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Application Monitoring System Design and Implementation using System Call Pattern
http://doi.org/10.5626/JOK.2022.49.10.795
A user application consists of a set of functions. An application gives a set of functions to do what the user needs. Applications that provide services such as web servers are very large and complex, making them a target for attackers. As a result of attacks by malicious hackers, application variables and program flow are distorted, leading to the hijacking of system administrator privileges or abnormal operations. In this paper, we designed and implemented a system that collects an application"s system call and detects anomalies in applications through the collected patterns. As a result of measuring the overhead through the actually implemented system, it was found that when about 1 million system calls were monitored, it had an overhead of about 0.8 seconds. This is about 1/28 of the overhead time of existing tools such as strace.
Validation of Intelligent Integrated Management Platform Capabilities based on a Large Virtual HPC Testbed
Seungwoo Rho, Jinseung Ryu, Sangwan Kim, Kwang Jin Oh, MyoungHwan Yoo
http://doi.org/10.5626/JOK.2022.49.4.276
This paper introduces an intelligent integrated management platform developed by itself to manage high-performance computers equipped with board management controller (BMC) functions, and presents large-scale virtual High Performance Computing (HPC) testbeds and experimental results to verify this platform. Intelligent integrated management platforms can monitor and control the hardware sensors of existing high-performance computers using an Intelligent Platform Management Interface (IPMI) to communicate with the BMC. In addition, a separate agent module operated within the controller was developed and applied to expand the function and performance of the BMC in a high performance computer developed in Korea. In this paper, we introduced an intelligent integrated management platform, built 1,200 virtual HPC testbeds, and verified their functions after linking them to the same integrated management platform as the actual physical server.
Developing a Connection Restrictions Filtering System for Websites based on Swear Words Extraction
http://doi.org/10.5626/JOK.2019.46.12.1272
Youth are exposed to various types of illegal and harmful information through the Internet. To reduce exposure to such information, the government adopts the SNI method to block access to illegal harmful sites. However, it does not block instances of bad information or swear words on the web page itself. In order to limit the access of these web pages in situations such as schools and institutions, this study suggests a connection restrictions filtering system for websites based on swear words extraction. We collected 5542 pseudonyms that were actually used in related research, questionnaires, and Internet searches. We extracted the profanity by using the w-shingling algorithm, then calculated the risk associated with the webpage according to the frequency of use and the weight of the profanity. The system developed in this study will help learning environments in small networks such as elementary and junior high schools by allowing them to restrict access to websites for educational purposes.
Web-based Integrated Management System Using oneM2M Platform in IoT Environment
Manseong Lee, Geonwoo Kim, Jiwoo Park, Kwangsue Chung
http://doi.org/10.5626/JOK.2018.45.10.1104
Today, the Internet of Things (IoT) is increasingly utilized to connect between devices as Machine to Machine (M2M) technology develops. A standardized communication protocol is required for device-to-device connections. The oneM2M standard is being used in IoT devices as a standardization method for stable communication between two devices. oneM2M controls resources by requesting resources through Create, Retrieve, Update, Delete, Notify (CRUDN) operations. Since the existing system checks the status information of the device through the application, a problem arises whereby the user has no accessibility and the real-time information cannot be served. The proposed system manages the IoT device as a oneM2M resource and advises the user to check the real-time resource information and log in the web environment.
SWAT: A Study on the Efficient Integration of SWRL and ATMS based on a Distributed In-Memory System
Myung-Joong Jeon, Wan-Gon Lee, Batselem Jagvaral, Hyun-Kyu Park, Young-Tack Park
http://doi.org/10.5626/JOK.2018.45.2.113
Recently, with the advent of the Big Data era, we have gained the capability of acquiring vast amounts of knowledge from various fields. The collected knowledge is expressed by well-formed formula and in particular, OWL, a standard language of ontology, is a typical form of well-formed formula. The symbolic reasoning is actively being studied using large amounts of ontology data for extracting intrinsic information. However, most studies of this reasoning support the restricted rule expression based on Description Logic and they have limited applicability to the real world. Moreover, knowledge management for inaccurate information is required, since knowledge inferred from the wrong information will also generate more incorrect information based on the dependencies between the inference rules. Therefore, this paper suggests that the SWAT, knowledge management system should be combined with the SWRL (Semantic Web Rule Language) reasoning based on ATMS (Assumption-based Truth Maintenance System). Moreover, this system was constructed by combining with SWRL reasoning and ATMS for managing large ontology data based on the distributed In-memory framework. Based on this, the ATMS monitoring system allows users to easily detect and correct wrong knowledge. We used the LUBM (Lehigh University Benchmark) dataset for evaluating the suggested method which is managing the knowledge through the retraction of the wrong SWRL inference data on large data.
Performance Analysis of LoRa(Long Range) according to the Distances in Indoor and Outdoor Spaces
Junyeong Lim, Jaemin Lee, Donghyun Kim, Jongdeok Kim
http://doi.org/10.5626/JOK.2017.44.7.733
LPWAN(Low Power Wide Area Network) technology is M2M (Machine to Machine) networking technology for the Internet of Things. The technology is designed to support low-power, long-distance and low-speed communications that are typical of LoRaWAN(Long Range Wide Area Network). To exchange inter-object information using a LoRaWAN, the link performances for various environments must be known. however, active performance analysis research that is based on an empirical environment is nonexistent. Therefore, this paper empirically evaluates the performance of the LoRa (Long Range) link, a physical communication technology of the LoRaWAN for various variables that may affect the link quality in indoor and outdoor environments. To achieve this, a physical performance monitoring system was designed and implemented. A communication experiment environment was subsequently constructed based on the indoor and outdoor conditions. The SNR(Signal to Noise Ratio), RSSI(Received Signal Strength Indication), and the PDR(Packet Delivery Ratio) were evaluated.
An Efficient Algorithm for Monitoring Continuous Top-k Queries
JaeHee Jang, HaRim Jung, YougHee Kim, Ung-Mo Kim
In this study, we propose an efficient method for monitoring continuous top-k queries. In contrast to the conventional top-k queries, the presented top-k query considers both spatial and non-spatial attributes. We proposed a novel main-memory based grid access method, called Bit-Vector Grid Index (BVGI). The proposed method quickly identifies whether the moving objects are included in some of the grid cell by encoding a non-spatial attribute value of the moving object to bit-vector. Experimental simulations demonstrate that the proposed method is several times faster than the previous method and uses considerably less memory.
Ontology-based Monitoring Approach for Efficient Power Management in Datacenters
Jungmin Lee, Jin Lee, Jungsun Kim
Recently, the issue of efficient power management in datacenters as a part of green computing has gained prominence. For realizing efficient power management, effective power monitoring and analysis must be conducted for servers in a datacenter. However, an administrator should know the exact structure of the datacenter and its associated databases, and is required to analyze relationships among the observed data. This is because according to previous monitoring approaches, servers are usually managed using only databases. In addition, it is not possible to monitor data that are not indicated in databases. To overcome these drawbacks, we proposed an ontology-based monitoring approach. We constructed domain ontology for management servers at a datacenter, and mapped observed data onto the constructed domain ontology by using semantic annotation. Moreover, we defined query creation rules and server state rules. To demonstrate the proposed approach, we designed an ontology based monitoring system architecture, and constructed a knowledge system. Subsequently, we implemented the pilot system to verify its effectiveness.
On-the-fly Monitoring Tool for Detecting Data Races in Multithread Programs
Bong-Jun Paeng, Se-Won Park, In-Bon Kuh, Ok-Kyoon Ha, Yong-Kee Jun
It is difficult and cumbersome to figure out whether a multithread program runs with concurrency bugs, such as data races and atomicity violations, because there are many possible executions of the program and a lot of the defects are hard to reproduce. Hence, monitoring techniques for collecting and analyzing the information from program execution, such as thread executions, memory accesses, and synchronization information, are important to locate data races for debugging multithread programs. This paper presents an efficient and practical monitoring tool, called VcTrace, that analyzes the partial ordering of concurrent threads and events during an execution of the program based on the vector clock system. Empirical results on C/C++ benchmarks using Pthreads show that VcTrace is a sound and practical tool for on-the-fly data race detection as well as for analyzing multithread programs.
An Abnormal Activity Monitoring System Using Sensors and Video
Sang-soo Kim, Sun-woo Kim, Yeon-sung Choi
In this paper, we presents a system to ensure the safety of residents through appropriate action or alarm in case the residents occurs an emergency situation and abnormal activity. We collect and analysis real-time data of living environment of the residents using video and sensor. The existing system have been determined by using only the sensor data it have several problems. Our system attach camera to solve the existing system problem. We use weighted difference image and motion vector. The existing system, it takes about 48 hours to determine that an abnormal activity occurs. However, our system takes less than 1 hour.
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