• Title/Summary/Keyword: Security Measurement

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Establishment of Evaluation System for Disaster Resilience Focusing on the Local Road under Complex Disaster (복합재해 발생 예상 시 지방도로 중심의 재난 레질리언스 평가체계 구축)

  • Kim, Young-Hwan;Jun, Kye-Won
    • Journal of Korean Society of Disaster and Security
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    • v.13 no.4
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    • pp.37-46
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    • 2020
  • Although the importance of resilience is emerging around the world, the single definition of resilience related to natural disasters is not clear. The reason for this is that there is no specific definition of how the definition of resilience relates to similar terms such as vulnerability, recovery, adaptability, and sustainability. In addition, it is because each country and region have different geographic and geological characteristics, and each measurement index is different, just as typhoons, droughts, and earthquakes have different types of disasters. Therefore, in this study, the definition of resilience is reflected in the spatial characteristics of this study as the ability to recover from'complex disasters (concentrated heavy rain, landslides, earth and stone flows) occurring on local roads or on local roads adjacent to people or facilities. Defined. And it was divided into DRR: Disaster Resilience focusing on the Road. In addition, domestic and foreign literature surveys were conducted to derive road-centered disaster resilience factors, and a hierarchical structure was established and AHP survey was conducted to establish a DRR evaluation system. As a result of the analysis of the AHP survey, the weight of direct road disaster influencing factors (drainage facilities, protection facilities, etc.) located inside local roads was 0.742, and the weight of indirect road disaster influencing factors (population, property, etc.) located near local roads. Was found to be 0.258, indicating that the direct impact factor of road disaster was relatively higher than that of the indirect impact factor.

The Effect of Road Networks on Urban Resilience in Flooding (도시침수 시 도로네트워크가 도시회복도에 미치는 영향 분석)

  • Hyung Jun Park;Dong Hyun Kim;Hyun Jung Lee;Seung Oh Lee
    • Journal of Korean Society of Disaster and Security
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    • v.16 no.2
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    • pp.85-98
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    • 2023
  • Flood is one of the most frequent natural disasters worldwide. In Korea, the probability of urban flooding is greatly increasing due to complex factors such as global warming, an increase in impervious areas, and limitations in expanding water supply facilities in existing urban areas. However, large-scale civil engineering works to prevent urban inundation are socially and economically difficult to obtain national consent. Recently the importance of resilience, which is the ability to return to the original state after a disaster through rapid recovery while preparing for natural disasters to a level that the local community can afford socially and economically, is increasing. Accordingly, various studies on urban resilience have been conducted, but the resilience measurement method related to the lifeline that provides essential services of the city is insufficient. However, among lifelines, road networks are important facilities for the transportation of recovery resources and rapid recovery in the event of a natural disaster, so road networks are a major factor that must be considered when measuring the degree of recovery of a city in the field of natural disasters. Therefore, this study proposes a recovery evaluation method considering the characteristics of resilience and road networks in the urban flooding field and analyzes the effect of road networks on urban resilience.

A Study on Open Source Version and License Detection Tool (오픈소스 버전 및 라이선스 탐지 도구에 관한 연구)

  • Ki-Hwan Kim;Seong-Cheol Yoon;Su-Hyun Kim;Im-Yeong Lee
    • The Transactions of the Korea Information Processing Society
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    • v.13 no.7
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    • pp.299-310
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    • 2024
  • Software is expensive, labor-intensive, and time-consuming to develop. To solve this problem, many organizations turn to publicly available open source, but they often do so without knowing exactly what they're getting into. Older versions of open source have various security vulnerabilities, and even when newer versions are released, many users are still using them, exposing themselves to security threats. Additionally, compliance with licenses is essential when using open source, but many users overlook this, leading to copyright issues. To solve this problem, you need a tool that analyzes open source versions, vulnerabilities, and license information. Traditional Blackduck provide a wealth of open source information when you request the source code, but it's a heavy lift to build the environment. In addition, Fossology extracts the licenses of open source, but does not provide detailed information such as versions because it does not have its own database. To solve these problems, this paper proposes a version and license detection tool that identifies the open source of a user's source code by measuring the source code similarity, and then detects the version and license. The proposed method improves the accuracy of similarity over existing source code similarity measurement programs such as MOSS, and provides users with information about licenses, versions, and vulnerabilities by analyzing each file in the corresponding open source in a web-based lightweight platform environment. This solves capacity issues such as BlackDuck and the lack of open source details such as Fossology.

Personal Information Detection by Using Na$\ddot{i}$ve Bayes Methodology (Na$\ddot{i}$ve Bayes 방법론을 이용한 개인정보 분류)

  • Kim, Nam-Won;Park, Jin-Soo
    • Journal of Intelligence and Information Systems
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    • v.18 no.1
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    • pp.91-107
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    • 2012
  • As the Internet becomes more popular, many people use it to communicate. With the increasing number of personal homepages, blogs, and social network services, people often expose their personal information online. Although the necessity of those services cannot be denied, we should be concerned about the negative aspects such as personal information leakage. Because it is impossible to review all of the past records posted by all of the people, an automatic personal information detection method is strongly required. This study proposes a method to detect or classify online documents that contain personal information by analyzing features that are common to personal information related documents and learning that information based on the Na$\ddot{i}$ve Bayes algorithm. To select the document classification algorithm, the Na$\ddot{i}$ve Bayes classification algorithm was compared with the Vector Space classification algorithm. The result showed that Na$\ddot{i}$ve Bayes reveals more excellent precision, recall, F-measure, and accuracy than Vector Space does. However, the measurement level of the Na$\ddot{i}$ve Bayes classification algorithm is still insufficient to apply to the real world. Lewis, a learning algorithm researcher, states that it is important to improve the quality of category features while applying learning algorithms to some specific domain. He proposes a way to incrementally add features that are dependent on related documents and in a step-wise manner. In another experiment, the algorithm learns the additional dependent features thereby reducing the noise of the features. As a result, the latter experiment shows better performance in terms of measurement than the former experiment does.

A Study on the Effects of the Information Asset Protection Performance on the Organization Performance: Management Activity and Control Activity (정보자산보호 성과가 조직성과에 미치는 영향에 관한 연구: 관리활동과 통제활동을 중심으로)

  • Kim, Kyung-Kyu;Shin, Ho-Kyoung;Park, Sung-Sik;Kim, Beom-Soo
    • Journal of Information Management
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    • v.40 no.3
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    • pp.61-77
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    • 2009
  • Recently, enterprises are protecting information assets with the various means of control and management. Nevertheless, they are confronted with the dilemma which the higher securitylevel they request, the lesser efficiency and productivity in short terms they acquire by the inconvenience of business process. In addition, in spite of the steady increase of organization's investment on information protection, the systematic way for the performance measurement of information protection has not been suggested, so that in reality, it is difficult to make the decision to invest on information-protection and elicit the direction to improve it. For this reason, this study intended to establish the concept of the protection and security of information assets of enterprises and to categorize the type of activities to protect information assets into management activity and control activity, and analyze the effects of management activity and control activity for information asset protection on the performance of information asset protection activity and organization. For this research, questionnaire survey was conducted with literature study and the PLS(Partial Least Square) was used to analyze the measurement model and hypotheses testing. The PLS analysis results indicate that management activity for information asset protection affects information asset protection performance. Further, organizational performance is influenced by information asset protection performance. Practical implications of these findings and future research implications are also discussed.

Development of Authentication Service Model Based Context-Awareness for Accessing Patient's Medical Information (환자 의료정보 접근을 위한 상황인식 기반의 인증서비스 모델 개발)

  • Ham, Gyu-Sung;Joo, Su-Chong
    • Journal of Internet Computing and Services
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    • v.22 no.1
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    • pp.99-107
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    • 2021
  • With the recent establishment of a ubiquitous-based medical and healthcare environment, the medical information system for obtaining situation information from various sensors is increasing. In the medical information system environment based on context-awareness, the patient situation can be determined as normal or emergency using situational information. In addition, medical staff can easily access patient information after simple user authentication using ID and Password through applications on smart devices. However, these services of authentication and patient information access are staff-oriented systems and do not fully consider the ubiquitous-based healthcare information system environment. In this paper, we present a authentication service model based context-awareness system for providing situational information-driven authentication services to users who access medical information, and implemented proposed system. The authentication service model based context-awareness system is a service that recognizes patient situations through sensors and the authentication and authorization of medical staff proceed differently according to patient situations. It was implemented using wearables, biometric data measurement modules, camera sensors, etc. to configure various situational information measurement environments. If the patient situation was emergency situation, the medical information server sent an emergency message to the smart device of the medical staff, and the medical staff that received the emergency message tried to authenticate using the application of the smart device to access the patient information. Once all authentication was completed, medical staff will be given access to high-level medical information and can even checked patient medical information that could not be seen under normal situation. The authentication service model based context-awareness system not only fully considered the ubiquitous medical information system environment, but also enhanced patient-centered systematic security and access transparency.

Design of FMCW Radar Signal Processor for Human and Objects Classification Based on Respiration Measurement (호흡 기반 사람과 사물 구분 가능한 FMCW 레이다 신호처리 프로세서의 설계)

  • Lee, Yungu;Yun, Hyeongseok;Kim, Suyeon;Heo, Seongwook;Jung, Yunho
    • Journal of Advanced Navigation Technology
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    • v.25 no.4
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    • pp.305-312
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    • 2021
  • Even though various types of sensors are being used for security applications, radar sensors are being suggested as an alternative due to the privacy issues. Among those radar sensors, PD radar has high-complexity receiver, but, FMCW radar requires fewer resources. However, FMCW has disadvantage from the use of 2D-FFT which increases the complexity, and it is difficult to distinguish people from objects those are stationary. In this paper, we present the design and the implementation results of the radar signal processor (RSP) that can distinguish between people and object by respiration measurement using phase estimation without 2D-FFT. The proposed RSP is designed with Verilog-HDL and is implemented on FPGA device. It was confirmed that the proposed RSP includes 6,425 LUT, 4,243 register, and 12,288 memory bits with 92.1% accuracy for target's breathing status.

Detection of Traffic Anomalities using Mining : An Empirical Approach (마이닝을 이용한 이상트래픽 탐지: 사례 분석을 통한 접근)

  • Kim Jung-Hyun;Ahn Soo-Han;Won You-Jip;Lee Jong-Moon;Lee Eun-Young
    • Journal of KIISE:Information Networking
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    • v.33 no.3
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    • pp.201-217
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    • 2006
  • In this paper, we collected the physical traces from high speed Internet backbone traffic and analyze the various characteristics of the underlying packet traces. Particularly, our work is focused on analyzing the characteristics of an anomalous traffic. It is found that in our data, the anomalous traffic is caused by UDP session traffic and we determined that it was one of the Denial of Service attacks. In this work, we adopted the unsupervised machine learning algorithm to classify the network flows. We apply the k-means clustering algorithm to train the learner. Via the Cramer-Yon-Misses test, we confirmed that the proposed classification method which is able to detect anomalous traffic within 1 second can accurately predict the class of a flow and can be effectively used in determining the anomalous flows.

Traffic Anomaly Detection for Campus Networks using Fisher Linear Discriminant (Fisher 선형 분류법을 이용한 비정상 트래픽 탐지)

  • Park, Hyun-Hee;Kim, Mee-Joung;Kang, Chul-Hee
    • Journal of IKEEE
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    • v.13 no.2
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    • pp.140-149
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    • 2009
  • Traffic anomaly detection is one of important technology that should be considered in network security and administration. In this paper, we propose an abnormal traffic detection mechanism that includes traffic monitoring and traffic analysis. We develop analytical passive monitoring system called WISE-Mon which can inspect traffic behavior. We establish a criterion by analyzing the characteristics of a traffic training set. To detect abnormal traffic, we derive a hyperplane by using Fisher linear discriminant and chi-square distribution as well as the analyzed characteristics of traffic. Our mechanism can support reliable results for traffic anomaly detection and is compatible to real-time detection. In addition, since the trend of traffic can be changed as time passes, the hyperplane has to be updated periodically to reflect the changes. Accordingly, we consider the self-learning algorithm which reflects the trend of the traffic and so enables to increase the pliability of detection probability. Numerical results are presented to validate the accuracy of proposed mechanism. It shows that the proposed mechanism is reliable and relevant for traffic anomaly detection.

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Noisy Weighted Data Aggregation for Smart Meter Privacy System (스마트 미터 프라이버시 시스템을 위한 잡음 가중치 데이터 집계)

  • Kim, Yong-Gil;Moon, Kyung-Il
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.3
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    • pp.49-59
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    • 2018
  • Smart grid system has been deployed fast despite of legal, business and technology problems in many countries. One important problem in deploying the smart grid system is to protect private smart meter readings from the unbelievable parties while the major smart meter functions are untouched. Privacy-preserving involves some challenges such as hardware limitations, secure cryptographic schemes and secure signal processing. In this paper, we focused particularly on the smart meter reading aggregation,which is the major research field in the smart meter privacy-preserving. We suggest a noisy weighted aggregation scheme to guarantee differential privacy. The noisy weighted values are generated in such a way that their product is one and are used for making the veiled measurements. In case that a Diffie-Hellman generator is applied to obtain the noisy weighted values, the noisy values are transformed in such a way that their sum is zero. The advantage of Diffie and Hellman group is usually to use 512 bits. Thus, compared to Paillier cryptosystem series which relies on very large key sizes, a significant performance can be obtained.