Spence Aaron, Bangay Shaun
School of Information Technology, Deakin University, Geelong 3216, Australia.
Entropy (Basel). 2024 Aug 13;26(8):684. doi: 10.3390/e26080684.
Side channels are unintended pathways within target systems that leak internal target information. Side-channel sensing (SCS) is the process of exploiting side channels to extract embedded target information. SCS is well established within the cybersecurity (CYB) domain, and has recently been proposed for medical diagnostics and monitoring (MDM). Remaining unrecognised is its applicability to human-computer interaction (HCI), among other domains (Misc). This article analyses literature demonstrating SCS examples across the MDM, HCI, Misc, and CYB domains. Despite their diversity, established fields of advanced sensing and signal processing underlie each example, enabling the unification of these currently otherwise isolated domains. Identified themes are collating under a proposed domain-agnostic SCS framework. This SCS framework enables a formalised and approach to studying, detecting, and exploiting of side channels both within and between domains. Opportunities exist for modelling SCS as data structures, allowing for computation irrespective of domain. Future methodologies can take such data structures to enable cross- and intra-domain transferability of extraction techniques, perform side-channel leakage detection, and discover new side channels within target systems.
侧信道是目标系统内意外出现的、会泄露目标内部信息的路径。侧信道传感（SCS）是利用侧信道来提取嵌入式目标信息的过程。SCS在网络安全（CYB）领域已得到充分确立，最近有人提出将其用于医疗诊断和监测（MDM）。尚未被认识到的是，它在人机交互（HCI）以及其他领域（Misc）中的适用性。本文分析了展示MDM、HCI、Misc和CYB领域中SCS示例的文献。尽管这些示例各不相同，但每个示例都基于先进传感和信号处理的既定领域，从而实现了这些目前相互孤立的领域的统一。已识别的主题正在一个提议的领域无关SCS框架下进行整理。这个SCS框架为跨领域和领域内研究、检测和利用侧信道提供了一种形式化的方法。将SCS建模为数据结构存在机会，这样可以进行与领域无关的计算。未来的方法可以采用这样的数据结构，以实现提取技术在跨领域和领域内的可转移性，执行侧信道泄漏检测，并在目标系统中发现新的侧信道。
