Sept. 18, 2023, 1:10 a.m. | Lachlan Simpson, Kyle Millar, Adriel Cheng, Hong Gunn Chew, Cheng-Chew Lim

cs.CR updates on arXiv.org arxiv.org

The need for improved network situational awareness has been highlighted by
the growing complexity and severity of cyber-attacks. Mobile phones pose a
significant risk to network situational awareness due to their dynamic
behaviour and lack of visibility on a network. Machine learning techniques
enhance situational awareness by providing administrators insight into the
devices and activities which form their network. Developing machine learning
techniques for situational awareness requires a testbed to generate and label
network traffic. Current testbeds, however, are unable …

a network applications attacks awareness complexity cyber devices dynamic machine machine learning mobile mobile devices mobile phones network phones risk severity techniques visibility

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