STTR Phase I: Stochastic Computing Host Intrusion Detection System (HIDS) for IoT devices

STTR 第一阶段：用于物联网设备的随机计算主机入侵检测系统 (HIDS)

• 批准号: 1956291
• 负责人: Kazi Ahmed
• 金额: $ 22.44万
• 依托单位: SECUTOPIA CORPORATION
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1956291&HistoricalAwards=false
• 关键词: STTR; Phase; Stochastic; Computing; Host

The broader impact of this Small Business Technology Transfer (STTR) Phase I project will result from providing a new additional layer of security protection for Internet of Things (IoT) devices by using a novel hardware-based intrusion detection system. Security remains a challenge with most IoT devices, mainly due to the resource-constrained nature of these devices – limited power, computing power and memory. The proposed approach will provide an additional IoT security layer by enabling the detection of anomalous behavior in such devices, encouraging adoption in many new applications. This Small Business Technology Transfer (STTR) Phase I project employs Stochastic Computing (SC) in a hardware-based Host Intrusion Detection System (HIDS) security solution for IoT devices. Current approaches to IoT security are unable to provide HIDS capability due to the resource constrained nature of such devices. As a result, anomalous behavior may go undetected. The proposed approach exploits two salient properties of SC: (i) low power and silicon area requirements, and (ii) the inherently probabilistic nature, enabling a HIDS for IoT devices by using a combination of SC hardware and a Neural Network to monitor incoming packets for malicious activity. This project will develop, train and test an SC-based HIDS for industrial drones.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.

该小型企业技术转让 (STTR) 第一阶段项目的更广泛影响将通过使用新型的基于硬件的入侵检测系统为物联网 (IoT) 设备提供新的附加安全保护层。对于大多数物联网设备来说，安全性仍然是一个挑战，这主要是由于这些设备的资源受限性质——有限的功率、计算能力和内存。 所提出的方法将通过检测此类设备中的异常行为来提供额外的物联网安全层，从而鼓励在许多新应用中采用。该小型企业技术转让 (STTR) 第一阶段项目在针对物联网设备的基于硬件的主机入侵检测系统 (HIDS) 安全解决方案中采用了随机计算 (SC)。由于此类设备的资源有限性质，当前的物联网安全方法无法提供 HIDS 功能。因此，异常行为可能不会被发现。所提出的方法利用了 SC 的两个显着特性：(i) 低功耗和硅面积要求，以及 (ii) 固有的概率性质，通过使用 SC 硬件和神经网络的组合来监控传入数据包是否存在恶意活动，从而为物联网设备启用 HIDS。该项目将为工业无人机开发、训练和测试基于 SC 的 HIDS。该奖项反映了 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。