I-Corps: Stochastic Computing-based Host Intrusion Detection System

这个i-Corps项目的更广泛的影响/商业潜力是通过使用一种新型的基于硬件的入侵检测系统为物联网(IoT)设备提供额外的安全保护层。在当今的纵深防御安全战略中，所有可用的安全控制都是串联放置的，旨在保护设备免受恶意网络物理攻击。市场研究估计，到2021年，物联网市场将达到5000亿美元以上，安全被认为是采用物联网的最大障碍之一。这种安全担忧的一个主要原因是物联网设备资源有限，这使得很难应用所有层的安全保护。采用拟议的方法将为物联网设备提供额外的安全层，从而增强摄像头、无人机、传感器和其他设备对物联网设备安全的信心。因此，它可能会引发以前不愿将物联网解决方案应用于其业务的新行业。I-Corps项目应用随机计算(SC)为资源受限的物联网设备提供硬件主机入侵检测系统(HIDS)安全解决方案。目前的物联网安全方法无法为这些资源受限的物联网设备提供HID解决方案，从而错过了纵深防御安全策略中的一个重要层。所提出的方法利用了SC的两个显著特性：1)消耗较少的硅面积和功耗；2)SC和HID本质上都是概率的。SC是从可以使用简单硬件块执行复杂数学运算的常规数字系统概率地产生的。该方法为物联网设备提供了基于简单硬件的HID，并结合机器学习神经网络算法。再加上密码、访问控制等其他安全层，这一轻量级硬件解决方案为资源受限的物联网设备提供了强大的安全性。嵌入在物联网设备中的这款HID监控传入的数据包是否有任何恶意活动，并提供最后一层重要的安全防御。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is to provide an extra layer of security protection for Internet of Things (IoT) devices by using a novel hardware-based intrusion detection system. In today's defense-in-depth security strategy, all available security controls are placed in series aiming to protect a device from malicious cyber-physical attack. Market research estimates that the IoT market will reach over $500B by 2021 and security is considered one of the biggest barriers in adopting IoT. One main reason of this security concern is due to the limited resource of IoT devices that makes it difficult to apply all layers of security protections. The adoption of the proposed approach will provide additive security layer to the IoT devices that will boost the confidence in IoT device security in cameras, drones, sensors and others. Consequently, it may induce new industries which have previously been reluctant to apply IoT solutions to their businesses. Due to the small resource occupation of the proposed device security, even non-IoT industries may apply the proposed approach to their security applications.This I-Corps project applies Stochastic Computing (SC) to provide hardware Host Intrusion Detection System (HIDS) security solution for resource limited IoT devices. Current approaches to IoT security cannot provide HIDS solution to these resource constraint IoT devices, thereby missing out from one of the important layers in defense-in-depth security strategy. The proposed approach exploited two salient properties of SC: 1) consumption of less silicon area and power, 2) both SC and HIDS are inherently probabilistic in nature. SC is generated probabilistically from conventional number system that can perform complex mathematical operation using simple hardware blocks. The proposed approach provides IoT devices with HIDS based on simple hardware together with Machine Learning Neural Network Algorithm. Coupled with other security layers such as cryptography, access control etc., this light weight hardware solution provides strong security to the resource limited IoT devices. Embedded inside the IoT device, this HIDS monitors the incoming packets for any malicious activity and offers the last important layer of security defense.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.