• Korean Journal of Remote Sensing
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• v.21 no.2
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• pp.135-143
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• 2005

RPC(Rational Polynomial Camera) models have become the replacement model of choice for a number of high resolution satellite imagery providers. RPCs(Rational Polynomial Coefficients) provide a compact accurate representation of the ground to image geometry, allowing users to perform full photogrammetric processing of satellite imagery including block adjustment, 3D feature extraction and orthorectification. This paper presents an algorithm for 3D feature extraction using downhill simpler method which requires only function evaluations, not derivatives. The algorithm was implemented as an executable software program and tested using stereo IKONOS images of Seoul city. The results showed that the proposed algorithm was fast and accurate enough to be used as a practical method for the 3D feature extraction from stereo images with RPCs.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.197-202
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• 2022

IoT (Internet of Things) devices are being attacked by malware due to many security vulnerabilities, such as the use of weak IDs/passwords and unauthenticated firmware updates. However, due to the diversity of CPU architectures, it is difficult to set up a malware analysis environment and design features. In this paper, we design time series features using the byte sequence of executable files to represent independent features of CPU architectures, and analyze them using recurrent neural networks. The proposed feature is a fixed-length time series pattern extracted from the byte sequence by calculating partial entropy and applying linear interpolation. Temporary changes in the extracted feature are analyzed by RNN and LSTM. In the experiment, the IoT malware detection showed high performance, while low performance was analyzed in the malware family classification. When the entropy patterns for each malware family were compared visually, the Tsunami and Gafgyt families showed similar patterns, resulting in low performance. LSTM is more suitable than RNN for learning temporal changes in the proposed malware features.

• Journal of Internet Computing and Services
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• v.14 no.1
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• pp.15-22
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• 2013

WAVE(Wireless Access for Vehicular Environment) is new concepts and Vehicles communications technology using for ITS(Intelligent Transportation Systems) service by IEEE standard 802.11p. Also it increases the efficiency and safety of the traffic on the road. However, the efficiency of Scrambler bit computational algorithms of OFDM modulation in WAVE systems will fall as it is not able to process in parallel in terms of hardware and software. This paper proposes an algorithm to configure 64-bits matrix table in scambler bit computation as well as an algorithm to compute 64-bits matrix table and input data in parallel. The proposed algorithm on this thesis is executed using 64-bits matrix table. In the result, the processing speed for 1 and 1000 times is improved about 40.08% ~ 40.27% and processing rate per sec is performed more than 468.35 compared to bit operation scramble. And processing speed for 1 and 1000 times is improved about 7.53% ~ 7.84% and processing rate per sec is performed more than 91.44 compared to 32-bits operation scramble. Therefore, if the 64 bit-CPU is used for 64-bits executable scramble algorithm, it is improved more than 40% compare to 32-bits scrambler.

• Journal of Korea Multimedia Society
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• v.1 no.2
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• pp.239-248
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• 1998

Software reengineering is making various research for solutions against problem of maintain existing system. Reengineering has a meaning of development of softwares on existing systems through the reverse-engineering and the forward-engineering. It extracts classes from existing system's softwares to increase the comprehension of the system and enhance the maintenability of softwares. Most of the important concepts used in reengineering is composition that is restructuring of the existing objects from other components. The classes and clusters in storage have structural relationship with system's main components to reuse in the higher level. These are referenced as dynamic informations through structuring an architect for each of them. The classes are created by extractor, searcher and composer through representing existing object-oriented source code. Each of classes and clusters extract refined informations through optimization. New architecture is created from the cluster based on its classes' relationship in storage. This information can be used as an executable code later on. In this paper, we propose the tools, it presented by this thesis presents a new information to users through analysing, based on reengineering, Object-Oriented informations and practicing composition methodology. These composite classes will increase reusability and produce higher comprehension information to consist maintainability for existing codes.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.2
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• pp.174-182
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• 2002

The object-oriented design methods and their CASE tools are widely used in practice by many real-time software developers. However, object-oriented CASE tools require an additional step of identifying tasks from a given design model. Unfortunately, it is difficult to automate this step for a couple of reasons: (1) there are inherent discrepancies between objects and tasks; and (2) it is hard to derive tasks while maximizing real-time schedulability since this problem makes a non-trivial optimization problem. As a result, in practical object-oriented CASE tools, task identification is usually performed in an ad-hoc manner using hints provided by human designers. In this paper, we present a systematic, schedulability-aware approach that can help mapping real-time object-oriented models to multi-threaded implementations. In our approach, a task contains a group of mutually exclusive transactions that may possess different periods and deadline. For this new task model, we provide a new schedulability analysis algorithm. We also show how the run-time system is implemented and how executable code is generated in our frame work. We have performed a case study. It shows the difficulty of task derivation problem and the utility of the automated synthesis of implementations as well as the Inappropriateness of the single-threaded implementations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.432-443
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• 2017

The primary goal of the MPEG-H 3D Audio standard is to provide immersive audio environments for high-resolution broadcasting services such as UHDTV. This standard incorporates a wide range of technologies such as encoding/decoding technology for multi-channel/object/scene-based signal, rendering technology for providing 3D audio in various playback environments, and post-processing technology. The reference software decoder of this standard is a structure combining several modules and can operate in various modes. Each module is composed of independent executable files and executed sequentially, real time decoding is impossible. In this paper, we make DLL library of the core decoder, format converter, object renderer, and binaural renderer of the standard and integrate them to enable frame-based decoding. In addition, by measuring the computation complexity of each mode of the MPEG-H 3D-Audio decoder, this paper also provides a reference for selecting the appropriate decoding mode for various hardware platforms. As a result of the computational complexity measurement, the low complexity profiles included in Korean broadcasting standard has a computation complexity of 2.8 times to 12.4 times that of the QMF synthesis operation in case of rendering as a channel signals, and it has a computation complexity of 4.1 times to 15.3 times of the QMF synthesis operation in case of rendering as a binaural signals.

• Journal of KIISE:Software and Applications
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• v.34 no.5
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• pp.431-446
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• 2007

Executable composite Web services are selected by binding a given abstract workflow with the specific Web services that satisfy given QoS requirements. Considering the rapidly increasing number of Web services and their highly dynamic QoS environment, the fast selection of composite services is important. This paper presents a method for quality driven comosite Web services selection based on a workflow partition strategy. The proposed method partitions an abstract workflow into two sub-workflows to decrease the number of candidate services that should be considered. The QoS requirement is also decomposed for each partitioned workflow. Since the decomposition of a QoS requirement is based on heuristics, the selection might fail to find composite Web services. To avoid such a failure, the tightness of a QoS requirement is defined and a workflow is determined to be partitioned according to the tightness. A mixed integer linear programming is utilized for the efficient service selection. Experimental results show that the success rate of partitioning is above 99%. Particularly, the proposed method performs faster and selects composite services whose qualities are not significantly different (less than 5%) from the optimal one.

• Journal of the Korea Society for Simulation
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• v.15 no.1
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• pp.35-42
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• 2006

Sensor network, that is an infrastructure of ubiquitous computing, consists of a number of sensor nodes of which hardware is very small. The network topology and routing scheme of the network should be determined according to its purpose, and its hardware and software may have to be changed as needed from time to time. Thus, the sensor network simulator being capable of verifying its behavior and estimating performance is required for better design. Sensor network simulators currently existing have been developed for specific hardwares or operating systems, so that they can only be used for such systems and do not provide any means to estimate the amount of power consumption and program execution time which are major issues for system design. In this study, we develop the sensor network simulator that can be used to design and verify various sensor networks without regarding to types of applications or operating systems, and also has the capability of predicting the amount of power consumption and program execution time. For this purpose, the simulator is developed by using machine instruction-level discrete-event simulation scheme. As a result, the simulator can be used to analyze program execution timings and related system behaviors in the actual sensor nodes in detail. Instruction traces used as workload for simulations are executable images produced by the cross-compiler for ATmega128L microcontroller.

• Journal of Industrial Convergence
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• v.21 no.9
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• pp.41-48
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• 2023

Recently, there has been a sharp increase in the damages caused by ransomware across various sectors of society, including individuals, businesses, and nations. Ransomware is a malicious software that infiltrates user computer systems, encrypts important files, and demands a ransom in exchange for restoring access to the files. Due to its diverse and sophisticated attack techniques, ransomware is more challenging to detect than other types of malware, and its impact is significant. Therefore, there is a critical need for accurate detection and mitigation methods. To achieve precise ransomware detection, an inference engine of a detection system must possess knowledge of ransomware features. In this paper, we propose a model to extract and classify the characteristics of ransomware for accurate detection of ransomware, calculate the similarity of the extracted characteristics, reduce the dimension of the characteristics, group the reduced characteristics, and classify the characteristics of ransomware into attack tools, inflow paths, installation files, command and control, executable files, acquisition rights, circumvention techniques, collected information, leakage techniques, and state changes of the target system. The classified characteristics were applied to the existing ransomware to prove the validity of the classification, and later, if the inference engine learned using this classification technique is installed in the detection system, most of the newly emerging and variant ransomware can be detected.