Narasimhan Seetharam, Wang Xinmu, Bhunia Swarup
Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:6425-8. doi: 10.1109/IEMBS.2010.5627327.
Implantable systems that monitor biological signals require increasingly complex digital signal processing (DSP) electronics for real-time in-situ analysis and compression of the recorded signals. While it is well-known that such signal processing hardware needs to be implemented under tight area and power constraints, new design requirements emerge with their increasing complexity. Use of nanoscale technology shows tremendous benefits in implementing these advanced circuits due to dramatic improvement in integration density and power dissipation per operation. However, it also brings in new challenges such as reliability and large idle power (due to higher leakage current). Besides, programmability of the device as well as security of the recorded information are rapidly becoming major design considerations of such systems. In this paper, we analyze the emerging issues associated with the design of the DSP unit in an implantable system. Next, we propose a novel ultra light-weight solution to address the information security issue. Unlike the conventional information security approaches like data encryption, which come at large area and power overhead and hence are not amenable for resource-constrained implantable systems, we propose a multilevel key-based scrambling algorithm, which exploits the nature of the biological signal to effectively obfuscate it. Analysis of the proposed algorithm in the context of neural signal processing and its hardware implementation shows that we can achieve high level of security with ∼ 13X lower power and ∼ 5X lower area overhead than conventional cryptographic solutions.
监测生物信号的可植入系统需要日益复杂的数字信号处理（DSP）电子设备，以便对记录的信号进行实时原位分析和压缩。虽然众所周知，这种信号处理硬件需要在严格的面积和功率限制下实现，但随着其复杂性的增加，新的设计要求也随之出现。由于每操作的集成密度和功耗有显著提高，纳米级技术的使用在实现这些先进电路方面显示出巨大优势。然而，它也带来了新的挑战，如可靠性和大的空闲功率（由于更高的漏电流）。此外，设备的可编程性以及记录信息的安全性正迅速成为此类系统的主要设计考虑因素。在本文中，我们分析了与可植入系统中DSP单元设计相关的新出现问题。接下来，我们提出一种新颖的超轻量级解决方案来解决信息安全问题。与诸如数据加密等传统信息安全方法不同，传统方法会带来大面积和高功率开销，因此不适用于资源受限的可植入系统，我们提出一种基于多级密钥的加扰算法，该算法利用生物信号的特性来有效地对其进行混淆。在神经信号处理背景下对所提出算法及其硬件实现的分析表明，与传统加密解决方案相比，我们可以实现高水平的安全性，同时功耗降低约13倍，面积开销降低约5倍。
