Wonil Kim

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Since the first computer virus has been found, scanning detection has been used as a primarily method in virus detection systems. As computer viruses and worms become more complex and sophisticated, the scanning detection method is no longer able to detect various forms of viruses and worms effectively. Many anti-virus researchers proposed various detection(More)
Digital multimedia data is dramatically being increased everyday since the Internet became popular. This increment in multimedia data increases adult image contents to the Internet as well. Consequently, a large number of children are exposed to these X-rated contents. In this paper, we propose an efficient classification system that can categorize input(More)
SUMMARY In ubiquitous environment that users access resource anytime and anywhere, access control model should consider user's location information. The proposed uT-RBAC includes the location information for user's least privilege. It also supports time related information, which enables the access control model to accommodate various ubiquitous(More)
As the Internet became popular, the volume of digital multimedia data is exponentially increased in all aspects of our life. This drastic increment in multimedia data causes unwelcome deliveries of adult image contents to the Internet. Consequently, a large number of children are wide-open to these harmful contents. In this paper, we propose an efficient(More)
As resource sharing is common practice in distributed and wireless network, authentication and authorization become important issue in the security field. Many access control mechanisms including Role-Based Access Control (RBAC) are widely used for authorization. The common use of the wireless network imposes not only existing problems such as secure system(More)
In this paper we introduce an effective method of the adult image classification via MPEG-7 descriptors. The proposed system uses MPEG-7 descriptors as the main feature of the adult image classification systems. The simulation shows that the proposed image classification system performs the 5 class classification task with success rate of above 70%.
SUMMARY ReMark is a fully automatic tool for clustering orthologs by combining a Recursive and a Markov clustering (MCL) algorithms. The ReMark detects and recursively clusters ortholog pairs through reciprocal BLAST best hits between multiple genomes running software program (RecursiveClustering.java) in the first step. Then, it employs MCL algorithm to(More)