Machine learning aided Android malware classification

TL;DR: The goal is to design a scalable anomaly detection engine suitable for large-scale smart grids, which can differentiate an actual fault from a disturbance and an intelligent cyber-attack.

TL;DR: This article presents a survey of DRL approaches developed for cyber security, including DRL-based security methods for cyber-physical systems, autonomous intrusion detection techniques, and multiagent D RL-based game theory simulations for defense strategies against cyberattacks.

TL;DR: The proposed method can detect and classify ransomware that can fingerprint the environment and it is discovered that different feature dimensions are required for achieving similar classifier performance with feature N-grams of diverse lengths.

TL;DR: Two distinct models are utilized to identify the obscure or new sort of malware in this paper and they got a testing accuracy of 74.5% on GoogleNet and 88.36% precision on ResNet.

TL;DR: Using TaintDroid to monitor the behavior of 30 popular third-party Android applications, this work found 68 instances of misappropriation of users' location and device identification information across 20 applications.

TL;DR: Preliminary experimental results are quite promising with 98% classification accuracy on a malware database of 9,458 samples with 25 different malware families and the technique exhibits interesting resilience to popular obfuscation techniques such as section encryption.

TL;DR: The use of machine learning and data mining to detect and classify malicious executables as they appear in the wild is described and it is suggested that the methodology could be used as the basis for an operational system for detecting previously undiscovered malicious executable.

TL;DR: The usefulness of PlayDrone is demonstrated in decompiling and analyzing application content by exploring four previously unaddressed issues: the characterization of Google Play application content at large scale and its evolution over time, library usage in applications and its impact on application portability, duplicative application content in Google Play, and the ineffectiveness of OAuth and related service authentication mechanisms.