The Internet of Things (IoT) represents a new technology that enables both virtual and physical objects to be connected and communicate with each other, and produce new digitized services that improve our quality of life. The IoT system provides several advantages, however, the current centralized architecture introduces numerous issues involving a single point of failure, security, privacy, transparency, and data integrity. These challenges are an obstacle in the way of the future developments of IoT applications. Moving the IoT into one of the distributed ledger technologies may be the correct choice to resolve these issues. Among the common and popular types of distributed ledger technologies is the blockchain. Integrating the IoT with blockchain technology can bring countless benefits. Therefore, this paper provides a comprehensive discussion of integrating the IoT system with blockchain technology. After providing the basics of the IoT system and blockchain technology, a thorough review of integrating the blockchain with the IoT system is presented by highlighting benefits of the integration and how the blockchain can resolve the issues of the IoT system. Then, the blockchain as a service for the IoT is presented to show how various features of blockchain technology can be implemented as a service for various IoT applications. This is followed by discussing the impact of integrating artificial intelligence (AI) on both IoT and blockchain. In the end, future research directions of IoT with blockchain are presented.

Internet of Things (IoT) forms the foundation of next generation infrastructures, enabling development of future cities that are inherently sustainable. Intrusion detection for such paradigms is a non-trivial challenge which has attracted further significance due to extraordinary growth in the volume and variety of security threats for such systems. However, due to unique characteristics of such systems i.e., battery power, bandwidth and processor overheads and network dynamics, intrusion detection for IoT is a challenge, which requires taking into account the trade-off between detection accuracy and performance overheads. In this context, we are focused at highlighting this trade-off and its significance to achieve effective intrusion detection for IoT. Specifically, this paper presents a comprehensive study of existing intrusion detection systems for IoT systems in three aspects: computational overhead, energy consumption and privacy implications. Through extensive study of existing intrusion detection approaches, we have identified open challenges to achieve effective intrusion detection for IoT infrastructures. These include resource constraints, attack complexity, experimentation rigor and unavailability of relevant security data. Further, this paper is envisaged to highlight contributions and limitations of the state-of-the-art within intrusion detection for IoT, and aid the research community to advance it by identifying significant research directions.

The connected or smart environment is the integration of smart devices (sensors, IoT devices, or actuator) into the Internet of Things (IoT) paradigm, in which a large number of devices are connected, monitoring the physical environment and processes and transmitting into the centralized database for advanced analytics and analysis. This integrated and connected setup allows greater levels of automation of smart systems than is possible with just the Internet. While delivering services to the different processes and application within connected smart systems, these IoT devices perform an impeccably large number of device-to-device communications that allow them to access the selected subsets of device information and data. The sensitive and private nature of these data renders the smart infrastructure vulnerable to copious attacks which threat agents exploit for cyberattacks which not only affect critical services but probably bring threat to people’s lives. Hence, advanced measures need to be taken for securing smart environments, such as dynamic access control, advanced network screening, and monitoring behavioural anomalies. In this paper, we have discussed the essential cyberthreats and vulnerabilities in smart environments and proposed ZAIB (Zero-Trust and ABAC for IoT using Blockchain), a novel secure framework that monitors and facilitates device-to-device communications with different levels of access-controlled mechanisms based on environmental parameters and device behaviour. It is protected by zero-trust architecture and provides dynamic behavioural analysis of IoT devices by calculating device trust levels for each request. ZAIB enforces variable policies specifically generated for each scenario by using attribute-based access control (ABAC). We have used blockchain to ensure anonymous device and user registrations and immutable activity logs. All the attributes, trust level histories, and data generated by IoT devices are protected using IPFS. Finally, a security evaluation shows that ZAIB satisfies the needs of active defence and end-to-end security enforcement of data, users, and services involved in a smart grid network.

Blockchain technology has gained significant attention in recent years for its potential to revolutionize various sectors, including finance, supply chain management, and digital forensics. While blockchain’s decentralization enhances security, it complicates the identification and tracking of illegal activities, making it challenging to link blockchain addresses to real-world identities. Also, although immutability protects against tampering, it introduces challenges for forensic investigations as it prevents the modification or deletion of evidence, even if it is fraudulent. Hence, this paper provides a systematic literature review and examination of state-of-the-art studies in blockchain forensics to offer a comprehensive understanding of the topic. This paper provides a comprehensive investigation of the fundamental principles of blockchain forensics, exploring various techniques and applications for conducting digital forensic investigations in blockchain. Based on the selected search strategy, 46 articles (out of 672) were chosen for closer examination. The contributions of these articles were discussed and summarized, highlighting their strengths and limitations. This paper examines the selected papers to identify diverse digital forensic frameworks and methodologies used in blockchain forensics, as well as how blockchain-based forensic solutions have enhanced forensic investigations. In addition, this paper discusses the common applications of blockchain-based forensic frameworks and examines the associated legal and regulatory challenges encountered in conducting a forensic investigation within blockchain systems. Open issues and future research directions of blockchain forensics were also discussed. This paper provides significant value for researchers, digital forensic practitioners, and investigators by providing a comprehensive and up-to-date review of existing research and identifying key challenges and opportunities related to blockchain forensics.