Covertvasion: Depicting threats through covert channels based novel evasive attacks in android

被引:0
作者
Gautam S. [1 ]
Pattani K. [2 ]
Zuhair M. [1 ]
Rashid M. [3 ]
Ahmad N. [4 ]
机构
[1] Department of Computer Science and Engineering, Institute of Technology, Nirma University Ahmedabad, Gujarat
[2] Department of Computer Sciences and Engineering, Institute of Advanced Research, Gujarat, Gandhinagar
[3] School of Information Communication and Technology, Bahrain Polytechnic, Isa Town
[4] Department of Information System, College of Applied Sciences, King Khalid University, P.O. Box 61913, Muhayel
来源
International Journal of Intelligent Networks | 2023年 / 4卷
关键词
Covert channel; Evasion; File-lock based evasive information invasion; Prime-composite evasive information invasion;
D O I
10.1016/j.ijin.2023.11.006
中图分类号
学科分类号
摘要
Privacy and security issues concerning mobile devices have substantial consequences for individuals, groups, governments, and businesses. The Android operating system bolsters smartphone data protection by imposing restrictions on app behavior. Nevertheless, attackers conduct systematic resource analyses and divert privacy-sensitive information from plain view. They employ evasive mechanisms to evade system monitoring and create an illusion of benign and non-sensitive communication. Furthermore, covert channels amplify the impact of these malicious activities by facilitating information transfer through non-standard methods. The purpose of this research is to shed light on these novel threats targeting Android systems. The study delves into security and privacy attacks that compromise sensitive user information. The methodology leverages evasion concepts and employs sound-specific covert channel communication, particularly ultrasonic channels. This research work introduces novel evasive attacks, namely Prime-Composite Evasive Information Invasion (PCEII) and File-lock-based Evasive Information Invasion (FEII), both relying on covert channel communication. These unique variants of attacks successfully evade user data within a few milliseconds for both noisy as well as non-noisy environments and do not show any signs of detection by antivirus mechanisms like Anti-Virus Guard (AVG), 360 security, etc. and state-of-the-art tools such as TaintDroid, MockDroid and others. The paper not only assesses their impact on the privacy and security of information but also introduces avenues for their detection and mitigation. © 2023 The Authors
引用
收藏
页码:337 / 348
页数:11
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