Stefano Zanero

Breaking the Laws of Robotics: Attacking Industrial Robots
Politecnico di Milano, Italy
21, Feb, 2019 14:00-14:45 (45 minutes)
CISTER, Porto, Portugal

ABSTRACT:
Industrial robots are complex cyber-physical systems used for manufacturing, and a critical component of any modern factory. These robots aren't just electromechanical devices but include complex embedded controllers, which are often interconnected with other computers in the factory network, safety systems, and to the Internet for remote monitoring and maintenance. In this scenario, industrial routers also play a key role, because they directly expose the robot's controller. Therefore, the impact of a single, simple vulnerability can grant attackers an easy entry point. The talk will discuss how remote attackers are able to attack such robots up to the point where they can alter the manufactured product, physically damage the robot, steal industry secrets, or injure humans.

BIO:
Stefano Zanero received a PhD in Computer Engineering from Politecnico di Milano, where he is currently an associate professor. His research focuses on malware analysis, cyberphysical security, and cybersecurity in general. Besides teaching "Computer Security" and "Computer Forensics" at Politecnico, he has an extensive speaking and training experience in Italy and abroad. He co-authored over 70 scientific papers and books. He is a Senior Member of the IEEE (for which he sits on the MGA board), the IEEE Computer Society (for which he is a member of the Board of Governors), and a lifetime senior member of the ACM. Stefano co-founded the Italian chapter of ISSA (Information System Security Association). He has been named a Fellow of ISSA and sits in its International Board of Directors. Stefano is also a co-founder and chairman of Secure Network, a leading information security consulting firm based in Milan and in London; a co-founder of 18Months, a cloud-based ticketing solutions provider; and a co-founder of BankSealer, a startup in the FinTech sector that addresses fraud detection through machine learning techniques.

EVENT PHOTOS:
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S101 Auditorium/Seminar Room
1st Floor