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pro vyhledávání: '"Shafiq, M. Omair"'
The need for robust, secure and private machine learning is an important goal for realizing the full potential of the Internet of Things (IoT). Federated learning has proven to help protect against privacy violations and information leakage. However,
Externí odkaz:
http://arxiv.org/abs/2101.03218
The proliferation of smart, connected, always listening devices have introduced significant privacy risks to users in a smart home environment. Beyond the notable risk of eavesdropping, intruders can adopt machine learning techniques to infer sensiti
Externí odkaz:
http://arxiv.org/abs/2011.06725
Machine learning models have made many decision support systems to be faster, more accurate, and more efficient. However, applications of machine learning in network security face a more disproportionate threat of active adversarial attacks compared
Externí odkaz:
http://arxiv.org/abs/1911.02621
Publikováno v:
In Machine Learning with Applications 15 December 2022 10
Autor:
Ibrahim, Rami, Shafiq, M. Omair
Publikováno v:
In Knowledge-Based Systems 27 September 2022 252
A modified attention mechanism powered by Bayesian Network for user activity analysis and prediction
Publikováno v:
In Data & Knowledge Engineering July 2022 140
Autor:
Obasi, ThankGod, Shafiq, M. Omair
Publikováno v:
In Computer Communications 1 June 2022 190:110-125
Publikováno v:
In Computers & Security May 2022 116
Autor:
IBRAHIM, RAMI1 ramif.ibrahim@carleton.ca, SHAFIQ, M. OMAIR1 omair.shafiq@carleton.ca
Publikováno v:
ACM Computing Surveys. Oct2023, Vol. 55 Issue 10, p1-37. 37p.
Akademický článek
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