Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/90979
Title: SpotCheck : on-device anomaly detection for Android
Authors: Vella, Mark Joseph
Colombo, Christian
Keywords: Software engineering
Malware (Computer software)
Mobile computing
Computer software -- Security measures
Intrusion detection systems (Computer security)
Issue Date: 2020
Publisher: Association for Computing Machinery
Citation: Vella, M., & Colombo, C. (2020). SpotCheck : on-device anomaly detection for Android. SIN 2020: 13th International Conference on Security of Information and Networks, Istanbul.
Abstract: many security sensitive operations, both from a privacy and a financial standpoint. While security mechanisms are deployed at various levels, these are frequently put under strain by previously unseen malware. An additional protection layer capable of novelty detection is therefore needed. In this work we propose SpotCheck, an anomaly detector intended to run on Android devices. It samples app executions and submits suspicious apps to more thorough processing by malware sandboxes. We compare Kernel Principal Component Analysis (KPCA) and Variational Autoencoders (VAE) on app execution representations based on the well-known system call traces, as well as a novel approach based on memory dumps. Results show that when using VAE, SpotCheck attains a level of effectiveness comparable to what has been previously achieved for network anomaly detection. Interestingly this is also true for the memory dump approach, relinquishing the need for continuous app monitoring.
URI: https://www.um.edu.mt/library/oar/handle/123456789/90979
Appears in Collections:Scholarly Works - FacICTCS

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