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Found 5 papers, 1 papers with code
Light up that Droid! On the Effectiveness of Static Analysis Features against App Obfuscation for Android Malware Detection
Therefore, it needs to be determined to what extent the use of a specific obfuscation strategy or tool poses a risk for the validity of ML malware detectors for Android based on static analysis features.
Towards a Fair Comparison and Realistic Evaluation Framework of Android Malware Detectors based on Static Analysis and Machine Learning
As in other cybersecurity areas, machine learning (ML) techniques have emerged as a promising solution to detect Android malware.
A review on outlier/anomaly detection in time series data
Recent advances in technology have brought major breakthroughs in data collection, enabling a large amount of data to be gathered over time and thus generating time series.
Survey of Network Intrusion Detection Methods from the Perspective of the Knowledge Discovery in Databases Process
As such, we discuss the techniques used for the capture, preparation and transformation of the data, as well as, the data mining and evaluation methods.
A review on distance based time series classification
The particularity of the data makes it a challenging task and different approaches have been taken, including the distance based approach.
