Today the digital evolution is progressing rapidly. This entails both pros and cons concerning the security of devices. Despite the evolution, security has been left in the dark. This results in threats and vulnerabilities in devices, which could potentially be used by a hacker with the purpose of exploiting information. Security has not been a priority in industrial enterprises, even though industrial devices and other networked devices reside on the same network. The evolution of the infrastructure of the Internet has resulted in an increase of cyberattacks. These attacks used to target random individuals. The attacks of today are more intelligent, and hackers have changed their targets to specific enterprises to further exploit sensitive information, damage devices or for financial benefits. Safety in today’s industrial workplaces, such as firewalls, encryption and intrusion detection systems are not specifically designed to work in this type of environment. This leads to new threats and vulnerabilities which further leads to more exploited vulnerabilities. This formulate the following questions: Which are the most occurring threats and vulnerabilities today? What current methods and tools are suited for controlling security in IIoT-networks and its internal industrial devices? The purpose of this thesis was to examine the most occurring threats and vulnerabilities in IIoT-networks and its internal devices and reason among the methods to evaluate security in industrial enterprises. Lastly, an experiment in a real industrial workplace was conducted to attain a nuanced picture of the implementation of finding threats and vulnerabilities in industrial systems. In summary, there are a lot of different threats and vulnerabilities divided into categories and many tools are available to ensure the vulnerability. To conduct a test to find threats and vulnerabilities in an industrial enterprise, it needs to be ethically correct and the consequences carefully considered. The result of this thesis is a mapping and a demonstration of how threats and vulnerabilities are detected in an industrial workplace.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hh-40263 |
| Date | January 2019 |
| Creators | Johnsson, Daniel, Krohn, Lina |
| Publisher | Högskolan i Halmstad, Akademin för informationsteknologi, Högskolan i Halmstad, Akademin för informationsteknologi |
| Source Sets | DiVA Archive at Upsalla University |
| Language | Swedish |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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