radiomic features for medical images tamper detection by equivalence checking

Abstract Digital medical images are very easy to be modified for illegal purposes. An attacker may perform this act in order to stop a political candidate, sabotage research, commit insurance fraud, perform an act of terrorism, or even commit murder. Between the machine that performs medical scans and the radiologist monitor, medical images pass through different devices: in this chain an attacker can perform its malicious action. In this paper we propose a method aimed to avoid medical images modifications by means of equivalence checking. Magnetic images are represented as finite state automata and equivalence checking is exploited to check whether the medical resource have been subject to illegal modifications

a blockchain based proposal for protecting healthcare systems through formal methods

Abstract Blockchain technology is one of the most important and disruptive technologies in the world. Multiple industries are adopting the blockchain technology to innovate the way they work. One of the industries that are looking to adopt the blockchain is the healthcare industry. In fact, the protection of the private information stored in hospital database is a critical issue. In this paper we propose a method aimed to protect information exchanged in hospital networks, with particular regard to magnetic resonance images. As required from blockchain technology, each host network must validate the transiting data network: we exploit formal equivalence checking to perform this validation, by modeling magnetic resonance images in terms of automata by exploiting radiomic features