The internet has become an essential part of most people's daily lives in recent years, and as more devices connect to the internet, the risk of cyber threats increases dramatically. As malware becomes more sophisticated, traditional security prevention measures are becoming less effective at defending from cyber attacks. As a result, Signature Based Detection and Anomaly Detection are two of many advanced techniques that have become crucial to defend against cyber threats such as malware, but even these are sometimes not enough to stop modern cyberattacks. In this literature review the goal is to discuss how trustworthy each of the mentioned malware detection techniques are at detecting malware in wireless networks. The study will measure trustworthiness by looking further into scalability, adaptability and robustness and resource consumption. This study concludes that both anomaly and signature-based malware detection methods exhibit strengths and weaknesses in scalability, robustness, adaptability, and resource consumption. Furthermore, more research is needed and as malware becomes more sophisticated and an increased threat to the world it is an area that is highly relevant.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:su-219693 |
| Date | January 2023 |
| Creators | Spångberg, Josephine, Mikelinskas, Vainius |
| Publisher | Stockholms universitet, Institutionen för data- och systemvetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| 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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