Analysis of Data Patterns Behaviour and Classification of Noise Data use in Mobile Forensics.

Mobile Forensic Data Analysis is an approach that aims to discover criminals by utilizing data collected from mobile devices and algorithms that detect suspicious patterns. In situations where criminal action is linked to automated processes, such as the propagation of malware, it is simple to anticipate the outcome. Prediction and detection become more appealing for situations in which human behavior is involved, such as in typical criminal cases. The current study suggests a combined criminal profiling and suspicious pattern detection approach. The study focuses on cyberbullying and small-scale drug sales, both of which rely extensively on mobile devices. Another focus of the study is on the identification of suspicious patterns. Through the connecting of several observable patterns, our evidence-based strategy leads to an increase in accuracy and a reduction in the number of false positives on a dataset. Immediately following the evaluation and presentation of the outcomes of tests carried out on a dataset that contains both benign and malicious traffic, the scenarios are re-executed on a real dataset for the purpose of conducting additional testing and verification. [ABSTRACT FROM AUTHOR]