ECCS/IHCS-SGER: Exploring Artificial Neural Networks to Develop Self-Adaptive Threat Detection Techniques for Bio-Implantable System-on-Chip

这项探索性研究的目标是开发一种网络自主威胁管理系统，旨在将当今脆弱的生物植入物转变为有弹性的生物植入芯片系统。目标是实现下一代生物植入式系统，该系统能够动态重新配置，以应对复杂和不可预测的人体中的意外威胁。该研究探讨了如何模拟意外威胁以及生物植入物如何知道存在威胁。为此，研究重点是使用统计和概率方法的威胁建模和注入方案，以及使用生物启发的人工神经网络技术的自适应威胁检测方案。就智力价值而言，本研究旨在重现中枢神经系统固有的威胁复原力，该系统通过自适应机制处理不可预测的威胁。具体来说，所提出的人工神经网络技术旨在通过捕捉大脑的高度并行和自组织性质，以及大脑在动态人体植入系统中识别意外威胁不同表现之间复杂非线性关系的能力，来模仿人脑中的生物对等体。就更广泛的影响而言，这项研究有可能促进未来可靠的生物植入技术的研究和发展，以了解生物系统，疾病的诊断和治疗，以及人类的增强。通过培养博士生、开发新教材和在线工具传播，实现研究与教育的整合。该项目将利用现有的大学外展计划，试图扩大女性和其他代表性不足群体学生的参与，并让K-12学生接触工程学。

The objective of this exploratory research is to develop a cyber-enabled autonomic threat-management system aimed at transforming today's vulnerable bio-implants into resilient bio-implantable systems-on-chip. The goal is to realize next-generation bio-implantable systems that are capable of dynamic reconfiguration to react to unexpected threats in the complex and unpredictable human body. The research explores how to model unexpected threats and how a bio-implant knows that there is a threat. To this end, the research focuses on threat modeling and injection schemes using statistical and probabilistic approaches and self-adaptive threat detection schemes using biologically-inspired artificial neural network techniques.With respect to intellectual merit, this research aims to reproduce the inherent threat resilience of the central nervous system, which handles unpredictable threats via self-adapting mechanisms. Specifically, the proposed artificial neural network technique is intended to mimic its biological counterpart in the human brain by capturing the brain's highly parallel and self-organizing nature and the brain's ability to recognize complex non-linear relationships among different manifestations of unexpected threats in a dynamical human-implant system.With respect to broader impacts, this research has the potential to facilitate future research and development of reliable bio-implantable technologies for the understanding of biological systems, the diagnosis and treatment of disease, and human augmentation. Integration of research and education is achieved through training of Ph.D. students, development of new educational material, and online tool dissemination. This project will use existing university outreach programs to attempt to broaden the participation of females and other students from underrepresented groups and to expose K-12 students to engineering.