Nikos Fotiou, Vasilios A. Siris, Spyros Voulgaris, George C. Polyzos and Dmitrij Lagutin

We address the limitations of existing information security solutions when applied to the cyber-physical world. In particular, we consider the case of Internet of Things (IoT) actuation and we argue that it is hard to secure such a process. To this end, we propose a “damage control” approach, where service time is divided into slots and users perform microservice transactions, paying essentially in advance for each one, corresponding to one service slot. Under these circumstances, in the case of service disruption, a user, in the worst case, may lose the amount of money that corresponds to a single micro-service transaction in a single time slot. We implement our solution by leveraging blockchain-based smart contracts, off-chain payments, and one-time Hash-based Message Authentication Code (HMAC) passwords. Our solution supports IoT devices with limited processing capabilities and which are not necessarily connected to the Internet. Moreover, with our solution, IoT devices do not interact directly with the blockchain. In fact, they are oblivious to the use of blockchain technology. They do not store any usersensitive information, neither are payments made to or is value stored on the devices.

View More Papers

Privacy preserving learning in IoT systems

Farinaz Koushanfar (Professor and Henry Booker Faculty Scholar, Co-Founder and Co-Director, Center for Machine-Integrated Computing and Security, Jacobs School of Engineering, University of California, San Diego)

Read More

Poisoning Attacks on Federated Learning-based IoT Intrusion Detection System

Thien Duc Nguyen, Phillip Rieger, Markus Miettinen and Ahmad-Reza Sadeghi (TU Darmstadt, Germany)

Read More

UIDS: Unikernel-based Intrusion Detection System for the Internet of...

Vittorio Cozzolino, Nikolai Schwellnus (Technical University of Munich, Germany); Aaron Yi Ding (Delft University of Technology, The Netherlands); Jörg Ott (Technical University of Munich, Germany)

Read More

Information Leaks in Sequential Federated Learning

Anastassiya Pustozerova and Rudolf Mayer (SBA Research, Austria)

Read More