SecFob: A Remote Keyless Entry Security Solution
SecFob: A Remote Keyless Entry Security Solution
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DOI：
10.1109/isc257844.2023.10293400
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发表时间：
2023-09
期刊：
影响因子：
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通讯作者：
Braxton Bolt;Hoda Maleki;Gagan Agrawal;Jeffrey D. Morris;Khan Farabi
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文献类型：
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作者：
Braxton Bolt;Hoda Maleki;Gagan Agrawal;Jeffrey D. Morris;Khan Farabi
所有主要供应商目前都为乘用车提供遥控无钥匙进入（RKE）系统，这已成为现代汽车的标准功能。这些系统实现了驾驶员和车辆之间的无线通信，方便了远程启动和被动无钥匙进入等功能。不幸的是，这些系统中实施的现有安全措施往往不足，使它们容易受到入侵和各种攻击。为了解决这些漏洞，我们提出了SecFob，这是一种结合了量子随机数生成（QRNG）、机器学习和加密技术的解决方案。SecFob旨在通过利用QRNG提供的完美熵并结合机器学习技术，特别是利用Siamese神经网络来防御常见的攻击技术。这些解决方案具有成本效益，便携式，并且使用ML技术，能够检测放大信号。
All major vendors currently offer Remote Keyless Entry (RKE) systems for passenger vehicles, which have become a standard feature of modern cars. These systems enable wireless communication between drivers and vehicles, facilitating convenient functions such as remote start and passive keyless entry. Unfortunately, the existing security measures implemented in these systems are often inadequate, leaving them vulnerable to intrusions and a wide array of attacks. To address these vulnerabilities, we present SecFob, a solution that combines quantum random number generation (QRNG), machine learning, and encryption techniques. SecFob is designed to defend against common attack techniques by leveraging the perfect entropy offered by QRNG and by incorporating machine learning techniques, specifically utilizing the Siamese Neural Network. These solutions are cost-effective, portable, and with the use of ML technique, are able to detect amplified signals.