OAC Core: MedKnights - Towards Secure and Flexible Medical IoT (IoMT) Infrastructure using Generative Adversarial Networks

OAC 核心：MedKnights - 使用生成对抗网络实现安全灵活的医疗物联网 (IoMT) 基础设施

• 批准号: 2212424
• 负责人: Tamer Nadeem
• 金额: $ 59.99万
• 依托单位: Virginia Commonwealth University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2212424&HistoricalAwards=false
• 关键词: OAC; Core; MedKnights; Towards; Secure

With growing healthcare demands, the Internet of Medical Things (IoMT) has grown significantly in recent years and is dominating the healthcare industry. However, these smarter and advanced medical devices are very complicated in terms of software and hardware, with defects and vulnerabilities that are found regularly and they are also vulnerable to possible malicious attacks. Healthcare organizations are the new focus of attackers for carrying out IoMT-focused cyberattacks, which are becoming more common. In recent years, ransomware and distributed denial of service (DDoS) attacks are malware-based popular attacks on IoMT devices. Cyberattacks and disruptions in clinical care can have a catastrophic effect on patient safety, which trickles down to the medical staff’s responsiveness. Moreover, because different medical devices have varying vital capabilities, it is critical to enable differentiated network services for these devices with varying critical levels of operation under varying network dynamics. Hence it is crucial to efficiently detect and identify any malicious network activities to eliminate or minimize the impact of these attacks, as well as to detect and identify network traffic belonging to different medical devices.The MedKnights project will extend knowledge in networking, machine learning, and the digital forensic domains in developing a holistic framework that can be deployed at the network edge components and effectively support different fine-grained security services for IoMT networks and devices. The main objectives of the project include: (1) creating a novel medical device testbed, IoMT network traffic datasets, IoMT device behavior signature datasets, and attack datasets; (2) employing generative adversarial networks (GANs) to identify many of the interesting features for medical networks and devices, to perform multi-class classification, automatic feature extraction, and be robust to noise, support drifts in networks, and support continual learning for new devices for securing IoMT networks and devices; and (3) enabling remote memory forensic capabilities for IoMT devices. The project will also carry out a number of educational activities involving K-12, undergraduate, and graduate students, make strong outreach efforts for recruiting and mentoring students from underrepresented groups, as well as enrich undergraduate and graduate curricula through exposing students to cutting-edge research in networking, security, and machine learning. In addition, multiple industrial collaborations are expected within the scope of the project.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.

随着医疗保健需求的不断增长，医疗物联网（IoMT）近年来显着增长，并在医疗保健行业占据主导地位。然而，这些更智能、更先进的医疗设备在软件和硬件方面都非常复杂，存在缺陷和漏洞。近年来，勒索软件和分布式拒绝服务 (DDoS) 攻击变得越来越常见，医疗机构也成为攻击者实施以 IoMT 为重点的网络攻击的新焦点。针对 IoMT 设备的基于恶意软件的流行攻击可能会对患者安全造成灾难性影响，进而影响到医务人员的响应能力。此外，由于不同的医疗设备具有不同的重要功能，因此实现差异化至关重要。这些设备的网络服务在不同的网络动态下具有不同的关键操作级别，因此有效检测和识别任何恶意网络活动以消除或最小化这些攻击的影响以及检测和识别属于这些攻击的网络流量至关重要。不同的医疗设备。 MedKnights 项目将扩展网络、机器学习和数字取证领域的知识，开发一个可部署在网络边缘组件的整体框架，并有效支持 IoMT 网络和设备的不同细粒度安全服务。项目包括：(1) 创建新型医疗设备测试平台、IoMT 网络流量数据集、IoMT 设备行为特征数据集和攻击数据集；(2) 采用生成对抗网络 (GAN) 来识别许多有趣的特征；医疗网络和设备，执行多类分类、自动特征提取，并对噪声具有鲁棒性，支持网络漂移，并支持新设备的持续学习，以保护 IoMT 网络和设备；(3) 启用远程内存取证功能；该项目还将开展一系列涉及 K-12、本科生和研究生的教育活动，大力招募和指导来自代表性不足群体的学生，并通过接触学生来丰富本科生和研究生课程。到此外，该项目预计将在网络、安全和机器学习领域开展多项前沿研究。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评估，被认为值得支持。影响审查标准。

项目成果

iKnight–Guarding IoT Infrastructure Using Generative Adversarial Networks

iKnight — 使用生成对抗网络保护物联网基础设施

• DOI: 10.1109/access.2022.3224583
• 发表时间: 2022-01
• 期刊: IEEE Access
• 影响因子: 3.9
• 作者: Nukavarapu, Santosh;Nadeem, Tamer
• 通讯作者: Nadeem, Tamer

MirageNet - Towards a GAN-based Framework for Synthetic Network Traffic Generation

MirageNet - 迈向基于 GAN 的合成网络流量生成框架

• 发表时间: 2022-12
• 期刊: IEEE Global Communications Conference 2022
• 作者: Nukavarapu, Santosh K.;Ayyat, M.;Nadeem, T.
• 通讯作者: Nadeem, T.

Dynamic Deep Neural Network Adversarial Attacks for Edge-based IoT Devices

针对基于边缘的物联网设备的动态深度神经网络对抗攻击

• 发表时间: 2022-12
• 期刊: IEEE Global Communications Conference 2022
• 作者: Ayyat, M.;Nukavarapu, Santosh K.;Nadeem, T.
• 通讯作者: Nadeem, T.