CAREER: Proactive Techniques for Enhancing Security and Resilience of Mobile Communication Infrastructure

职业：增强移动通信基础设施安全性和弹性的主动技术

• 批准号: 1943079
• 负责人: Guanhua Yan
• 金额: $ 49.89万
• 依托单位: SUNY at Binghamton
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1943079&HistoricalAwards=false
• 关键词: CAREER; Proactive; Techniques; Enhancing; Security

The 5G networks currently being rolled out globally are expected to revolutionize a wide spectrum of application domains, including, but not limited to, automotive, healthcare, smart cities, factories, and first responders. This project seeks to enhance the security and resilience of the next-generation mobile communication networks against threats that may cause infrastructure-level damages. First, the ease of distributing mobile applications from marketplaces (e.g., Google Play and Apple App Store) and the growing popularity of IoT (Internet-of-Things) devices have made it possible to construct large botnets capable of attacking critical infrastructures. Second, both insider threats (e.g., disgruntled former employees) and unintentional human errors (e.g., network misconfiguration) can cause widespread cellular service failures. Third, virtualization of 5G core network services makes them attractive targets for APT (Advanced Persistent Threat) attackers who covet sensitive user data, such as mobile users' account information, locations, and private keys. The successful execution of this project will not only produce tools that can protect the Nation's mobile communication infrastructures but also train students from diverse backgrounds for jobs in critical infrastructure protection.The main goal of this CAREER project is to develop three-layered, proactive defenses for the next-generation mobile communication infrastructures. The first layer of defense will provide infrastructure-level accountability support to deter potential attackers because their attack origins can be traced from observable network events with high accuracy. The second layer will use real-time machine learning techniques enhanced with knowledge of communication protocol specifications to identify anomalous activities. These anomaly detection methods will be designed with robustness against adversarial manipulations such as model poisoning and evasion attacks. The third layer of defense will focus on diverting attackers who have successfully penetrated into the mobile communication infrastructures to deceptive environments, where their attack capabilities, intentions, and origins can be revealed. This CAREER project will engage 5G infrastructure stakeholders in improving the security and resilience of their mobile network operations. Its research activities will involve undergraduates and under-represented minority students.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.

目前在全球范围内推出的5G网络预计将彻底改变广泛的应用领域，包括但不限于汽车、医疗保健、智能城市、工厂和急救人员。该项目旨在增强下一代移动通信网络的安全性和弹性，以应对可能造成基础设施级破坏的威胁。首先，从市场（例如b谷歌Play和Apple App Store）分发移动应用程序的便利性以及物联网（IoT）设备的日益普及使得构建能够攻击关键基础设施的大型僵尸网络成为可能。其次，内部威胁（例如，心怀不满的前雇员）和无意的人为错误（例如，网络配置错误）都可能导致广泛的蜂窝服务故障。第三，5G核心网服务的虚拟化使其成为APT（高级持续威胁）攻击者的诱人目标，这些攻击者觊觎敏感的用户数据，如移动用户的账户信息、位置和私钥。该项目的成功实施不仅将产生能够保护国家移动通信基础设施的工具，还将培养来自不同背景的学生从事关键基础设施保护工作。CAREER项目的主要目标是为下一代移动通信基础设施开发三层主动防御。第一层防御将提供基础设施级别的责任支持，以阻止潜在的攻击者，因为他们的攻击起源可以从可观察的网络事件中以高精度跟踪。第二层将使用实时机器学习技术，增强通信协议规范知识，以识别异常活动。这些异常检测方法将被设计成对对抗性操作（如模型中毒和逃避攻击）具有鲁棒性。第三层防御将侧重于将成功渗透到移动通信基础设施的攻击者转移到欺骗性环境，在那里他们的攻击能力、意图和来源可以被揭示。该CAREER项目将使5G基础设施利益相关者参与改善其移动网络运营的安全性和弹性。它的研究活动将涉及本科生和少数族裔学生。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

VET5G: A Virtual End-to-End Testbed for 5G Network Security Experimentation

VET5G：用于 5G 网络安全实验的虚拟端到端测试平台

• DOI: 10.1145/3546096.3546111
• 发表时间: 2022
• 期刊: The 15th Workshop on Cyber Security Experimentation and Test
• 作者: Wen, Zhixin;Pacherkar, Harsh Sanjay;Yan, Guanhua
• 通讯作者: Yan, Guanhua

IoTInfer: Automated Blackbox Fuzz Testing of IoT Network Protocols Guided by Finite State Machine Inference

• DOI: 10.1109/jiot.2022.3182589
• 发表时间: 2022-11
• 期刊: IEEE Internet of Things Journal
• 影响因子: 10.6
• 作者: Zhan Shu;Guanhua Yan