Malware analysis and detection in enterprise systems
| dc.contributor.author | Mokoena, Tebogo | |
| dc.contributor.co-supervisor | Harmse, Anneke | |
| dc.contributor.supervisor | Zuva, Tranos, Prof. | |
| dc.date.accessioned | 2022-02-14T04:03:59Z | |
| dc.date.available | 2022-02-14T04:03:59Z | |
| dc.date.issued | 2017-03 | |
| dc.description | M. Tech. (Department of Information Technology, Faculty of Applied and Computer Sciences), Vaal University of Technology | en_US |
| dc.description.abstract | Malware is today one of the biggest security threats to the Internet. Malware is any malicious software with the intent to perform malevolent activities on a targeted system. Viruses, worms, trojans, backdoors and adware are but a few examples that fall under the umbrella of malware. The purpose of this research is to investigate techniques that are used in order to effectively perform Malware analysis and detection on enterprise systems to reduce the damage of malware attacks on the operation of organizations. Malware analysis experiments were carried out using the two techniques of malware analysis, which are Dynamic and Static analysis, on two different malware samples. Portable executable and Microsoft word document files were the two samples that were analysed in an isolated sandbox lab environment. Static analysis is the process of examining and extracting information from malware code without executing the malware, while Dynamic analysis is the process of executing malware in order to observe and record its behaviour in a controlled environment. The results from the experiments disclosed the behaviour, encryption techniques, and other techniques employed by the malware samples. These malware analysis experiments were carried out in an isolated lab environment that was built for the purpose of this research. The results showed that Dynamic analysis is more effective than Static analysis. The study proposes the use of both techniques for comprehensive malware analysis and detection. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10352/494 | |
| dc.language.iso | en | en_US |
| dc.publisher | Vaal University of Technology | en_US |
| dc.subject | Computer systems | en_US |
| dc.subject | Computer virus | en_US |
| dc.subject | Malware analysis | en_US |
| dc.subject.lcsh | Dissertations, Academic -- South Africa | en_US |
| dc.subject.lcsh | Malware (Computer software) | en_US |
| dc.subject.lcsh | Computer security | en_US |
| dc.title | Malware analysis and detection in enterprise systems | en_US |
| dc.type | Thesis | en_US |