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The use of Internet-of-Things (IoT) makes it possible to inter-connect Information Technology (IT) and Operational Technology (OT) into a completely new system. This convergence is often known as Industrial IoT (IIoT). IIoT brings a lot of benefits to industrial assets, such as improved efficiency and productivity, reduced cost, and depletion of human error. However, the high inter-connectivity opens new possibilities for cyber incidents. These incidents can cause major damage like halting of production on the manufacturing line, or catastrophic havoc to companies, communities, and countries causing power outages, floods, and fuel shortages. Such incidents are important to be predicted, stopped, or alleviated at no cost. Moreover, these incidents are a great motive for researchers and practitioners to investigate known security problems and find potential moderation strategies.  In this thesis work, we try to identify what types of IIoT systems have been investigated in the literature. We seek out to find if software-related issues can yield security problems. Also, we make an effort to perceive what are the proposed methods to mitigate the security threats.We employ the systematic literature review (SLR) methodology to collect this information. The results are gathered from papers published in the last five years and they show an increased interest in research in this domain. We find out software vulnerabilities are a concern for IIoT systems, mainly firmware vulnerabilities and buffer overflows, and there are a lot of likely attacks that can cause damage, mostly injection and DDoS attacks. There are a lot of different solutions which offer the possibility to stop the identified problems and we summarize them. Furthermore, the research gap considering the update process in these systems and devices, as well as a problem with the unsupervised software supply chain is identified.