Detection of malware applications using social spider algorithm in mobile cloud computing environment. (6th July 2020)

• Record Type: Journal Article
• Authors: Nisha, O.S. Jannath; Bhanu, S. Mary Saira
• Is Part Of: International journal of ad hoc and ubiquitous computing. Volume 34:Number 3(2020)
• Page Start: 154
• Page End: 169
• Publication Date: 2020-07-06
• Subjects: malware and benign applications -- social spider algorithm -- SSA -- mobile cloud services -- permissions -- feature selection; Ubiquitous computing -- Periodicals; Embedded computer systems -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Wireless communication systems -- Periodicals; Computer architecture -- Periodicals; 004.2
• Languages: English
• ISSNs: 1743-8225

Abstract

Nowadays, mobile devices are essential for day to day life. The mobile users use the applications available in both official and unofficial application markets. The mobile device's computing power and storage capacity are insufficient for executing these applications. So, to overcome this, mobile cloud computing technology is used, which allows the developers to build these applications suitable for mobile devices. The attackers can also develop apps with malicious codes to perform malicious activities. Security threats are to be considered before installing an application in a mobile device. Among the features that characterise the behaviour of an application, permission to access resources is an important feature which is used for detecting malicious applications. In this paper, the proposed model uses a social spider algorithm (SSA) to select the optimal set of permission features and malicious applications are detected using classification techniques. The experimental results demonstrate that SSA outperforms other stochastic-based optimisation algorithms.