Advanced Analysis and Detection Techniques for Android Malware: Enhancing Security and Mitigation Strategies
Mr Ramesh Kumar,Asst. Prof.,AIIT,Amity University,Patna
Rohit Kumar,Student,AIIT,Amity University,Patna
Abstract
Android’s popularity as a mobile operating device makes it one of the most attractive targets for cybercriminals. Banking, shopping, and other essential activities have increasingly become reliant on mobile apps. Consequently, Android devices face a growing number of security risks. This study aims to enhance the methods for detecting and preventing threats by delving deeper into understanding Android malware—software that is programmed to exploit these vulnerabilities. The study will focus on several specific types of Android malware, including spyware, adware, ransomware, and Trojan malware. Each of these parasites has a different objective, ranging from the theft of personal information, generating ad revenue by controlling users’ devices, to the use of files as hostages until the demand for payment is completed. Learning their methods of operation and damage will allow for the creation of improved protective measures for the users. For the purpose of detecting and analyzing malware in the most effective way possible, the research will focus on these three main processes: static, dynamic, and hybrid analysis. Static analysis allows the analyst to examine the code of the application as well as its structure without execution, allowing one to identify the existing threats. Dynamic analysis observes an application’s code and structure during runtime within a controlled environment to reveal secrets of malicious undertakings. Hybrid analysis increases accuracy by integrating both methods. The study will analyze the advantages and disadvantages of each technique in order to evaluate the existing gaps in the methodologies. The more sophisticated aspects of malware detection, such as the use of obfuscation and evasion tactics, like code encryption, polymorphism, and anti-analysis schemes tend to render traditional approaches to be less effective. The aim of this research is to improve mechanisms of detection so that the results will be accurate and the process remain efficient. By understanding the transforming landscape of Android malware, this research will support the development of more effective security strategies that defend user privacy, sensitive information, and the overall security of the Android environment. Through theoretical and practical research, it will deliver a holistic approach to malware detection and mitigation.
Keywords: Android App , Static Analysis , Malware, Privacy , Data Protection
