Visible to the public Threat Is in the Air: Machine Learning for Wireless Network Applications

TitleThreat Is in the Air: Machine Learning for Wireless Network Applications
Publication TypeConference Paper
Year of Publication2019
AuthorsPajola, Luca, Pasa, Luca, Conti, Mauro
Conference NameProceedings of the ACM Workshop on Wireless Security and Machine Learning
Date PublishedMay 2019
PublisherAssociation for Computing Machinery
Conference LocationMiami, FL, USA
ISBN Number978-1-4503-6769-1
KeywordsAdversarial Machine Learning, composability, machine learning, privacy, pubcrawl, resilience, Resiliency, security, Wireless network applications

With the spread of wireless application, huge amount of data is generated every day. Thanks to its elasticity, machine learning is becoming a fundamental brick in this field, and many of applications are developed with the use of it and the several techniques that it offers. However, machine learning suffers on different problems and people that use it often are not aware of the possible threats. Often, an adversary tries to exploit these vulnerabilities in order to obtain benefits; because of this, adversarial machine learning is becoming wide studied in the scientific community. In this paper, we show state-of-the-art adversarial techniques and possible countermeasures, with the aim of warning people regarding sensible argument related to the machine learning.

Citation Keypajola_threat_2019