Description
Complex embedded devices are becoming ever prevalent in our everyday lives, yet only a tiny amount of people consider the potential security and privacy implications of attaching such devices to our home, business and government networks. As demonstrated through recent publications from academia and blog posts from numerous industry figures, these devices are plagued by poor design choices concerning end-user security. What’s even more worrying, are reports of manufacturers inserting backdoor-like functionality into the production firmware of those devices.This talk will provide a precise definition of the term backdoor and outline a framework we have devised for reasoning about such constructs. We will discuss the main challenges in backdoor detection, and present two tools we have developed to perform backdoor detection in a semi-automated manner. We will demonstrate the effectiveness of our methods through a number of case-studies of real-world backdoors.
Practical infos
Next sessions
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Tackling obfuscated code through variant analysis and Graph Neural Networks
Speaker : Roxane Cohen and Robin David - Quarkslab
Existing deobfuscation techniques usually target specific obfuscation passes and assume a prior knowledge of obfuscated location within a program. Also, some approaches tend to be computationally costly. Conversely, few research consider bypassing obfuscation through correlation of various variants of the same obfuscated program or a clear program and a later obfuscated variant. Both scenarios are[…]-
Malware analysis
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Binary analysis
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Obfuscation
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