Malware Detection Using Dynamic Analysis

In the international cyberspace the main thing to be maintained by the experts is security. The physical security is provided by security companies and men. But the software and digital data protection is only provides by software’s like antivirus. These codes are written by many malicious hackers all around the world.. The present technological antivirus are in static nature. This method of malware identification is out dated as the malware are coming in a modifying manner and many more malware’s are being identified. This creates a problem of uselessness of a antivirus when it has no signature of a malware which is attacking the system. The machine learning algorithms can be very useful in building a dynamic malware analyzer. The prediction mechanism can be helpful in finding the malware’s which are modified from its original form to another form to hide itself from antivirus (family). Then another method is to dynamically updating the signature database in the antivirus software. This can be done using getting the signature from all over the world and dynamically updating the software’s signature database. When these two methods are integrated then it would be a good software with dynamic properties.