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Title: MALWARE DETECTION IN DTN BASED ON ITS BEHAVIOUR

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Title:
MALWARE DETECTION IN DTN BASED ON ITS BEHAVIOUR
Author Name:
R.P.Kaaviya Priya, G.Bhavani
Abstract:
The Behavioural characterization of malware is an effective alternative to pattern matching in detecting malware. The Delay tolerant network is a viable communication with mobile consumer electronics equipped with short range communication technologies such as Bluetooth, Wi-Fi Direct. This paper propose a general behaviour characterization of proximity malware based on Naive Bayesian model. It was identified with two unique challenges for extending Bayesian malware detection to DTNs and so propose a simple and effective method “look ahead”, to address the challenges with two extensions to look ahead, dogmatic filtering, and adaptive look ahead, they address the challenge of “malicious nodes sharing false evidence.” Real mobile network traces are used to verify the effectiveness of the proposed methods.
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