Collaborative Research: SaTC: CORE: Medium: ONSET: Optics- enabled Network Defenses for Extreme Terabit DDoS Attacks

协作研究：SaTC：核心：中：ONSET：针对极端太比特 DDoS 攻击的光学网络防御

• 批准号: 2132651
• 负责人: Ramakrishnan Durairajan
• 金额: $ 40万
• 依托单位: University of Oregon Eugene
• 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: 2022-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2132651&HistoricalAwards=false
• 关键词: Collaborative; Research; SaTC; CORE; Medium

Distributed Denial of Service (DDoS) attacks continue to present a clear and imminent danger to critical network infrastructures. DDoS attacks have increased in sophistication with advanced strategies to continuously adapt (e.g., changing threat postures dynamically) and induce collateral damage (i.e., higher latency and loss for legitimate traffic). Furthermore, advanced attacks may also employ reconnaissance (e.g., mapping the network to find bottleneck links) to target the network infrastructure itself. In light of these trends, state-of-art defenses (e.g., advanced scrubbing, emerging software-defined defenses, and programmable switching hardware) have fundamental shortcomings. This project will develop a new framework, referred to as "Optics-enabled In-Network defenSe for Extreme Terabit DDoS attacks" (ONSET). The framework makes a case for new dimensions of defense agility that can programmatically control the topology of the network (in addition to the processing behavior) to tackle advanced and future attacks. The project will facilitate the use of optical technologies as an exciting visual medium for engaging K-12 students via suitable channels for dissemination. The project will also result in new course materials at the intersection of optical networking, software-defined networking, and network security to enable students to become domain experts in this emerging problem space. The project will take an interdisciplinary approach spanning security, optics, systems, and networks, to address fundamental challenges along three thrusts: (1) novel "data plane" solutions to rapidly reconfigure the wavelengths and switches and new capabilities in programmable switches to rapidly identify malicious vs. benign traffic at line rate; (2) novel "control plane" orchestration mechanisms for scalable resource management algorithms and coordinated control across optical networking and programmable switches; and (3) new "northbound application programming interfaces (APIs)" to express novel defenses to combat current and future DDoS attacks (e.g., with reconnaissance). This project will develop a new framework, referred to as "Optics-enabled In-Network defenSe for Extreme Terabit DDoS attacks" (ONSET). The research efforts will result in end-to-end prototypes using open-source and standardized interfaces to demonstrate the novel defense capabilities of ONSET. The efficacy of ONSET will be evaluated using pilot studies on operational networks to create a roadmap to practical deployment, using real testbeds and large-scale simulations. The project outcomes will be released as open-source software tools, models, and simulation frameworks that will inform industry and academic work.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.

分布式拒绝服务（DDoS）攻击继续给关键的网络基础设施带来明显和迫在眉睫的危险。DDoS攻击越来越复杂，采用先进的策略来不断适应（例如，动态改变威胁姿态）并引起附带损害（例如，更高的延迟和合法流量的损失）。此外，高级攻击还可能采用侦察（例如，映射网络以找到瓶颈链接）来瞄准网络基础设施本身。鉴于这些趋势，最先进的防御（例如，先进的清洗、新兴的软件定义防御和可编程交换硬件）具有根本的缺点。该项目将开发一个新框架，称为“针对极端太比特DDoS攻击的光纤网络防御”（ONSET）。该框架提出了防御敏捷性的新维度，可以通过编程控制网络拓扑（除了处理行为之外）来应对高级和未来的攻击。该项目将促进使用光学技术作为一种令人兴奋的视觉媒介，通过适当的渠道传播，吸引K-12学生。该项目还将产生光网络、软件定义网络和网络安全交叉领域的新课程材料，使学生成为这一新兴问题领域的专家。该项目将采用跨学科的方法，涵盖安全、光学、系统和网络，以解决以下三个方面的基本挑战：(1)新颖的“数据平面”解决方案，快速重新配置波长和交换机，以及可编程交换机的新功能，以线路速率快速识别恶意与良性流量；(2)新型“控制平面”编排机制，用于可扩展的资源管理算法和跨光网络和可编程交换机的协调控制；(3)新的“北向应用程序编程接口（api）”，以表达对抗当前和未来DDoS攻击的新防御（例如，侦察）。该项目将开发一个新框架，称为“针对极端太比特DDoS攻击的光纤网络防御”（ONSET）。研究工作将产生端到端原型，使用开源和标准化接口来演示攻击的新型防御能力。启动的有效性将通过对运营网络的试点研究进行评估，以创建实际部署的路线图，使用真实的测试平台和大规模模拟。项目成果将作为开源软件工具、模型和仿真框架发布，为工业和学术工作提供信息。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

Improving Scalability in Traffic Engineering via Optical Topology Programming

• DOI: 10.1109/tnsm.2023.3335898
• 发表时间: 2024-04
• 期刊: IEEE Transactions on Network and Service Management
• 影响因子: 5.3
• 作者: Matthew Nance-Hall;P. Barford;Klaus-Tycho Foerster;Ramakrishnan Durairajan

Dynamic Scheduling of Approximate Telemetry Queries

• 发表时间: 2022
• 作者: Chris Misa;Walt O'Connor;Ramakrishnan Durairajan;R. Rejaie;Walter Willinger

DynATOS+: A Network Telemetry System for Dynamic Traffic and Query Workloads

• 期刊: IEEE/ACM Transactions on Networking
• 作者: Chris Misa;Ramakrishnan Durairajan;R. Rejaie