• Title/Summary/Keyword: Real-time computing

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Fuzzy Expert System for Detecting Anti-Forensic Activities (안티 포렌식 행위 탐지를 위한 퍼지 전문가 시스템)

  • Kim, Se-Ryoung;Kim, Huy-Kang
    • Journal of Internet Computing and Services
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    • v.12 no.5
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    • pp.47-61
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    • 2011
  • Recently, the importance of digital forensic has been magnified because of the dramatic increase of cyber crimes and the increasing complexity of the investigation of target systems such as PCs, servers, and database systems. Moreover, some systems have to be investigated with live forensic techniques. However, even though live forensic techniques have been improved, they are still vulnerable to anti-forensic activities when the target systems are remotely accessible by criminals or their accomplices. To solve this problem, we first suggest a layer-based model and the anti-forensic scenarios which can actually be applicable to each layer. Our suggested model, the Anti-Forensic Activites layer-based model, has 5 layers - the physical layer, network layer, OS layer, database application layer and data layer. Each layer has possible anti-forensic scenarios with detailed commands. Second, we propose a fuzzy expert system for effectively detecting anti-forensic activities. Some anti-forensic activities are hardly distinguished from normal activities. So, we use fuzzy logic for handling ambiguous data. We make rule sets with extracted commands and their arguments from pre-defined scenarios and the fuzzy expert system learns the rule sets. With this system, we can detect anti-forensic activities in real time when performing live forensic.

A Study on Creative Cognition of Language based concept Generation of Game Graphics (언어기반 게임그래픽 디자인 발상의 창의적 인지에 관한 연구)

  • Huh, Yoon-Jung
    • Journal of Internet Computing and Services
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    • v.12 no.5
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    • pp.171-179
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    • 2011
  • In this paper it is hypothesized that word stimuli that are presented by Google’s search word, would improve the quality of the design solution, so this research examines the effect of related search word stimuli in concept generation and analyzes the results through the processes of creative cognition. In the process of concept generation, words are given as stimuli which are generated through Google's related search and these search words are given by 5 levels. Google search is based on the collaboration philosophy. People's participation and contribution recreate knowledge and information, so these renewed and related search words update in real time by people are used as stimuli. Two problems are provided with related search words. After the design concept generation the results are analyzed by 3 bases: the usage of related search words and those of frequency, creativity, and Finke's 12 Geneplore model. These are the results of the research. Many levels of related search words are used in design concept generation but especially higher levels which are more related to search words are more used than lower levels. The usage of multi words and conjunction with higher levels and lower levels words are observed in creative results. On the creative cognitive processes, it is more creative when using association and mental transformation with the related search words than using the related search words simply. Creative outputs also use conceptual interpretation, functional inference, and contextual shifting of creative cognitive processes of Finke's 12 Geneplore model.

Efficient Tracking System for Passengers with the Detection Algorithm of a Stopping Vehicle (차량정차감지 알고리즘을 이용한 탑승자의 효율적 위치추적시스템)

  • Lee, Byung-Mun;Shin, Hyun-Ho;Kang, Un-Gu
    • Journal of Internet Computing and Services
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    • v.12 no.6
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    • pp.73-82
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    • 2011
  • The location-based service is emerging again to the public attention. The location recognition environment up-to-now has been studied with its focus only on a person, an object or a moving object. However, this study proposes a location recognition model that serves to recognize and track, in real time, multiple passengers in a moving vehicle. Identifying the locations of passengers can be classified into two classes: one is to use the high price terminal with GPS function, and the other is to use the economic price compact terminal without GPS function. Our model enables the simple compact terminal to provide effective location recognition under the on-boarding situation by transmitting messages through an interface device and sensor networks for a vehicle equipped with GPS. This technology reduces transmission traffic after detecting the condition of a vehicle (being parked or running), because it does not require transmission/receiving of information on the locations of passengers who are confined in a vehicle when the vehicle is running. Also it extends battery life by saving power consumption of the compact terminal. Hence, we carried out experiments to verify its serviceability by materializing the efficient tracking system for passengers with the detection algorithm of a stopping vehicle proposed in this study. Moreover, about 200 experiments using the system designed with this technology proved successful recognition on on-boarding and alighting of passengers with the maximum transmission distance of 12 km. In addition to this, the running recognition tests showed the test with the detection algorithm of a stopping vehicle has reduced transmission traffic by 41.6% compared to the algorithm without our model.

Optimal Moving Pattern Mining using Frequency of Sequence and Weights (시퀀스 빈발도와 가중치를 이용한 최적 이동 패턴 탐사)

  • Lee, Yon-Sik;Park, Sung-Sook
    • Journal of Internet Computing and Services
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    • v.10 no.5
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    • pp.79-93
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    • 2009
  • For developing the location based service which is individualized and specialized according to the characteristic of the users, the spatio-temporal pattern mining for extracting the meaningful and useful patterns among the various patterns of the mobile object on the spatio-temporal area is needed. Thus, in this paper, as the practical application toward the development of the location based service in which it is able to apply to the real life through the pattern mining from the huge historical data of mobile object, we are proposed STOMP(using Frequency of sequence and Weight) that is the new mining method for extracting the patterns with spatial and temporal constraint based on the problems of mining the optimal moving pattern which are defined in STOMP(F)[25]. Proposed method is the pattern mining method compositively using weighted value(weights) (a distance, the time, a cost, and etc) for our previous research(STOMP(F)[25]) that it uses only the pattern frequent occurrence. As to, it is the method determining the moving pattern in which the pattern frequent occurrence is above special threshold and the weight is most a little bit required among moving patterns of the object as the optimal path. And also, it can search the optimal path more accurate and faster than existing methods($A^*$, Dijkstra algorithm) or with only using pattern frequent occurrence due to less accesses to nodes by using the heuristic moving history.

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Intermediate-Representation Translation Techniques to Improve Vulnerability Analysis Efficiency for Binary Files in Embedded Devices (임베디드 기기 바이너리 취약점 분석 효율성 제고를 위한 중간어 변환 기술)

  • Jeoung, Byeoung Ho;Kim, Yong Hyuk;Bae, Sung il;Im, Eul Gyu
    • Smart Media Journal
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    • v.7 no.1
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    • pp.37-44
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    • 2018
  • Utilizing sequence control and numerical computing, embedded devices are used in a variety of automated systems, including those at industrial sites, in accordance with their control program. Since embedded devices are used as a control system in corporate industrial complexes, nuclear power plants and public transport infrastructure nowadays, deliberate attacks on them can cause significant economic and social damages. Most attacks aimed at embedded devices are data-coded, code-modulated, and control-programmed. The control programs for industry-automated embedded devices are designed to represent circuit structures, unlike common programming languages, and most industrial automation control programs are designed with a graphical language, LAD, which is difficult to process static analysis. Because of these characteristics, the vulnerability analysis and security related studies for industry automation control programs have only progressed up to the formal verification, real-time monitoring levels. Furthermore, the static analysis of industrial automation control programs, which can detect vulnerabilities in advance and prepare for attacks, stays poorly researched. Therefore, this study suggests a method to present a discussion on an industry automation control program designed to represent the circuit structure to increase the efficiency of static analysis of embedded industrial automation programs. It also proposes a medium term translation technology exploiting LLVM IR to comprehensively analyze the industrial automation control programs of various manufacturers. By using LLVM IR, it is possible to perform integrated analysis on dynamic analysis. In this study, a prototype program that converts to a logical expression type of medium language was developed with regards to the S company's control program in order to verify our method.

Internet-of-Things Based Approach for Monitoring Pharmaceutical Cold Chain (사물인터넷을 이용한 의약품 콜드체인 관리 시스템)

  • Chandra, Abel Avitesh;Back, Jong Sang;Lee, Seong Ro
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39C no.9
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    • pp.828-840
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    • 2014
  • There is a new evolution in technological advancement taking place called the Internet of Things (IoT). The IoT enables physical world objects in our surroundings to be connected to the Internet. For this idea to come to life, two architectures are required: the Sensing Entity in the environment which collects data and connects to the cloud and the Cloud Service that hosts the data. In particular, the combination of wireless sensor network for sensing and cloud computing for managing sensor data is becoming a popular intervention for the IoT era. The pharmaceutical cold chain requires controlled environmental conditions for the sensitive products in order for them to maintain their potency and fit for consumption. The monitoring of distribution process is the only assurance that a process has been successfully validated. The distribution process is so critical that anomaly at any point will result in the process being no longer valid. Taking the cold chain monitoring to IoT and using its benefits and power will result in better management and product handling in the cold chain. In this paper, Arduino based wireless sensor network for storage and logistics (land and sea) is presented and integrated with Xively cloud service to offer a real-time and innovative solution for pharmaceutical cold chain monitoring.

A step-by-step service encryption model based on routing pattern in case of IP spoofing attacks on clustering environment (클러스터링 환경에 대한 IP 스푸핑 공격 발생시 라우팅 패턴에 기반한 단계별 서비스 암호화 모델)

  • Baek, Yong-Jin;Jeong, Won-Chang;Hong, Suk-Won;Park, Jae-Hung
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.10 no.6
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    • pp.580-586
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    • 2017
  • The establishment of big data service environment requires both cloud-based network technology and clustering technology to improve the efficiency of information access. These cloud-based networks and clustering environments can provide variety of valuable information in real-time, which can be an intensive target of attackers attempting illegal access. In particular, attackers attempting IP spoofing can analyze information of mutual trust hosts constituting clustering, and attempt to attack directly to system existing in the cluster. Therefore, it is necessary to detect and respond to illegal attacks quickly, and it is demanded that the security policy is stronger than the security system that is constructed and operated in the existing single system. In this paper, we investigate routing pattern changes and use them as detection information to enable active correspondence and efficient information service in illegal attacks at this network environment. In addition, through the step-by -step encryption based on the routing information generated during the detection process, it is possible to manage the stable service information without frequent disconnection of the information service for resetting.

TeloSIM: Instruction-level Sensor Network Simulator for Telos Sensor Node (TeloSIM: Telos 형 센서노드를 위한 명령어 수준 센서네트워크 시뮬레이터)

  • Joe, Hyun-Woo;Kim, Hyung-Shin
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.11
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    • pp.1021-1030
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    • 2010
  • In the sensor network, many tiny nodes construct Ad-Hoc network using wireless interface. As this type of system consists of thousands of nodes, managing each sensor node in real world after deploying them is very difficult. In order to install the sensor network successfully, it is necessary to verify its software using a simulator beforehand. In fact Sensor network simulators require high fidelity and timing accuracy to be used as a design, implementation, and evaluation tool of wireless sensor networks. Cycle-accurate, instruction-level simulation is the known solution for those purposes. In this paper, we developed an instruction-level sensor network simulator for Telos sensor node as named TeloSlM. It consists of MSP430 and CC2420. Recently, Telos is the most popular mote because MSP430 can consume the minimum energy in recent motes and CC2420 can support Zigbee. So that TeloSlM can provide the easy way for the developers to verify software. It is cycle-accurate in instruction-level simulator that is indispensable for OS and the specific functions and can simulate scalable sensor network at the same time. In addition, TeloSlM provides the GUI Tool to show result easily.

Development of a Simulation Prediction System Using Statistical Machine Learning Techniques (통계적 기계학습 기술을 이용한 시뮬레이션 결과 예측 시스템 개발)

  • Lee, Ki Yong;Shin, YoonJae;Choe, YeonJeong;Kim, SeonJeong;Suh, Young-Kyoon;Sa, Jeong Hwan;Lee, JongSuk Luth;Cho, Kum Won
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.11
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    • pp.593-606
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    • 2016
  • Computer simulation is widely used in a variety of computational science and engineering fields, including computational fluid dynamics, nano physics, computational chemistry, structural dynamics, and computer-aided optimal design, to simulate the behavior of a system. As the demand for the accuracy and complexity of the simulation grows, however, the cost of executing the simulation is rapidly increasing. It, therefore, is very important to lower the total execution time of the simulation especially when that simulation makes a huge number of repetitions with varying values of input parameters. In this paper we develop a simulation service system that provides the ability to predict the result of the requested simulation without actual execution for that simulation: by recording and then returning previously obtained or predicted results of that simulation. To achieve the goal of avoiding repetitive simulation, the system provides two main functionalities: (1) storing simulation-result records into database and (2) predicting from the database the result of a requested simulation using statistical machine learning techniques. In our experiments we evaluate the prediction performance of the system using real airfoil simulation result data. Our system on average showed a very low error rate at a minimum of 0.9% for a certain output variable. Using the system any user can receive the predicted outcome of her simulation promptly without actually running it, which would otherwise impose a heavy burden on computing and storage resources.

A Realtime Expression Control for Realistic 3D Facial Animation (현실감 있는 3차원 얼굴 애니메이션을 위한 실시간 표정 제어)

  • Kim Jung-Gi;Min Kyong-Pil;Chun Jun-Chul;Choi Yong-Gil
    • Journal of Internet Computing and Services
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    • v.7 no.2
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    • pp.23-35
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    • 2006
  • This work presents o novel method which extract facial region und features from motion picture automatically and controls the 3D facial expression in real time. To txtract facial region and facial feature points from each color frame of motion pictures a new nonparametric skin color model is proposed rather than using parametric skin color model. Conventionally used parametric skin color models, which presents facial distribution as gaussian-type, have lack of robustness for varying lighting conditions. Thus it needs additional work to extract exact facial region from face images. To resolve the limitation of current skin color model, we exploit the Hue-Tint chrominance components and represent the skin chrominance distribution as a linear function, which can reduce error for detecting facial region. Moreover, the minimal facial feature positions detected by the proposed skin model are adjusted by using edge information of the detected facial region along with the proportions of the face. To produce the realistic facial expression, we adopt Water's linear muscle model and apply the extended version of Water's muscles to variation of the facial features of the 3D face. The experiments show that the proposed approach efficiently detects facial feature points and naturally controls the facial expression of the 3D face model.

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