• Journal of Astronomy and Space Sciences
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• v.25 no.3
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• pp.321-328
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• 2008

Software Test Bench should be simulated with maximum quality to real execution environment in order to verify the performance of software which is changed or newly developed. And especially faults detection and recovery are crucial function of the performance test environment. Simulated Software Test Bench based on processor emulator is attractive and can be available prior to hardware Software Test Bench if real time performance aspect is ignored. In this paper, the results of conceptual study for developing the simulated Software Test Bench are presented.

• Journal of IKEEE
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• v.17 no.3
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• pp.371-377
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• 2013

This thesis propose an efficient parallel structure method for implementing a FAST and BRIEF algorithm based Augmented Reality. SURF algorithm that is well known in the object recognition algorithms is robust in object recognition. However, there is a disadvantage for real time operation because, SURF implementation requires a lot of computation. Therefore, we used a FAST and BRIEF algorithm for object recognition, and we improved Conventional Parallel Structure based on OpenMP Library. As a result, it achieves a 70%~100% improvement in execution time on the embedded system.

• ETRI Journal
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• v.37 no.6
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• pp.1220-1230
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• 2015

An autonomous valet parking (AVP) system is designed to locate a vacant parking space and park the vehicle in which it resides on behalf of the driver, once the driver has left the vehicle. In addition, the AVP is able to direct the vehicle to a location desired by the driver when requested. In this paper, for an AVP system, we introduce technology to recognize a parking space using image sensors. The proposed technology is mainly divided into three parts. First, spatial analysis is carried out using a height map that is based on dense motion stereo. Second, modelling of road markings is conducted using a probability map with a new salient-line feature extractor. Finally, parking space recognition is based on a Bayesian classifier. The experimental results show an execution time of up to 10 ms and a recognition rate of over 99%. Also, the performance and properties of the proposed technology were evaluated with a variety of data. Our algorithms, which are part of the proposed technology, are expected to apply to various research areas regarding autonomous vehicles, such as map generation, road marking recognition, localization, and environment recognition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.346-349
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• 2014

Currently, the growing cyber threat continues, the damage caused by the evolution of malicious code incidents become more bigger. Such advanced attacks as APT using 'zero-day vulnerability' bring easy way to steal sensitive data or personal information. However it has a lot of limitation that the traditional ways of defense like 'access control' with blocking of application ports or signature base detection mechanism. This study is suggesting a way of controlling application activities focusing on keeping integrity of applications, authorization to running programs and changes of files of operating system by hardening of legitimate resources and programs based on 'white-listing' technology which analysis applications' behavior and its usage.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.31-43
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• 2014

Large number of Android mobile application has been developed and deployed through the Android open market by increasing android-based smart work device users recently. But, it has been discovered security vulnerabilities on malicious applications that are developed and deployed through the open market or 3rd party market. There are issues to leak user's personal and financial information in mobile devices to external server without the user's knowledge in most of malicious application inserted Trojan Horse forms of malicious code. Therefore, in order to minimize the damage caused by malignant constantly increasing malicious application, it is required a proactive detection mechanism development. In this paper, we analyzed the existing techniques' Pros and Cons to detect a malicious application and proposed discrimination and detection result using malicious application discrimination mechanism based on Jaccard similarity after collecting events occur in real-time execution on android-mobile devices.

• Journal of the Korea Computer Industry Society
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• v.4 no.12
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• pp.965-974
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• 2003

Today's network consists of a large number of routers and servers running a variety of applications. In this paper, we have designed and constructed the general simulation environment of network security model composed of multiple IDSs agent and a firewall agent which coordinate by CNP (Contract Net Protocol). The CNP, the methodology for efficient integration of computer systems on heterogeneous environment such as distributed systems, is essentially a collection of agents, which cooperate to resolve a problem. Command console in the CNP is a manager who controls the execution of agents or a contractee, who performs intrusion detection. In the knowledge-based network security model, each model of simulation environment is hierarchically designed by DEVS (Discrete Event system Specification) formalism. The purpose of this simulation is the application of rete pattern-matching algorithm speeding up the inference cycle phases of the intrusion detection expert system. we evaluate the characteristics and performance of CNP architecture with rete pattern-matching algorithm.

• Journal of KIISE
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• v.43 no.10
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• pp.1067-1072
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• 2016

Software birthmarks, which are unique characteristics of the software, are used to detect software plagiarism or software similarity. Generally, software birthmarks are divided into static birthmarks or dynamic birthmarks, which have evident pros and cons depending on the extraction method. In this paper, we propose a method for extracting the API sequence birthmarks using a dynamic analysis and similarity detection between the executable codes. Dynamic birthmarks based on API sequences extract API functions during the execution of programs. The extracted API sequences often include all the API functions called from the start to the end of the program. Meanwhile, our dynamic birthmark scheme extracts the API functions only called directly from the executable code. Then, it uses a sequence alignment algorithm to calculate the similarity metric effectively. We evaluate the birthmark with several open source software programs to verify its reliability and credibility. Our dynamic birthmark scheme based on the extracted API sequence can be utilized in a similarity test of executable codes.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• Journal of IKEEE
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• v.18 no.2
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• pp.291-297
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• 2014

Since hand gesture recognition was realized thanks to improved image processing algorithms, sign language translation has been a critical issue for the hearing-impaired. In this paper, we extract human hand figures from a real time image stream and detect gestures in order to figure out which kind of hand language it means. We used depth-color calibrated image from the Kinect to extract human hands and made a decision tree in order to recognize the hand gesture. The decision tree contains information such as number of fingers, contours, and the hand's position inside a uniform sized image. We succeeded in recognizing 'Hangul', the Korean alphabet, with a recognizing rate of 98.16%. The average execution time per letter of the system was about 76.5msec, a reasonable speed considering hand language translation is based on almost still images. We expect that this research will help communication between the hearing-impaired and other people who don't know hand language.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5B
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• pp.526-531
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• 2009

In this paper, we propose new novel technique (ILCT: Instruction-Level Correlation Technique) which can detect tempered instructions by software attacks or hardware attacks before their execution. In conventional works, due to both high complex computation of cipher process and low processing speed of cipher modules, existing secure processor architecture applying cipher technique can cause serious performance degradation. While, the secure processor architecture applying ILCT with FEC does not incur excessive performance decrease by complexity of computation and speed of tampering detection modules. According to experimental results, total memory overhead including parity are increased in average of 26.62%. Also, secure programs incur CPI degradation in average of $1.20%{\sim}1.97%$.