Exploring the Possibility of USB based Fork Bomb Attack on Windows Environment

Efendy, Rezky Aulia; Almaarif, Ahmad; Budiono, Avon; Saputra, Muhardi; Puspitasari, Warih; Sutoyo, Edi

doi:10.1109/iciss48059.2019.8969789

Cited by 7 publications

(1 citation statement)

References 2 publications

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“…Malware has various types, namely viruses, worms, spyware, adware, trojans, keyloggers, rootkits, botnets and phishing [1]. Malware can be spread using various attack vector, including website and USB Flash Drive [2]. One example of malware is botnet, botnet is usually used to send spam and phishing host websites that make it difficult to track and blacklist [3].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Malware Impact on Network Traffic using Behavior-based Detection Technique

Muhtadi

Almaarif

2020

Int. J. Adv. Data Inf. Syst.

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Malware is a software or computer program that is used to carry out malicious activity. Malware is made with the aim of harming user’s device because it can change user’s data, use up bandwidth and other resources without user's permission. Some research has been done before to identify the type of malware and its effects. But previous research only focused on grouping the types of malware that attack via network traffic. This research analyzes the impact of malware on network traffic using behavior-based detection techniques. This technique analyzes malware by running malware samples into an environment and monitoring the activities caused by malware samples. To obtain accurate results, the analysis is carried out by retrieving API call network information and network traffic activities. From the analysis of the malware API call network, information is generated about the order of the API call network used by malware. Using the network traffic, obtained malware activities by analyzing the behavior of network traffic malware, payload, and throughput of infected traffic. Furthermore, the results of the API call network sequence used by malware and the results of network traffic analysis, are analyzed so that the impact of malware on network traffic can be determined.

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Section: Introductionmentioning

confidence: 99%