A Review on Malware Variants Detection Techniques for Threat Intelligence in Resource Constrained Devices: Existing Approaches, Limitations and Future Direction

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Chimeleze C.U.
Jamil N.
Ismail R.
Lam K.-Y.
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Springer Science and Business Media Deutschland GmbH
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The Internet of Things (IoT) has been an immediate major turning point in information and communication technology as it gives room for connection and information sharing among numerous devices. Notwithstanding, malicious code attacks have exponentially increased, with malicious code variants ranked as a major threat in resource constrained devices in IoT environment thereby making the efficient malware variants detection a serious concern for researchers in recent years. The capacity to detect malware variants is essential for protection against security breaches, data theft and other dangers. Hence with the explosion of resource constrained devices for IoT applications, it becomes very important to document existing cutting-edge techniques developed to detect malware variants in these devices. In this paper, we have investigated extensively the implementation of malware variants detection models particularly in smartphones as a case study for resource constrained devices. The paper covers the current techniques for detection of malware variants, comprehensive assessment of the techniques and recommendations for future researches. � 2021, Springer Nature Singapore Pte Ltd.
Codes (symbols); Internet of things; Comprehensive assessment; Detection models; Information and Communication Technologies; Information sharing; Internet of thing (IOT); IOT applications; Resourceconstrained devices; Security breaches; Malware