08-slay-botnet-csss-talk.pdf - Jill Slay Developing Network...

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Jill Slay Developing Network Forensic Mechanisms for the Botnet of Things
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Work carried out by Slay, Sitnikova, Moustafa and Koroniotis Introduction Background to IoT and our work Machine Learning IoT Security Review Botnets in the IOT Network Forensics in the IOT Network Forensics Architectures Evaluation Metrics Results Conclusion
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Overview The IoT is a network of interconnected everyday objects called “things”, that have been augmented with a small measure of computing capabilities. Lately, the IoT has been affected by a variety of different botnet activities. As botnets have been the cause of serious security risks and financial damage over the years, existing network forensic techniques cannot identify and track current sophisticated methods of botnets. This is because commercial tools mainly depend on signature-based approaches that cannot discover new forms of botnet. In the literature, several studies have conducted the use of Machine Learning (ML) techniques in order to train and validate a model for defining such attacks, but they still produce high false alarm rates with the challenge of investigating the tracks of botnets. This presentation investigates the role of ML techniques for developing a network forensic mechanism based on network flow identifiers that can track suspicious activities of botnets. The experimental results using the UNSW-NB15 dataset revealed that ML techniques with flow identifiers can effectively and efficiently detect botnets’ attacks and their tracks.
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The Internet of Things The concept thought to date back to the early 1980s. a vending machine selling beverages at the Carnegie Mellon University was connected to the Internet, so that its inventory could be accessed online to determine if drinks were available Term covering a multitude of devices and technologies. Can be viewed as a collection of devices with low processing power and network communication capabilities. Increasing number of IoT devices. In 2017 reached 8,3 billion, are expected to reach 20,4 billion in 2020.
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Recent Events Mirai a botnet consisting of 100.000 infected “things” that in October 2016, attacked and took out a good portion of the Internet’s high-profile services such as Twitter and Netflix by doing a DDoS attack on Dyn (DNS provider) [36]. Since then, Mirai has slowly been divided into smaller botnets, and new botnets have risen, such as BrickerBot, which as its name implies “bricks” an IoT device (permanently disables it) and Hajime
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Our work Different security controls have been used for defining botnet events, including network forensic techniques and tools and intrusion detection and prevention systems.
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