Giulia Milan
Design of a Reinforcement Learning Framework to Automatically Interact with IoT Devices.
Rel. Marco Mellia, Luca Vassio, Idilio Drago. Politecnico di Torino, Master of science program in Computer Engineering, 2020
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Abstract
In IT systems, the presence of IoT devices is exponentially growing. Most of them are custom devices, and they rely on proprietary protocols, often closed or poorly documented. This could lead to possible security threats and abuses. Given this situation, we would like to monitor the activity of possible attackers to these IT systems. This monitoring task could be realized, for example, with honeypots, which are decoys that mimic a target for hackers, and use their intrusion attempts to gain information about them, learning about their intentions and learning about new kinds of attacks. This is a challenging task, since the honeypot should communicate with unknown attackers through a huge variety of protocols.
Moreover, each protocol has its own format, syntax and its own state-machine
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