Visible to the public Identification of Distributed Malware

TitleIdentification of Distributed Malware
Publication TypeConference Paper
Year of Publication2018
AuthorsJain, D., Khemani, S., Prasad, G.
Conference Name2018 IEEE 3rd International Conference on Communication and Information Systems (ICCIS)
ISBN Number978-1-5386-9273-8
Keywordsandroid, Android malware, Android system, attackers, botnets, computer malware, computer viruses, distributed direction, distributed malware, fully functional portable computers, generic viruses, Google, graph matching algorithm, graph theory, Human Behavior, inholding multiple applications, Labeling, Malware, malware analysis, malware detection, malware prevention, malware writers, Metrics, mobile computing, Mobile handsets, multiple anti-virus apps, open source platform, personal data, privacy, pubcrawl, public domain software, Resiliency, security, Servers, simple worms, smart phones, smartphone revolution, sophisticated DDOS, static analysis, technological complexities increase

Smartphones have evolved over the years from simple devices to communicate with each other to fully functional portable computers although with comparatively less computational power but inholding multiple applications within. With the smartphone revolution, the value of personal data has increased. As technological complexities increase, so do the vulnerabilities in the system. Smartphones are the latest target for attacks. Android being an open source platform and also the most widely used smartphone OS draws the attention of many malware writers to exploit the vulnerabilities of it. Attackers try to take advantage of these vulnerabilities and fool the user and misuse their data. Malwares have come a long way from simple worms to sophisticated DDOS using Botnets, the latest trends in computer malware tend to go in the distributed direction, to evade the multiple anti-virus apps developed to counter generic viruses and Trojans. However, the recent trend in android system is to have a combination of applications which acts as malware. The applications are benign individually but when grouped, these may result into a malicious activity. This paper proposes a new category of distributed malware in android system, how it can be used to evade the current security, and how it can be detected with the help of graph matching algorithm.

Citation Keyjain_identification_2018