SunBlock:为物联网系统提供无云保护

Vadim Safronov, A. Mandalari, Daniel J. Dubois, D. Choffnes, Hamed Haddadi
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引用次数: 0

摘要

随着家庭中物联网(IoT)设备的日益增多,潜在的信息泄漏渠道及其相关的安全威胁和隐私风险也随之增加。尽管针对未受保护的家庭网络中的物联网设备的攻击由来已久,但准确、快速地检测和预防此类攻击的问题仍未解决。许多现有的物联网保护解决方案都是基于云的,有时效果不佳,而且可能会与未知的第三方共享消费者数据。本文将人工智能工具与基于规则的经典流量过滤算法相结合,研究了在家用路由器上本地有效检测物联网威胁的潜力。我们的研究结果表明,在机器学习和流量过滤逻辑略微增加路由器硬件资源的情况下,采用我们的解决方案的典型家用路由器能够有效检测风险并保护典型的家庭物联网网络,其性能等同于或优于现有的流行解决方案,而且不会对良性物联网功能造成任何影响,也无需依赖云服务和第三方。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SunBlock: Cloudless Protection for IoT Systems
With an increasing number of Internet of Things (IoT) devices present in homes, there is a rise in the number of potential information leakage channels and their associated security threats and privacy risks. Despite a long history of attacks on IoT devices in unprotected home networks, the problem of accurate, rapid detection and prevention of such attacks remains open. Many existing IoT protection solutions are cloud-based, sometimes ineffective, and might share consumer data with unknown third parties. This paper investigates the potential for effective IoT threat detection locally, on a home router, using AI tools combined with classic rule-based traffic-filtering algorithms. Our results show that with a slight rise of router hardware resources caused by machine learning and traffic filtering logic, a typical home router instrumented with our solution is able to effectively detect risks and protect a typical home IoT network, equaling or outperforming existing popular solutions, without any effects on benign IoT functionality, and without relying on cloud services and third parties.
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