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Found 4 papers, 1 papers with code
Fast & Furious: Modelling Malware Detection as Evolving Data Streams
This constant evolution of malware samples causes changes to the data distribution (i. e., concept drifts) that directly affect ML model detection rates, something not considered in the majority of the literature work.
Online Binary Models are Promising for Distinguishing Temporally Consistent Computer Usage Profiles
This paper investigates whether computer usage profiles comprised of process-, network-, mouse-, and keystroke-related events are unique and consistent over time in a naturalistic setting, discussing challenges and opportunities of using such profiles in applications of continuous authentication.
People Still Care About Facts: Twitter Users Engage More with Factual Discourse than Misinformation--A Comparison Between COVID and General Narratives on Twitter
We found that (i) factual tweets, regardless of whether COVID-related, were more engaging than misinformation tweets; and (ii) features that most heavily correlated with engagement varied depending on the veracity and content of the tweet.
Machine Learning (In) Security: A Stream of Problems
Machine Learning (ML) has been widely applied to cybersecurity and is considered state-of-the-art for solving many of the open issues in that field.
