Detecting Firmware Vulnerabilities in Smart Home Devices

83%的澳大利亚人拥有智能家居设备。47%的人声称他们有三个或更多。这些设备很容易成为网络攻击的目标，寻找它们的漏洞变得比以往任何时候都更加重要。我们的行业合作伙伴GPG正在积极寻找检测其智能家居产品漏洞的方法，但尚未找到满足三个关键要求的现有方法：1)海量搜索，2)跨平台检测，3)发现看不见的漏洞。因此，我们建议使用一系列新的技术来解决上述挑战，如高效的内存模糊、条件公式和迁移学习。该项目的成果将帮助澳大利亚在漏洞检测方面获得尖端技术。

83% of Australians have smart home devices. 47% claim they have three or more. These devices are easily targeted by cyber-attacks, and searching for their vulnerabilities has become more crucial than ever. Our industry partner GPG is actively looking for ways to detect vulnerabilities in their smart home products, but have not found any existing methods that satisfy three critical requirements: 1) massive search, 2) cross platform detection, and 3) finding unseen vulnerabilities. We therefore propose to use a series of new techniques such as efficient in-memory fuzzing, conditional formulas, and transfer learning to solve the above challenges. The project outcomes will help Australia gain cutting edge techniques in vulnerability detection.