The need for improving the security level of IoT systems is growing. Users may refrain from using such systems if they realize that security measures are not in place. In this context, one of the most important IoT components has not received the necessary attention by the community: the gateway. IoT gateways play a central role in an IoT system as they solve heterogeneity issues. However, if compromised, gateways can be a source of security threats, and these threats become more relevant due to the gateway’s central role. Gateways connect IoT devices and cloud services, and successful attacks on this component may exploit this fact. Using a well-known security requirements engineering approach, this paper evaluates and prioritizes security requirements specifically for IoT gateways. The prioritization highlights a set of security requirements that must be observed when evaluating and improving the gateway security level. Also, current solutions are detailed to support the enforcement of such security requirements. Finally, a set of open challenges are discussed to highlight current research gaps that must be addressed to support security requirements.

The growth of the Internet of Things (IoT) has provided significant advances in several areas of the industry, but security concerns have also increased due to this expansion. Many IoT devices are the target of cyber attacks due to various firmware, source code, and software vulnerabilities. In this context, static code analysis, leveraging various techniques, has emerged as an effective approach to examine and identify security vulnerabilities, including insecure functions, buffer overflows, and code injection. However, recent research has shown several challenges associated with this approach, such as limited understanding of vulnerabilities, inadequate threat detection, and insufficient semantic analysis of IoT device source code. Consequently, several IoT security research studies integrate static analysis with other methods, such as dynamic analysis, machine learning, and natural language processing, to enhance vulnerability analysis and detection. To provide a comprehensive understanding of the current state of static analysis in IoT security, this systematic literature review explores existing vulnerabilities, techniques, and methods while highlighting the challenges that hinder the extraction of meaningful insights from such analyses.

While IoT systems are increasingly present in different areas of society, ensuring their data’s privacy, security, and inviolability becomes paramount. In this direction, Blockchain has been used to protect the security and immutability of data generated by IoT devices and sensors. At the heart of Blockchain solutions, consensus algorithms are crucial in ensuring the security of creating and writing data in new blocks. Choosing which consensus algorithms to utilise is critical because of a fundamental tradeoff between their security strength and response time. However, recent surveys of consensus mechanisms for IoT-based Blockchain focused on individually using and analysing these algorithms. Investigating the integration between these algorithms to address IoT-specific requirements better is a promising approach. In this context, this paper presents a literature review that explains and discusses consensus algorithms in IoT environments and their combinations. The review analyses eight dimensions that help understand existing proposals: ease of integration, scalability, latency, throughput, power consumption, configuration issues, integrated algorithms, and adversary tolerance. The final analysis also suggests and discusses open challenges in integrating multiple consensus algorithms considering the particularities of IoT systems.