• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1123-1129
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• 2015

Macro(automatic hunting) of mobile game is a program that touch the screen by defined rules like a game bot in PC online games, and it is used by make various ways like android application or windows application program. This gives honest users deprivation and make to lose their interest. Finally they would leave the game and gradually game life would be shorten. Although many studies to prevent these problems in PC online game are conducted, applying mobile game to PC's way is difficult because mobile games are limited to use the network and device performance is different with PC. In this paper, we propose a framework for macro detection by using the touch event information. A touch event on the mobile game is a necessary control command to the game. Because macro touches the screen with the same pattern, there is a difference between normal user's behavior and macro's operation. In mobile games that casual games are mostly, Touch event is the best difference that identify normal user against macro for a short period of time. As a result of detecting macros used in real mobile game by using the proposed framework it showed 100% accuracy and 0% false positive rate.

• Journal of KIISE:Software and Applications
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• v.28 no.2
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• pp.179-191
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• 2001

Comparison shopping is a merchant brokering process that finds the best price for the desired product from several Web-based online stores. To get a scalable comparison shopper, we need an agent that automatically constructs a simple information extraction procedure, called a wrapper, for each semi-structured store. Automatic construction of wrappers for HTML-based Web stores is difficult because HTML only defines how information is to be displayed, not what it means, and different stores employ different ways of manipulating customer queries and different presentation formats for displaying product descriptions. Wrapper induction has been suggested as a promising strategy for overcoming this heterogeneity. However, previous scalable comparison-shoppers such as ShopBot rely on a strong bias in the product descriptions, and as a result, many stores that do not confirm to this bias were unable to be recognized. This paper proposes a more scalable comparison-shopping agent named MORPHEUS. MORPHEUS presents a simple but robust inductive learning algorithm that antomatically constructs wrappers. The main idea of the proposed algorithm is to recognize the position and the structure of a product description unit by finding the most frequent pattern from the sequence of logical line information in output HTML pages. MORPHEUS successfully constructs correct wtappers for most stores by weakening a bias assumed in previous systems. It also tolerates some noises that might be present in production descriptions such as missing attributes. MORPHEUS generates the wrappers rapidly by excluding the pre-processing phase of removing redundant fragments in a page such as a header, a tailer, and advertisements. Eventually, MORPHEUS provides a framework from which a customized comparison-shopping agent can be organized for a user by facilitating the dynamic addition of new stores.