User attribution based on keystroke dynamics in digital forensic readiness process

As the development of technology increases, the security risk also increases. This has affected most organizations, irrespective of size, as they depend on the increasingly pervasive technology to perform their daily tasks. However, the dependency on technology has introduced diverse security vulnerabilities in organizations which requires a reliable preparedness for probable forensic investigation of the unauthorized incident. Keystroke dynamics is one of the cost-effective methods for collecting potential digital evidence. This paper presents a keystroke pattern analysis technique suitable for the collection of complementary potential digital evidence for forensic readiness. The proposition introduced a technique that relies on the extraction of reliable behavioral signature from user activity. Experimental validation of the proposition demonstrates the effectiveness of proposition using a multi-scheme classifier. The overall goal is to have forensically sound and admissible keystroke evidence that could be presented during the forensic investigation to minimize the costs and time of the investigation.