Role of Telemedicine for Facio-Odontogenic Pain Management During COVID-19 Pandemic

Chaos blended cellular automata on fractals: the effective way of reconfigurable hardware assisted medical image privacy

In more recent times data continues to be generated at a very unprecedented scale. This is a result of the pervasive nature of modern-day digitisation. As such, it is absolutely critical that this data only be accessed by the trusted parties concerned in an effort to maintain the privacy of individuals. One particular type data that could severely compromise the identity and privacy of an individual is 'medical data'. With a focus on medical images, this work proposes a novel 'fractalized' chaos-cellular automata encryption scheme, implemented on Cyclone IV EP2C35F672C6 FPGA, resulting in a hardware-based concurrent security solution. The scheme entails three stages of diffusion, which arise from different mechanisms. In tandem with the diffusion process is the "On the Fly" process of confusion governed by a Linear feedback Shift Register (LFSR), all of which in implemented by applying the nature of fractals. The security architecture occupies 16,351 Logic Elements (LEs) with 230 registers on the target FPGA with the power dissipation of 133.39 mW. Further, the encryption achieves near zero correlation with the average entropy of 15.17156 that ensures the statistical properties. In addition, the security framework requires 12.13 ms to encrypt a 256 × 256 × 16 DICOM image which results in the throughput of 86.44 Mbps. The proposed encryption resists the brute force attack and chosen plain text attack by achieving a very large span of keyspace.