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

ECCS/IHCS-SGER：探索人工神经网络以开发生物植入片上系统的自适应威胁检测技术

• 批准号: 0832990
• 负责人: Allen Cheng
• 金额: $ 7.5万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0832990&HistoricalAwards=false
• 关键词: ECCS; IHCS; SGER; Exploring; Artificial

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.

这项探索性研究的目标是开发一种网络支持的自主威胁管理系统，旨在将当今脆弱的生物植入物转化为具有弹性的生物植入式芯片系统。 目标是实现下一代生物植入式系统，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。 该研究探讨了如何对意外威胁进行建模，以及生物植入物如何知道存在威胁。 为此，本研究的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。在智力方面，本研究旨在再现中枢神经系统固有的威胁弹性，通过自适应机制处理不可预测的威胁。具体而言，所提出的人工神经网络技术旨在通过捕捉大脑的高度平行和自组织性质以及大脑识别动态人体植入系统中意外威胁的不同表现形式之间的复杂非线性关系的能力来模仿其在人类大脑中的生物对应物。这项研究有可能促进今后研究和开发可靠的生物植入技术，以了解生物系统、诊断和治疗疾病以及人体增强。 通过培养博士生实现研究与教育的一体化。学生，开发新的教育材料和在线工具的传播。 该项目将利用现有的大学外联方案，试图扩大女性和其他代表性不足群体的学生的参与，并使K-12学生接触工程。