CAGDEEP : Mobile malware analysis using force atlas 2 with strong gravity call graph and deep learning

• Main Authors: Nur Khairani, Kamarudin, Ahmad Firdaus, Zainal Abidin, Azlee, Zabidi, Mohd Faizal, Ab Razak
• Format: Conference or Workshop Item
• Language: English; English
• Published: Institute of Electrical and Electronics Engineers Inc. 2023
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software; T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/40367/1/CAGDEEP_Mobile%20malware%20analysis%20using%20force%20atlas%202.pdf; http://umpir.ump.edu.my/id/eprint/40367/2/CAGDEEP_Mobile%20malware%20analysis%20using%20force%20atlas%202%20with%20strong%20gravity%20call%20graph%20and%20deep%20learning_ABS.pdf; http://umpir.ump.edu.my/id/eprint/40367/; https://doi.org/10.1109/ICSECS58457.2023.10256350

Today many smart devices are running on Android systems. With the increasing popularity of Android, mobile malware continuously evolves as well, and further attacks Android operating systems. To address these shortcoming issues many security experts use different approaches to detect malware based o...