SUMMARYContext-aware systems detect user's physical and social contexts based on sensor networks, and provide services that adapt to the user accordingly. Representing, detecting, and managing the contexts are important issues in context-aware systems. Composition of contexts is a useful method for these works, since it can detect a context by automatically composing small pieces of information to discover service. Dangeraware services are a kind of context-aware services which need description of relations between a user and his/her surrounding objects and between users. However when applying the existing composition methods to danger-aware services, they show the following shortcomings that (1) they have not provided an explicit method for representing composition of multi-user' contexts, (2) there is no flexible reasoning mechanism based on similarity of contexts, so that they can just provide services exactly following the predefined context reasoning rules. Therefore, in this paper, we propose a two-stage composition method based on context similarity to solve the above problems. The first stage is composition of the useful information to represent the context for a single user. The second stage is composition of multi-users' contexts to provide services by considering the relation of users. Finally the danger degree of the detected context is computed by using context similarity between the detected context and the predefined context. Context is dynamically represented based on two-stage composition rules and a Situation theory based Ontology, which combines the advantages of Ontology and Situation theory. We implement the system in an indoor ubiquitous environment, and evaluate the system through two experiments with the support of subjects. The experiment results show the method is effective, and the accuracy of danger detection is acceptable to a danger-aware system.

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Flash has a number of security defects even though Flash Player is installed on most of world's PC. Protection using sandbox has limitation to protect a user from vulnerabilities of Flash application because an attacker can attack a vulnerable Flash application when a sandbox can't work if an engineer or a web administrator set sandbox permission wrongly.Another way to solve it is testing. As a testing, penetration testing is useful for detecting vulnerability of Flash Application. Existing penetration testing performs penetration test through UI manually, which is inefficient and time consuming.In this paper, to overcome a problem of existing penetration test, we design a new penetration testing, which enables to generate as many test patterns as possible from VM inputs, inputting test patterns into VM, and checks the existence of vulnerabilities from VM outputs automatically. We demonstrate our testing method using an example, which can detect Flash Parameter Injection that is a one kind of vulnerability of Flash application.

With the progress of ubiquitous techniques and devices, such as RF-ID and sensors, etc., invisible computers are embedded in one's life and working environment, such as applicants, etc. Research on ubiquitous environment becomes very important. On the other hand, E-learning using WWW has been studying prosperously. Merging creatively the techniques in the two fields to construct a support environment of ubiquitous learning is demanded. Specially, the ubiquitous learning environment is suitable for outdoor learning to increase the students in middle school and high school for increasing their experiences and knowledge from real world, not only from text books. In this paper, we propose a new personalized ubiquitous learning support environment. In the ubiquitous learning environment, every learner's behavior or habit can be sensed and observed precisely. By comparingthem with learning instructional requirement set by an instructor, the situation can be grasped. Personalized support suitable for the learner's situation can be provided to the learner. The proposed environment will be very useful for promoting ubiquitous learning. .