• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.1-9
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• 2021

Disaster alerts are text messages sent by government to people in the area in the event of a disaster. Since the number of disaster alerts has increased, the number of people who block disaster alerts is increasing as many unnecessary disaster alerts are being received. To solve this problem, this study proposes a deep learning model that automatically classifies disaster alerts by disaster type, and allows only necessary disaster alerts to be received according to the recipient. The proposed model embeds disaster alerts via KoBERT and classifies them by disaster type with LSTM. As a result of classifying disaster alerts using 3 combinations of parts of speech: [Noun], [Noun + Adjective + Verb] and [All parts], and 4 classification models: Proposed model, Keyword classification, Word2Vec + 1D-CNN and KoBERT + FFNN, the proposed model achieved the highest performance with 0.988954 accuracy.

• YAKHAK HOEJI
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• v.59 no.6
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• pp.278-283
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• 2015

The computerized prospective Drug Utilization Review (DUR) program supported by the Korean government has provided alerts to physicians and pharmacists since December 2010. This study aims to propose and apply the tiering system in "drug combinations to avoid (DCA)" and "age-precaution" alerts based on severity to improve the compliance of users. To propose the severity and clinical importance of 647 DCA alerts and 140 age precautions, a Delphi evaluation survey was conducted. An expert panel comprising 5 clinical pharmacists and 5 physicians were participated in mail surveys. Based on the results of Delphi survey, DCA pairs were classified into 3 groups; group 1 (70.6%), 2 (26.9%), and 3 (2.8%). Drug-age precaution ingredients were also classified into three groups; group 1 (53.6%), group 2 (40.7%), and group 3 (5.7%). When this grouping was applied to claim data from 2011 to 2013, the majority of alerts had occurred in the groups of high severity. Presenting DUR alerts with severity level is expected to improve the compliance of clinicians. The implementation of tiering system in DUR criteria should be considered.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.799-808
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• 2021

The frequency of KPAS alerts is causing the behavior of blocking KPAS alerts. It is necessary to control the frequency of KPAS alerts to prevent this behavior. This study analyzed the effect of problematic frequency types on the adjustment expectation of KPAS alerts. Three types of problematic frequency were selected: dailiness, other areas, similarity. An online survey with 1,212 participants was analyzed, with the following result. The three types of problematic frequency positively influenced the adjustment expectation of KPAS alerts. It turned out that the unique contribution of individual variables was found in the order of similarity, other areas, and dailiness. These results are meaningful in that they can be used as basic data for the improvement of the frequency of KPAS alerts.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.39-49
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• 2014

Cyber threats on the Internet are tremendously increasing and their techniques are also evolving constantly. Intrusion Detection System (IDS) is one of the powerful solutions for detecting and analyzing the cyber attacks in realtime. Most organizations deploy it into their networks and operate it for security monitoring and response service. However, IDS has a fatal problem in that it raises a large number of alerts and most of them are false positives. In order to cope with this problem, many approaches have been proposed for the purpose of automatically identifying whether the IDS alerts are caused by real attacks or not. In this paper, we present an alert verification method based on correlation analysis between vulnerability inspection results for real systems that should be protected and the IDS alerts. In addition, we carry out practical experiments to demonstrate the effectiveness of the proposed verification method using two types of real data, i.e., the IDS alerts and the vulnerability inspection results.

• Journal of KIISE:Databases
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• v.34 no.6
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• pp.473-482
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• 2007

Network-based IDS(Intrusion Detection System) gathers network packet data and analyzes them into attack or normal. They raise alarm when possible intrusion happens. But they often output a large amount of low-level of incomplete alert information. Consequently, a large amount of incomplete alert information that can be unmanageable and also be mixed with false alerts can prevent intrusion response systems and security administrator from adequately understanding and analyzing the state of network security, and initiating appropriate response in a timely fashion. So it is important for the security administrator to reduce the redundancy of alerts, integrate and correlate security alerts, construct attack scenarios and present high-level aggregated information. False alarm rate is the ratio between the number of normal connections that are incorrectly misclassified as attacks and the total number of normal connections. In this paper we propose a false alarm classification model to reduce the false alarm rate using classification analysis of data mining techniques. The proposed model can classify the alarms from the intrusion detection systems into false alert or true attack. Our approach is useful to reduce false alerts and to improve the detection rate of network-based intrusion detection systems.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.76-83
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• 2023

Purpose: In emergency situations such as earthquakes, heavy rains, typhoons, or fires, when quick delivery of emergency alerts is crucial, the hearing impaired are the ones who are the most disadvantaged and vulnerable when alerts are only delivered through auditory or text alerts. They can't perceive auditory information, and many have difficulties in fast understanding text-based alerts. Method: An alert system that can deliver pictograms for specific disaster situations has been devised. Then, a novel approach based on artificial intelligence has been studied so that the pictograms for specific disaster situations can be chosen instantly once a disaster alert is issued in text. Result: A disaster alert system that delivers pictograms for specific disaster situations was developed and a novel method has been suggested for automatic delivery. Conclusion: A system to instantaneously deliver disaster alert information in pictograms has been developed to improve alert delivery to the populations vulnerable to disaster due to hearing impairment by the instantaneous understanding of disaster situations through visual information.

• Journal of Navigation and Port Research
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• v.46 no.1
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• pp.11-17
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• 2022

The high wind wave alert has a great impact on ships and maritime service workers navigating in the vicinity of Korea. This study aims to evaluate the appropriateness of the high wind wave alert by comparing and analyzing the observation data of major marine meteorological buoys with the high wind wave alerts in the coastal sea and offshore of the West Sea, South Sea, and the East Sea announced by the Korea Meteorological Administration for the past 11 years(2010-2020). As a result of comparing the daily, monthly, and annual statistics of the high wind wave alert and marine meteorological buoy observation data for each sea area by annual, monthly, and seasonal average, the accuracy of high wind wave alerts was very low across the entire sea area. In particular, it was analyzed that the accuracy in the coastal sea of the South Sea and Jejudo was the lowest in winter. It was confirmed that the accuracy of marine weather forecasts and alerts needs to be improved when considering the effects of the high wind wave alerts on fishing vessels, passenger ships operations and tourism, and marine leisure activities.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.45-68
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• 2022

The central and local governments of the Republic of Korea provided information necessary for disaster response through wireless emergency alerts (WEAs) in order to overcome the pandemic situation in which COVID-19 rapidly spreads. Among all channels for delivering disaster information, wireless emergency alert is the most efficient, and since it adopts the CBS(Cell Broadcast Service) method that broadcasts directly to the mobile phone, it has the advantage of being able to easily access disaster information through the mobile phone without the effort of searching. In this study, the characteristics of wireless emergency alerts sent to Seoul during the past year and one month (January 2020 to January 2021) were derived through various text mining methodologies, and various types of information contained in wireless emergency alerts were analyzed. In addition, it was confirmed through the population mobility by age in the districts of Seoul that what kind of influence it had on the movement behavior of people. After going through the process of classifying key words and information included in each character, text analysis was performed so that individual sent characters can be used as an analysis unit by applying a document cluster analysis technique based on the included words. The number of WEAs sent to the Seoul has grown dramatically since the spread of Covid-19. In January 2020, only 10 WEAs were sent to the Seoul, but the number of the WEAs increased 5 times in March, and 7.7 times over the previous months. Since the basic, regional local government were authorized to send wireless emergency alerts independently, the sending behavior of related to wireless emergency alerts are different for each local government. Although most of the basic local governments increased the transmission of WEAs as the number of confirmed cases of Covid-19 increases, the trend of the increase in WEAs according to the increase in the number of confirmed cases of Covid-19 was different by region. By using structured econometric model, the effect of disaster information included in wireless emergency alerts on population mobility was measured by dividing it into baseline effect and accumulating effect. Six types of disaster information, including date, order, online URL, symptom, location, normative guidance, were identified in WEAs and analyzed through econometric modelling. It was confirmed that the types of information that significantly change population mobility by age are different. Population mobility of people in their 60s and 70s decreased when wireless emergency alerts included information related to date and order. As date and order information is appeared in WEAs when they intend to give information about Covid-19 confirmed cases, these results show that the population mobility of higher ages decreased as they reacted to the messages reporting of confirmed cases of Covid-19. Online information (URL) decreased the population mobility of in their 20s, and information related to symptoms reduced the population mobility of people in their 30s. On the other hand, it was confirmed that normative words that including the meaning of encouraging compliance with quarantine policies did not cause significant changes in the population mobility of all ages. This means that only meaningful information which is useful for disaster response should be included in the wireless emergency alerts. Repeated sending of wireless emergency alerts reduces the magnitude of the impact of disaster information on population mobility. It proves indirectly that under the prolonged pandemic, people started to feel tired of getting repetitive WEAs with similar content and started to react less. In order to effectively use WEAs for quarantine and overcoming disaster situations, it is necessary to reduce the fatigue of the people who receive WEA by sending them only in necessary situations, and to raise awareness of WEAs.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.317-324
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• 2016

This paper proposes a message transfer application using smartphone with NFC(Near Field Communication) and GCM(Goolge Cloud Messaging) technology for prevention of personal information leakage. In implementing for the proposed system, we design a NFC-based vehicle status alerts service which make it possible to communicate with smartpone message without phone-number between a car driver and an unspecified person. The application provides message communication mechanism without exposing the real phone number, using the NFC tag written with the driver's smartphone device ID and GCM push messages. Through the evaluation result of the actual implemented application, the proposed system can be efficient technology in protection for leakage of personal information such as personal phone- number in daily life.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.71.2-71.2
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• 2019

We have developed and tested a prototype system to process transient alert messages from the currently working facilities such as Gaia and GCN notices. Our experiments with the prototype focus on developing a platform that can be used in the LSST era with about 10 million alerts per night and helping Korean community members with the automated processing environment to provide auxiliary information for every alert message. The system consists of a message broker implemented by Redis and multiple message subscribers specialized for specific scientific interests. The current implementation of the entire system allows new Korean members to adopt their own processing chains receiving the messages from our local broker. We welcome experimental ideas and opinions from the Korean community about the current message processing system. We plan to test the current system with the ZTF alerts in the near future.