### Existing Surveys and Our Contributions  
From a general viewpoint, some of the security and privacy issues in IoT have been discussed in [40; 41; 42; 43; 44; 45]. However, these papers primarily survey IoT progress in general covering applications, enabling technologies, architectures, and some security fundamentals. Some of the IoT-related security concerns have been surveyed in Refs. [46; 47] provides a survey on M2M research security, and [47] discusses the challenges and solutions for securing fog computing for IoT applications. In regard to IoT-enabled cyberattacks, the authors in [48] deliver an assessment survey on attack paths to relevant infrastructures and services. Ref. [49] presents a reasonable review of intrusion detection systems for IoT technologies, but the paper mainly focuses on architecture types. Recently, a few reasonable surveys on IoT security [50; 51; 52; 53; 54; 55; 56; 57; 58; 59] have been made available in the literature; however, the spectrum of IoT security is so large that many critical issues and aspects are yet to be investigated. In Table 3, we show a comparative analysis on the scope of our paper with that of the existing surveys. [PERSON] et al. [59] divided the IoT attacks into five different layered architectures and presents security issues of each layer with the security measures and mechanisms to defeat these attacks. However, a more useful classification of the prominent IoT attacks based on other parameters, such as devices' properties and severity level, may help us to better understand and analyze the exiting security problems and mitigation techniques. Similarly, [PERSON] et al. [50] presented different attacks taxonomy based on the different layer of IoT architecture and discusses the use of emerging technologies, such as artificial intelligence and blockchain in mitigating these attacks. Nevertheless, a more comprehensive discussion on IoT attack surface and vulnerabilities of IoT ecosystem is desired. [PERSON] et al. [60] primarily explored the integration of Blockchain and IoT, specifically focusing on energy, security, and hardware aspects. This provided insights into the challenges and opportunities associated with this integration, offering a specialized examination within the mentioned domains. [PERSON] et al. [61] primarily concentrated on bolstering security in cloud manufacturing equipment clusters for Industry 4.0. By leveraging edge-based blockchain and fog computing, they targeted challenges related to privacy, authentication, and overall system performance. In contrast, our work takes a broader approach, systematically analyzing security vulnerabilities across IoT layers and proposing a comprehensive Blockchain-based forensic framework. While both works contribute significantly to IoT security, our research spans a wider spectrum, addressing diverse aspects beyond the specific focus of cloud manufacturing. Another recent work [51] demonstrated the feasibility of using deep-learning-based techniques and provides a taxonomy of the machine-learning-based methods for IoT security. The research also illustrates the common IoT security threats and the attacks surfaces of an IoT ecosystem focusing on the use of machine learning and artificial intelligence. However, the paper does not cover the detailed security requirements needed to ensure secure operational and access model, a very much desirable aspect in IoT security. Then, [PERSON] et al. [52] focused on fundamental challenges, theoretical frameworks, and research trends in the IoT forensics. The authors discuss existing IoT forensics and their usefulness and provide some guidelines to the digital forensics professionals. The research provides a good taxonomy of the attacks on IoT systems, but does not focus on the prospective solutions to mitigate the attacks. [PERSON] [62] proposes an SDN-based