Security and privacy of users have become significant concerns due to the involvement of the Internet of Things (IoT) devices in numerous applications. Cyber threats are growing at an explosive pace making the existing security and privacy measures inadequate. Hence, everyone on the Internet is a product for hackers. Consequently, Machine Learning (ML) algorithms are used to produce accurate outputs from large complex databases, where the generated outputs can be used to predict and detect vulnerabilities in IoT-based systems. Furthermore, Blockchain (BC) techniques are becoming popular in modern IoT applications to solve security and privacy issues. Several studies have been conducted on either ML algorithms or BC techniques. However, these studies target either security or privacy issues using ML algorithms or BC techniques, thus posing a need for a combined survey on efforts made in recent years addressing both security and privacy issues using ML algorithms and BC techniques. In this article, we provide a summary of research efforts made in the past few years, from 2008 to 2019, addressing security and privacy issues using ML algorithms and BC techniques in the IoT domain. First, we discuss and categorize various security and privacy threats reported in the past 12 years in the IoT domain. We then classify the literature on security and privacy efforts based on ML algorithms and BC techniques in the IoT domain. Finally, we identify and illuminate several challenges and future research directions using ML algorithms and BC techniques to address security and privacy issues in the IoT domain.

中文翻译：

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使用机器学习和区块链的物联网安全和隐私

由于物联网 (IoT) 设备在众多应用中的参与，用户的安全和隐私已成为重要问题。网络威胁正以爆炸性的速度增长，使得现有的安全和隐私措施不足。因此，互联网上的每个人都是黑客的产物。因此，机器学习 (ML) 算法用于从大型复杂数据库生成准确的输出，其中生成的输出可用于预测和检测基于物联网的系统中的漏洞。此外，区块链 (BC) 技术在现代物联网应用中越来越流行，以解决安全和隐私问题。已经对 ML 算法或 BC 技术进行了几项研究。然而，这些研究使用 ML 算法或 BC 技术针对安全或隐私问题，因此需要对近年来使用 ML 算法和 BC 技术解决安全和隐私问题所做的努力进行综合调查。在本文中，我们总结了过去几年（从 2008 年到 2019 年）在物联网领域使用机器学习算法和 BC 技术解决安全和隐私问题的研究工作。首先，我们讨论和分类了过去 12 年中物联网领域报告的各种安全和隐私威胁。然后，我们根据物联网领域的机器学习算法和 BC 技术对有关安全和隐私工作的文献进行分类。最后，我们使用 ML 算法和 BC 技术确定并阐明了几个挑战和未来的研究方向，以解决物联网领域的安全和隐私问题。