Sang-Jun Han

Learn More
The process of learning the behavior of a given program by using machine-learning techniques (based on system-call audit data) is effective to detect intrusions. Rule learning, neural networks, statistics, and hidden Markov models (HMMs) are some of the kinds of representative methods for intrusion detection. Among them, neural networks are known for good(More)
Hidden Markov model (HMM) has been successfully applied to anomlay detection as a technique to model normal behavior. Despite its good performance, there are some problems in applying it to real intrusion detection systems: it requires large amount of time to model normal behaviors and the false-positive error rate is relatively high. To remedy these(More)
As the information technology grows interests in the intrusion detection system (IDS), which detects unauthorized usage, misuse by a local user and modification of important data, has been raised. In the field of anomaly-based IDS several data mining techniques such as hidden Markov model (HMM), artificial neural network, statistical techniques and expert(More)
In the development of location-based services, various locationsensing techniques and experimental/commercial services have been used. We propose a novel method of predicting the user's future movements in order to develop advanced location-based services. The user’s movement trajectory is modeled using a combination of recurrent self-organizing maps (RSOM)(More)
As the information technology grows interests in the intrusion detection system (IDS), which detects unauthorized usage, misuse by a local user and modification of important data, have been raised. In the field of anomaly-based IDS several artificial intelligence techniques are used to model normal behavior. However, there is no perfect detection method so(More)
As technology improves, mobile phones are becoming essential aspects of human communication. As more and more people begin to use mobile phones, various services based on mobile phone networks and high-end devices are developing. In addition, with the growth of ubiquitous computing, there have been many ongoing studies regarding novel and useful services(More)
Learning program’s behavior using machine learning techniques based on system call audit data is effective to detect intrusions. Among several machine learning techniques, the neural networks are known for its good performance in learning system call sequences. However, it suffers from very long training time because there are no formal solutions for(More)
In the development of location-based services, various location-sensing techniques and experimental/commercial services have been used. However, conventional location-based services are limited in terms of flexibility because they depend on the current location of the user. We propose a novel method of predicting the user’s future movements in order to(More)
As more people get using mobile phones, smartphone which is a new generation of mobile phone with computing capability earns world-wide reputation as new personal business assistant and entertainment equipment. This paper presents a synthetic character which acts as a user assistant and an entertainer in smartphone. It collects low-level information from(More)