Web application scanning for malware attack detection with provide appropriate incident report by using hybrid method

In the era of Internet of Things (IoT) technology, potential malware that has the ability to attack any computer software, server or network from various way are increasingly due to the common use of anti-malware software and some of malware, which is not detectable by antivirus. Seeing that the number of malware is increasing rapidly and each malware have different way to attack, it become more challenges to the existing malware detection to stave off extensively. Malware detection is a process to perform analysis of malware on examine the components and behaviours of malware. Malware detection involve two techniques, which consists of static and dynamic analysis techniques. Static analysis technique examine malware without running it or not viewing the actual code. It will employs different tools to identify malicious file, provide the functional information and collect technical indicator to produce signature. For dynamic analysis technique also called as behaviour analysis technique, it runs malware to observe its behaviour, understand the functionality and identify the technical indicator for signature detection. Although there are advantages to conducting static and dynamic separately, but there are some limitation. Implement static and dynamic analysis techniques together are more valuable for reverse engineering complex malware. It will helps to identify the true intent and capabilities of malware and can provide a technical indicator, which cannot be achievable individually. This research propose a hybrid technique, which integrates static and dynamic analysis technique, to examine malware and measure the effectiveness based on the detection time. The proposed scheme should able to run and examine a malware with a low detection time. Besides, this research will also come with some suggestion to be taken once the malware is detected. By using Java language, the web application to analysis malware by using hybrid technique will be presented.