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  1. Proceedings of the 1st International Workshop on Agents and CyberSecurity (ACySE '14)
  2. SMS mobile botnet detection using a multi-agent system: research in progress
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Identifying and modeling botnet C&C behaviors
SMS mobile botnet detection using a multi-agent system: research in progress
Playing hide-and-seek: an abstract game for cyber security
A memory efficient privacy preserving representation of connection graphs
Agent-based modeling of user circumvention of security
An agent-based framework for dynamical understanding of DNS events (DUDE)
The science of security: introduction from the perspective of secure collaboration
How to spend it: optimal investment for cyber security
Cyber-security challenges of agent technology in intelligent transportation systems
Using agents towards providing security on a context-aware architecture
Effects of network delays on swarming in a multi-agent security system

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SMS mobile botnet detection using a multi-agent system: research in progress

Content Provider ACM Digital Library
Author Alzahrani, Abdullah J. Ghorbani, Ali A.
Abstract With the enormous growth of Android mobile devices and the huge increase in the number of published applications (apps), Short Message Service (SMS) is becoming an important issue. SMS can be abused by attackers when they send SMS spam, transfer all command and control (C&C) instructions, launch denial-of-service (DoS) attacks to send premium-rate SMS messages without user permission, and propagate malware via URLs sent within SMS messages. Thus, SMS has to be reliable as well as secure. In this paper, we propose a SMS botnet detection framework that uses multi-agent technology based on observations of SMS and Android smartphone features. This system detects SMS botnets and identifies ways to block the attacks in order to prevent damage caused by these attacks. An adaptive hybrid model of SMS botnet detectors is being developed by using a combination of signature-based and anomaly-based methods. The model is designed to recognize malicious SMS messages by applying behavioural analysis to find the correlation between suspicious SMS messages and reported profiling. Behaviour profiles of Android smartphones are being created to carry out robust and efficient anomaly detection. A multi-agent system technology was selected to perform light-weight detection without exhausting smartphone resources such as battery and memory.
Starting Page 1
Ending Page 8
Page Count 8
File Format PDF
ISBN 9781450327282
DOI 10.1145/2602945.2602950
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2014-05-06
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Multi-agent system Sms Botnet detection Smartphone
Content Type Text
Resource Type Article
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