The performance analysis of malware attack / Nur Khairani Kamarudin ... [et al.]

• Main Authors: Kamarudin, Nur Khairani (Author), Md Hasani, Nur Nazifa (Author), Ruslan, Rafiza (Author), Ramle, Rashidah (Author), Ahmad Zukri, Nurul Hidayah (Author), Abd Halim, Iman Hazwam (Author)
• Format: Book
• Published: UiTM Cawangan Perlis, 2018.
• Subjects: Article; PeerReviewed
• Online Access: Link Metadata
• Notes: https://ir.uitm.edu.my/id/eprint/59587/1/59587.pdf; The performance analysis of malware attack / Nur Khairani Kamarudin ... [et al.]. (2018) Journal of Computing Research and Innovation (JCRINN) <https://ir.uitm.edu.my/view/publication/Journal_of_Computing_Research_and_Innovation_=28JCRINN=29/>, 3 (4): 3. pp. 19-24. ISSN 2600-8793
• Keywords: Computer networks. General works. Traffic monitoring; Intrusion detection systems (Computer security). Computer network security. Hackers

People in this new era of modernization nowadays take Internet as one of the vital thing for daily activities. Internet is not only for adults, it is also a needs for people of all ages. However, network vulnerabilities exist in all network that are connec ted to the Internet. The network mostly are exposed to the malicious software or mostly known as malware. In fact, this malware is growing rapidly and giving a bad impact to the human intervention. The number of attack are increasing rapidly and it comes i n various way just to exploit the victims. There are various type of malware attack. For instance, viruses, worms, spyware, rootkits, Trojan horse and botnet are considered as noteworthy threat for the computer network. Some people giving full confidence on the security of data transmission to the network. However, other can access the personal information without them realizing it. The objective of this paper is to detect malware attack using honeypot Dionaea. Malicious file launched was detected by the honeypot and the file was analyzed by using the sandbox tool, Virus Total. This paper found that honeypot Dionaea is helpful in detecting various types of malware attack.