Memristor-Based Encryption For Free-Floating Neural Implants

Abstract

The recent advances in the semiconductor industry have given rise to the development of highly scalable, wireless and battery-free neural-implant interfaces that enable brain monitoring and brain stimulation with high spatial and temporal resolution. Such implants are referred to as Free-Floating Neural Implants (FFNI), as the small size and untethered communication allow them to be scattered throughout the cortex. Nevertheless, the plethora of proposed interfaces have failed to mention and act against the potential security implications that may arise in highly-constrained FFNIs even though the U.S. Food and Drug Administration (FDA) has recently acknowledged the possibility of short-/long-range attacks on wireless Implantable Medical Devices (IMD). Hence, in this project, the existing threats in FFNIs are revealed, followed by the proposal of a memristor-based lightweight security approach to secure intracranial electromagnetic transmissions whilst considering the anticipated physical limitations of these constrained topologies. More specifically, a consolidated envisioned system is highlighted for which a read-only GIFT cipher is implemented. This lightweight encryption block primarily consists of a One-Transistor-One-Memristor (1T1R) crossbar structure for carrying out operations such as Substitution, Permutation, and addRoundKey, without destroying the resistive states and by only performing ‘read’ operations to maintain low power operation. With a footprint of 0.0034 mm2 the 1T1R-GIFT cipher reaches an average power and energy consumption of only 60.38 µW and 241.52 pJ, respectively. However, the performance does not exceed a CMOS-based implementation yet, whose footprint is similar but has roughly half the average power and energy consumption. This can be attributed mainly to the immaturity of the memristor technology. This work demonstrates that only after further advancements in memristor logic gates, crossbar topologies and fabrication processes, highly-constrained FFNIs can fully benefit from the scalable memristor-based security paradigm.