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JavaScript is a popular technique for activating static HTML. JavaScript has drawn more attention following the introduction of HTML5 Standard. In proportion to JavaScript's growing importance, attacks (ex. DDos, Information leak using its function) become more dangerous. Since these attacks do not create a trail, whether the JavaScript code is malicious or not must be decided. The real attack action is completed while the browser runs the JavaScript code. For these reasons, there is a need for a real-time classification and determination technique for malicious JavaScript. This paper proposes the Analysis Engine for detecting malicious JavaScript by adopting the requirements above. The analysis engine performs static analysis using signature-based detection and dynamic analysis using behavior-based detection. Static analysis can detect malicious JavaScript code, whereas dynamic analysis can detect the action of the JavaScript code.

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Advances in information technology have increased the number of people using mobile device and have made mobile service pervasive. In spite of increase of rapid diffusion and usage of mobile service, previous papers mainly focused on figuring out factors influencing the mobile technology adoption but understanding of customer behavior regarding the usage of mobile channel is lacking. Moreover, mobile service channel is one of alternative channels and customer choice of one service channel affects customer use of other channels. We investigate the relationship between service channels. Specifically, this paper empirically investigates the mutual influence between internet and mobile channels in banking service through VAR test using data of Korea online banking service. Our result shows that, as customer's use of mobile channel increases, it has influences on internet channel use, and vice versa. Customers using mobile banking service channel tend to use internet banking service as a complementary channel. On the contrary, the use of internet banking service does not have an influence on the use of mobile banking service channel. Additionally, the trait of this relationship depends on the characteristic of task. Also cross channel influence is differentiated by banking service task. This paper provides the understanding of customer behavior in multiple service channels and implication that strategic management of multi-channel has to be concerned in terms of relationship between service channels.