A Machine Learning Approach for Detecting and Categorizing Sensitive Methods in Android Malware

Hayyan Salman Hasan; Hasan Muhammad Deeb; Behrouz Tork Ladani

Articles in Press, Accepted Manuscript, Available Online from 20 June 2022

http://dx.doi.org/10.22042/isecure.2022.321436.741

Abstract
  Sensitive methods are those that are commonly used by Android malware to perform malicious behavior. These methods may be either evasion or malicious payload methods. Although there are several approaches to handle these methods for performing effective dynamic malware analysis, but generally most of ...  Read More

Curious-Monkey: Evolved Monkey for Triggering Malicious Payloads in Android Malware

Hayyan Hasan; Behrouz Tork Ladani; Bahman Zamani

Volume 13, Issue 2 , July 2021, , Pages 131-143

http://dx.doi.org/10.22042/isecure.2021.262208.589

Abstract
  Dynamic analysis is a prominent approach in analyzing the behavior of Android apps. To perform dynamic analysis, we need an event generator to provide proper environment for executing the app in an emulator. Monkey is the most popular event generator for Android apps in general, and is used in dynamic ...  Read More

DyVSoR: dynamic malware detection based on extracting patterns from value sets of registers

M. Ghiasi; A. Sami; Z. Salehi

Volume 5, Issue 1 , January 2013, , Pages 71-82

http://dx.doi.org/10.22042/isecure.2013.5.1.5

Abstract
  To control the exponential growth of malware files, security analysts pursue dynamic approaches that automatically identify and analyze malicious software samples. Obfuscation and polymorphism employed by malwares make it difficult for signature-based systems to detect sophisticated malware files. The ...  Read More