• Title/Summary/Keyword: Alert Data

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A Study on Implementation of a Disaster Crisis Alert System based on National Disaster Management System

  • Hyong-Seop, Shim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.1
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    • pp.55-63
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    • 2023
  • In this paper, we propose a function and service of the Disaster Crisis Alert Management System that automatically analyzes the situation judgment criteria to issue a disaster crisis alert and a plan to operate in the National Disaster Management System(NDMS). In the event of a disaster, a crisis alert(interest-caution-alert-serious) is issued according to the crisis alert level. In order to automatically analyze and determine the crisis alert level, first, data collection, crisis alert level analysis, crisis alert level judgment, and disaster crisis alert management system that expresses the crisis alert level by spatial scale(province, city, district) were implemented. The crisis alert level was analyzed and expressed in two ways by applying the intelligent crisis alert level(determination of regional sensitivity, risk level, and crisis alert level) and the crisis alert standard of the crisis management manual(province-level standard setting). Second, standard metadata, linkage of situation information of target) and API standards for data provision are presented to jointly utilize data linkage and crisis alert data of the disaster and safety data sharing platform so that it can be operated within the NDMS.

Implementation of Analyzer of the Alert Data using Data Mining (데이타마이닝 기법을 이용한 경보데이타 분석기 구현)

  • 신문선;김은희;문호성;류근호;김기영
    • Journal of KIISE:Databases
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    • v.31 no.1
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    • pp.1-12
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    • 2004
  • As network systems are developed rapidly and network architectures are more complex than before, it needs to use PBNM(Policy-Based Network Management) in network system. Generally, architecture of the PBNM consists of two hierarchical layers: management layer and enforcement layer. A security policy server in the management layer should be able to generate new policy, delete, update the existing policy and decide the policy when security policy is requested. And the security policy server should be able to analyze and manage the alert messages received from Policy enforcement system in the enforcement layer for the available information. In this paper, we propose an alert analyzer using data mining. First, in the framework of the policy-based network security management, we design and implement an alert analyzes that analyzes alert data stored in DBMS. The alert analyzer is a helpful system to manage the fault users or hosts. Second, we implement a data mining system for analyzing alert data. The implemented mining system can support alert analyzer and the high level analyzer efficiently for the security policy management. Finally, the proposed system is evaluated with performance parameter, and is able to find out new alert sequences and similar alert patterns.

An Alert Data Mining Framework for Intrusion Detection System (침입탐지시스템의 경보데이터 분석을 위한 데이터 마이닝 프레임워크)

  • Shin, Moon-Sun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.1
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    • pp.459-466
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    • 2011
  • In this paper, we proposed a data mining framework for the management of alerts in order to improve the performance of the intrusion detection systems. The proposed alert data mining framework performs alert correlation analysis by using mining tasks such as axis-based association rule, axis-based frequent episodes and order-based clustering. It also provides the capability of classify false alarms in order to reduce false alarms. We also analyzed the characteristics of the proposed system through the implementation and evaluation of the proposed system. The proposed alert data mining framework performs not only the alert correlation analysis but also the false alarm classification. The alert data mining framework can find out the unknown patterns of the alerts. It also can be applied to predict attacks in progress and to understand logical steps and strategies behind series of attacks using sequences of clusters and to classify false alerts from intrusion detection system. The final rules that were generated by alert data mining framework can be used to the real time response of the intrusion detection system.

How to Measure Alert Fatigue by Using Physiological Signals?

  • Chae, Jeonghyeun;Kang, Youngcheol
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.760-767
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    • 2022
  • This paper introduces alert fatigue and presents methods to measure alert fatigue by using physiological signals. Alert fatigue is a phenomenon that which an individual is constantly exposed to frequent alarms and becomes desensitized to them. Blind spots are one leading cause of struck-by accidents, which is one most common causes of fatal accidents on construction sites. To reduce such accidents, construction equipment is equipped with an alarm system. However, the frequent alarm is inevitable due to the dynamic nature of construction sites and the situation can lead to alert fatigue. This paper introduces alert fatigue and proposes methods to use physiological signals such as electroencephalography, electrodermal activity, and event-related potential for the measurement of alert fatigue. Specifically, this paper presents how raw data from the physiological sensors measuring such signals can be processed to measure alert fatigue. By comparing the processed physiological data to behavioral data, validity of the measurement is tested. Using preliminary experimental results, this paper validates that physiological signals can be useful to measure alert fatigue. The findings of this study can contribute to investigating alert fatigue, which will lead to lowering the struck-by accidents caused by blind spots.

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Framework for False Alarm Pattern Analysis of Intrusion Detection System using Incremental Association Rule Mining

  • Chon Won Yang;Kim Eun Hee;Shin Moon Sun;Ryu Keun Ho
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.716-718
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    • 2004
  • The false alarm data in intrusion detection systems are divided into false positive and false negative. The false positive makes bad effects on the performance of intrusion detection system. And the false negative makes bad effects on the efficiency of intrusion detection system. Recently, the most of works have been studied the data mining technique for analysis of alert data. However, the false alarm data not only increase data volume but also change patterns of alert data along the time line. Therefore, we need a tool that can analyze patterns that change characteristics when we look for new patterns. In this paper, we focus on the false positives and present a framework for analysis of false alarm pattern from the alert data. In this work, we also apply incremental data mining techniques to analyze patterns of false alarms among alert data that are incremental over the time. Finally, we achieved flexibility by using dynamic support threshold, because the volume of alert data as well as included false alarms increases irregular.

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Design and evaluation of an alert message dissemination algorithm using fuzzy logic for VANETs

  • Bae, Ihn-Han
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.4
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    • pp.783-793
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    • 2010
  • Several multi-hop applications developed for vehicular ad hoc networks use broadcast as a means to either discover nearby neighbors or propagate useful traffic information to other vehicles located within a certain geographical area. However, the conventional broadcast mechanism may lead to the so-called broadcast storm problem, a scenario in which there is a high level of contention and collisions at the link layer due to an excessive number of broadcast packets. We present a fuzzy alert message dissemination algorithm to improve performance for road safety alert application in Vehicular Ad-hoc Network (VANET). In the proposed algorithm, when a vehicle receives an alert message for the first time, the vehicle rebroadcasts the alert message according to the fuzzy control rules for rebroadcast degree, where the rebroadcast degree depends on the current traffic density of the road and the distance between source vehicle and destination vehicle. Also, the proposed algorithm is the hybrid algorithm that uses broadcast protocol together with token protocol according to traffic density. The performance of the proposed algorithm is evaluated through simulation and compared with that of other alert message dissemination algorithms.

Implementation of Data Mining Engine for Analyzing Alert Data of Security Policy Server (보안정책 서버의 경보데이터 분석을 위한 데이터마이닝 엔진의 구현)

  • 정경자;신문선
    • Journal of the Korea Society of Computer and Information
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    • v.7 no.4
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    • pp.141-149
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    • 2002
  • Recently, a number of network systems are developed rapidly and network architectures are more complex than before, and a policy-based network management should be used in network system. Especially, a new paradigm that policy-based network management can be applied for the network security is raised. A security policy server in the management layer can generate new policy, delete. update the existing policy and decide the policy when security policy is requested. The security server needs to analyze and manage the alert message received from server Policy enforcement system in the enforcement layer for the available information. In this paper, we implement an alert analyzer that analyze the stored alert data for making of security policy efficiently in framework of the policy-based network security management. We also propose a data mining system for the analysis of alert data The implemented mining system supports alert analyzer and the high level analyzer efficiently for the security.

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Correlation among the Medication Error Risk of High-alert Medication, Attitudes to Single Checking Medication, and Medication Safety Activities of Nurses in the Intensive Care Unit (중환자실 간호사의 고위험약물에 대한 투약오류 위험과 약물단독확인 태도, 투약안전간호활동 간의 상관성)

  • Kim, Myoung Soo;Jung, Hyun Kyeong
    • Journal of Korean Critical Care Nursing
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    • v.8 no.1
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    • pp.1-10
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    • 2015
  • This study was conducted to examine the relationship among the error risk of high-alert medication, attitudes to single-person checking of medication, and medication safety activities. The participants were 60 nurses working in the intensive care unit. Data were analyzed using descriptive analysis, t-test, analysis of variance, and Pearson's correlation coefficient. The mean scores of the knowledge and certainty of high-alert medication were $0.71{\pm}0.11$ and $2.74{\pm}0.59$, respectively. The mean score of the error risk of high-alert medication was $1.63{\pm}0.24$ and that of attitudes to single checking medication was $3.32{\pm}0.49$. The error risk of high-alert medication had a positive correlation with nurses' attitudes to single checking medication (r = .258, p = .047), which is correlated with the scores for certainty of knowledge (r = .284, p = .028). Based on the results of this study, continuing education for high-alert medication and the development of an accurate protocol for single checking medication are needed to improve the stability of high-alert medication.

A Synchronous Cooperative Communication for Emergency Alert Broadcast Based on Cellular Systems (이동통신 기반의 재난경보 방송을 위한 동기식 협력통신 방식)

  • Chang, Sekchin
    • Journal of Broadcast Engineering
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    • v.19 no.2
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    • pp.184-194
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    • 2014
  • The CBS methodology has been utilized in order to make a rapid broadcast of emergency alert based on cellular systems. We present a synchronous cooperative communication method for the CBS. Especially, we suggest a synchronization scheme and a data recovery approach for high-rate cooperative communications. For the high-rate transfer of emergency alert, the cyclic prefix is added to the preamble for the synchronization. For the data recovery, the Alamouti technique is utilized on frequency domain, which is similar to SC-FDE. The simulation results confirm that our proposed scheme is very suitable for the CBS.

Design and evaluation of a VPRS-based misbehavior detection scheme for VANETs (차량애드혹망을 위한 가변정밀도 러프집합 기반 부정행위 탐지 방법의 설계 및 평가)

  • Kim, Chil-Hwa;Bae, Ihn-Han
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.6
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    • pp.1153-1166
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    • 2011
  • Detecting misbehavior in vehicular ad-hoc networks is very important problem with wide range of implications including safety related and congestion avoidance applications. Most misbehavior detection schemes are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners. Because of rational behavior, it is more important to detect false information than to identify misbehaving nodes. In this paper, we propose the variable precision rough sets based misbehavior detection scheme which detects false alert message and misbehaving nodes by observing their action after sending out the alert messages. In the proposed scheme, the alert information system, alert profile is constructed from valid actions of moving nodes in vehicular ad-hoc networks. Once a moving vehicle receives an alert message from another vehicle, it finds out the alert type from the alert message. When the vehicle later receives a beacon from alert raised vehicle after an elapse of time, then it computes the relative classification error by using variable precision rough sets from the alert information system. If the relative classification error is lager than the maximum allowable relative classification error of the alert type, the vehicle decides the message as false alert message. Th performance of the proposed scheme is evaluated as two metrics: correct ratio and incorrect ratio through a simulation.