Search and Applications ISBN: 9783319684734
SISAP
SISAP
We present a demo of behaviour-based similarity retrieval in network traffic data. The underlying framework is intended to support domain experts searching for network nodes (computers) infected by malicious software, especially in cases when single
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b787f71dd36bac2ae5acb21ca0bb959
https://doi.org/10.1007/978-3-319-68474-1_22
https://doi.org/10.1007/978-3-319-68474-1_22