With the growing scale of the IoT, many industries enjoy the benefit of automation. The IoT consists of an interconnected network of devices that sense their surroundings and share data among other IoT devices. However, this data can be sensitive and private in nature, making security within the ever-growing IoT network a high priority. Because of the constrained nature of IoT devices, namely limited computing power, memory and energy, classical cryptographic solutions are not desired. Furthermore, current IoT frameworks are heavily centralised around central servers which can result in single points of failure in the case of DoS attacks. Because of these drawbacks, the emerging blockchain technology is seen as a potential solution to these problems. A blockchain is a distributed ledger that is able to keep an immutable list of transactions occurring in a network. The purpose of this research is to compare blockchain-based frameworks for mitigating DDoS and Sybil attacks in the IoT by comparing proposed blockchain-based frameworks. Qualitative evaluation of proposed frameworks suggests that there are several strategies to improve security within the IoT. Blockchain, in addition to other technologies such as SDN, can provide effective mitigation of DDoS attacks and Sybil attacks. However, there is limited quantitative test data available and further research is required in this novel field of research.

Blockchain is a technology that is in use increasingly. Although owing its common use to the cryptocurrencies there is more to the blockchain technology than just the monetary use. One of these uses is by smaller groups of participants under the control of a central authority, for instance at a company. Such private blockchains use permissioned blockchain consensus algorithms as the participants need the permission of the authority to be able to join the system. This paper will give an overview of the blockchain technology, investigate permissioned and permissionless blockchain, and focus on permissioned blockchains to analyze it in terms of, e.g. trust models between the nodes, incentives, number of nodes & parties involved, and scalability regarding the number of transactions.