• Title/Summary/Keyword: software updates

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A Selective Compression Strategy for Performance Improvement of Database Compression (데이터베이스 압축 성능 향상을 위한 선택적 압축 전략)

  • Lee, Ki-Hoon
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.9
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    • pp.371-376
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    • 2015
  • The Internet of Things (IoT) significantly increases the amount of data. Database compression is important for big data because it can reduce costs for storage systems and save I/O bandwidth. However, it could show low performance for write-intensive workloads such as OLTP due to the updates of compressed pages. In this paper, we present practical guidelines for the performance improvement of database compression. Especially, we propose the SELECTIVE strategy, which compresses only tables whose space savings are close to the expected space savings calculated by the compressed page size. Experimental results using the TPC-C benchmark and MySQL show that the strategy can achieve 1.1 times better performance than the uncompressed counterpart with 17.3% space savings.

Directional Particle Filter Using Online Threshold Adaptation for Vehicle Tracking

  • Yildirim, Mustafa Eren;Salman, Yucel Batu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.2
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    • pp.710-726
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    • 2018
  • This paper presents an extended particle filter to increase the accuracy and decrease the computation load of vehicle tracking. Particle filter has been the subject of extensive interest in video-based tracking which is capable of solving nonlinear and non-Gaussian problems. However, there still exist problems such as preventing unnecessary particle consumption, reducing the computational burden, and increasing the accuracy. We aim to increase the accuracy without an increase in computation load. In proposed method, we calculate the direction angle of the target vehicle. The angular difference between the direction of the target vehicle and each particle of the particle filter is observed. Particles are filtered and weighted, based on their angular difference. Particles with angular difference greater than a threshold is eliminated and the remaining are stored with greater weights in order to increase their probability for state estimation. Threshold value is very critical for performance. Thus, instead of having a constant threshold value, proposed algorithm updates it online. The first advantage of our algorithm is that it prevents the system from failures caused by insufficient amount of particles. Second advantage is to reduce the risk of using unnecessary number of particles in tracking which causes computation load. Proposed algorithm is compared against camshift, direction-based particle filter and condensation algorithms. Results show that the proposed algorithm outperforms the other methods in terms of accuracy, tracking duration and particle consumption.

Efficient Continuous Skyline Query Processing Scheme over Large Dynamic Data Sets

  • Li, He;Yoo, Jaesoo
    • ETRI Journal
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    • v.38 no.6
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    • pp.1197-1206
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    • 2016
  • Performing continuous skyline queries of dynamic data sets is now more challenging as the sizes of data sets increase and as they become more volatile due to the increase in dynamic updates. Although previous work proposed support for such queries, their efficiency was restricted to small data sets or uniformly distributed data sets. In a production database with many concurrent queries, the execution of continuous skyline queries impacts query performance due to update requirements to acquire exclusive locks, possibly blocking other query threads. Thus, the computational costs increase. In order to minimize computational requirements, we propose a method based on a multi-layer grid structure. First, relational data object, elements of an initial data set, are processed to obtain the corresponding multi-layer grid structure and the skyline influence regions over the data. Then, the dynamic data are processed only when they are identified within the skyline influence regions. Therefore, a large amount of computation can be pruned by adopting the proposed multi-layer grid structure. Using a variety of datasets, the performance evaluation confirms the efficiency of the proposed method.

Design and Prototype Implementation of the Curved Plates Flow Tracking and Monitoring System using RFID (RFID 기술을 이용한 곡가공 부재 추적 및 모니터링 시스템 설계 및 프로토타입의 구현)

  • Noh, Jac-Kyou;Shin, Jong-Gye
    • Korean Journal of Computational Design and Engineering
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    • v.14 no.6
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    • pp.424-433
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    • 2009
  • In order to improve productivity and efficiency of ship production process, production technology converged with Information Technology can be considered. Mid-term scheduling based on long-term schedule of ship building and execution planning based on short-term production schedule have an important role in ship production processes and techniques. However, data used in the scheduling are from the experiences of the past, cognitive, and often inaccurate, moreover the updates of the data by formatted documents are not being performed efficiently. This paper designs the tracking and monitoring system for the curved plates forming process with shop level. At first step to it, we redefine and analyze the curved plates forming process by using SysML. From the definition and analysis of the curved plates forming process, we design the system with respect to operational view considering operational environment and interactions between systems included and scenario about operation, and with respect to system view considering functionalities and interfaces of the system. In order to study the feasibility of the system designed, a prototype of the system has been implemented with 13.56 MHz RHD hardware and application software.

Development Hi-DPI Algorithm for High Speed Packet Filtering of Anti-DDoS based on HW (하드웨어 기반 Anti-DDoS 대응 장비 고속 패킷 필터링을 위한 Hi-DPI 알고리즘 연구)

  • Kim, Jeom Goo
    • Convergence Security Journal
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    • v.17 no.2
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    • pp.41-51
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    • 2017
  • The explosive increase in the range of Internet usage gradually makes the speed and capacity of network high-speed, rapidly evolving it into mass storage. Accordingly, network equipment such as switch and router are coping with it through hardware-based rapid technological evolution, but as the technological development of the most basic and essential network security system in the hyper-connected society requires frequent alterations and updates about the security issues and signatures of tens of thousands, so it is not easy to overcome the technical limitations based on the software. In this paper, to improve problems in installing and operating such anti-DDoS devices, we propose a Hi-DPI algorithm best reflecting the hardware characteristics and parallel processing characteristics of FPGA (Field Programmable Gate Array), and would verify the practicality.

Technology and Policy Post-Security Management Framework for IoT Electrical Safety Management (IoT 제품의 안전 관리를 위한 기술 및 정책적 사후 보안관리 프레임워크)

  • Lee, Donghyeok;Park, Namje
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.12
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    • pp.1879-1888
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    • 2017
  • The Internet of Things (IoT) environment has been gradually approaching reality, and although it provides great convenience, security threats are increasing accordingly. For the IoT environment to settle safely, careful consideration of information security is necessary. Although many security measures in the design and development stages of IoT products have been studied thus far, apart from them, the establishment of systems and countermeasures for post management after the launch of IoT products is also very important. In the present paper, a technical and policy post-security management framework is proposed to provide secure IoT environments. The proposed framework defines the concrete response procedures of individual entities such as users, manufacturers, and competent authorities in the case of the occurrence of security flaws after launching IoT products, and performs appropriate measures such as software updates and recalls based on an assessment of the risk of security flaws.

Hierarchical Location Caching Scheme for Mobile Object Tracking in the Internet of Things

  • Han, Youn-Hee;Lim, Hyun-Kyo;Gil, Joon-Min
    • Journal of Information Processing Systems
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    • v.13 no.5
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    • pp.1410-1429
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    • 2017
  • Mobility arises naturally in the Internet of Things networks, since the location of mobile objects, e.g., mobile agents, mobile software, mobile things, or users with wireless hardware, changes as they move. Tracking their current location is essential to mobile computing. To overcome the scalability problem, hierarchical architectures of location databases have been proposed. When location updates and lookups for mobile objects are localized, these architectures become effective. However, the network signaling costs and the execution number of database operations increase particularly when the scale of the architectures and the numbers of databases becomes large to accommodate a great number of objects. This disadvantage can be alleviated by a location caching scheme which exploits the spatial and temporal locality in location lookup. In this paper, we propose a hierarchical location caching scheme, which acclimates the existing location caching scheme to a hierarchical architecture of location databases. The performance analysis indicates that the adjustment of such thresholds has an impact on cost reduction in the proposed scheme.

A Study on Malicious Code Detection Using Blockchain and Deep Learning (블록체인과 딥러닝을 이용한 악성코드 탐지에 관한 연구)

  • Lee, Deok Gyu
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.2
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    • pp.39-46
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    • 2021
  • Damages by malware have recently been increasing. Conventional signature-based antivirus solutions are helplessly vulnerable to unprecedented new threats such as Zero-day attack and ransomware. Despite that, many enterprises have retained signature-based antivirus solutions as part of the multiple endpoints security strategy. They do recognize the problem. This paper proposes a solution using the blockchain and deep learning technologies as the next-generation antivirus solution. It uses the antivirus software that updates through an existing DB server to supplement the detection unit and organizes the blockchain instead of the DB for deep learning using various samples and forms to increase the detection rate of new malware and falsified malware.

Buffer Overflow Attack and Defense Techniques

  • Alzahrani, Sabah M.
    • International Journal of Computer Science & Network Security
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    • v.21 no.12
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    • pp.207-212
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    • 2021
  • A buffer overflow attack is carried out to subvert privileged program functions to gain control of the program and thus control the host. Buffer overflow attacks should be prevented by risk managers by eradicating and detecting them before the software is utilized. While calculating the size, correct variables should be chosen by risk managers in situations where fixed-length buffers are being used to avoid placing excess data that leads to the creation of an overflow. Metamorphism can also be used as it is capable of protecting data by attaining a reasonable resistance level [1]. In addition, risk management teams should ensure they access the latest updates for their application server products that support the internet infrastructure and the recent bug reports [2]. Scanners that can detect buffer overflows' flaws in their custom web applications and server products should be used by risk management teams to scan their websites. This paper presents an experiment of buffer overflow vulnerability and attack. The aims to study of a buffer overflow mechanism, types, and countermeasures. In addition, to comprehend the current detection plus prevention approaches that can be executed to prevent future attacks or mitigate the impacts of similar attacks.

Factors Influencing Successful Implementation of Cloud ERP Solutions at Small and Medium Enterprises in Vietnam

  • CHU, Hai Hong Thi;NGUYEN, Thuy Van
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.5
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    • pp.239-250
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    • 2022
  • A business's Enterprise Resource Planning (ERP) solution is software that fully integrates the services that businesses require, continuously updates business processes and department operations in real-time, and so aids in the successful management of enterprise resources. Previously, ERP solutions were often deployed for large enterprises, but along with the strong digital transformation process, many small and medium enterprises have been deploying Cloud ERP (CERP) solutions. The objective of the study is to measure the factors affecting the successful implementation of CERP solutions at small and medium enterprises and the impact of successful implementation of CERP solutions on business process re-engineering and enterprise performance. Using a quantitative method based on data collected from 230 small and medium enterprises in Vietnam that have been implementing CERP solutions, the results show that there are 5 factors affecting, which are Organizational ERP Strategic, Top management Commitment, Data Security, Training in ERP Projects, Organizational Culture. Research results also show that Successful implementation of CERP has a direct impact on business process re-engineering and business performance. Based on the results, the study has made a number of policy implications in the successful implementation of CERP towards re-engineering business processes to improve the performance of small and medium enterprises.