AI-Based Real-Time Fraudulent and Suspicious Activity Detection on Secure Software-Defined Wireless Networks

安全软件定义无线网络上基于人工智能的实时欺诈和可疑活动检测

• 批准号: 10076403
• 金额: $ 6.37万
• 依托单位: CONATIX UK LTD
• 依托单位国家: 英国
• 项目类别: Grant for R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10076403
• 关键词: AI; Based; Real; Time; Fraudulent

The aim of the project AI-Based Real-Time Fraudulent and Suspicious Activity Detection on Secure Software-Defined Wireless Networks is to transplant and adapt Conatix fraud and anomaly detection technology from "conventional" networks to virtual software-defined wireless networks. Once we prove the concept and value in this project, we can then apply the technology to many different specific technical use cases requiring secure wireless networks, such as autonomous vehicles, ships, planes, tanks, remote and outdoor working, isolated locations, emergency disasters and extreme weather conditions, and others.One of the main barriers to market acceptance of autonomous vehicles is the current insecurity and exposure of the wireless networks they depend on. Transport and military are only the leading edge of the market for wireless networks. Virtual software-defined networks can and will further transform business and society with their speed, convenience and value, but the risk of attack especially from within, by "insiders" (must) be reduced before they can be used widely and effectively. This can only be done by capturing and analyzing massive messy unstructured data to model events and behavior at the level of individual users and endpoints rather than at the level of the entire network.Conatix and its team have won numerous innovation awards for applying artificial intelligence to fraud and suspicious activity monitoring on standard enterprise IT networks. The present activity brings this expertise to the leading technical edge of communications networks: secure virtual software-defined wireless networks, on which insider / user-based threats remain the major unaddressed gap in security, and a place where the Conatix massive unstructured streaming continuous data approach is particularly suited to raise the level of protection.All of these things position Conatix to bring our leading edge analytics to the exact platform that requires them now and where they can shine.Our subcontractor and partner iQuila is a leading startup provider of advanced wireless networks who can help Conatix with data availability and field testing to ensure that the prototype(s) resulting from the project work effectively for real-world wireless networking use cases.The project applies AI to provide next gen security for next gen networks and will result in a prototype / minimum viable product AI-based software for increased security on wireless networks, field tested and validated and ready to be fully productized and launched on the market.

安全软件定义无线网络上基于人工智能的实时欺诈和可疑活动检测项目的目的是将Conatix欺诈和异常检测技术从“传统”网络移植和调整到虚拟软件定义无线网络。一旦我们在这个项目中证明了概念和价值，我们就可以将该技术应用于许多需要安全无线网络的不同特定技术用例，例如自动驾驶汽车，船舶，飞机，坦克，远程和户外工作，孤立的位置，紧急灾难和极端天气条件，市场接受自动驾驶汽车的主要障碍之一是它们所依赖的无线网络目前的不安全性和暴露。运输和军事只是无线网络市场的领先优势。虚拟软件定义网络能够并将以其速度、便利性和价值进一步改变商业和社会，但在广泛有效地使用之前，必须降低“内部人员”的攻击风险，特别是来自内部的攻击风险。这只能通过捕获和分析大量杂乱的非结构化数据来实现，从而在单个用户和端点级别（而不是整个网络级别）对事件和行为进行建模。Conatix及其团队因将人工智能应用于标准企业IT网络的欺诈和可疑活动监控而赢得了众多创新奖项。目前的活动将这种专业知识带到了通信网络的领先技术优势：安全的虚拟软件定义的无线网络，其中基于内部人员/用户的威胁仍然是安全性方面的主要未解决差距，Conatix的大规模非结构化流连续数据方法特别适合于提高保护级别。所有这些都使Conatix能够将我们领先的分析技术带到我们的分包商和合作伙伴iQuila是先进无线网络的领先初创供应商，可以帮助Conatix提供数据可用性和现场测试，以确保项目产生的原型在真实的环境中有效工作-世界无线网络用例。该项目应用人工智能为下一代网络提供下一代安全，并将产生一个原型/最小可行产品基于AI的软件，用于提高无线网络的安全性，经过现场测试和验证，准备全面产品化并投放市场。