• Title/Summary/Keyword: 공격 모델

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Identifying Security Requirement using Reusable State Transition Diagram at Security Threat Location (보안 위협위치에서 재사용 가능한 상태전이도를 이용한 보안요구사항 식별)

  • Seo Seong-Chae;You Jin-Ho;Kim Young-Dae;Kim Byung-Ki
    • The KIPS Transactions:PartD
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    • v.13D no.1 s.104
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    • pp.67-74
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    • 2006
  • The security requirements identification in the software development has received some attention recently. However, previous methods do not provide clear method and process of security requirements identification. We propose a process that software developers can build application specific security requirements from state transition diagrams at the security threat location. The proposed process consists of building model and identifying application specific security requirements. The state transition diagram is constructed through subprocesses i) the identification of security threat locations using security failure data based on the point that attackers exploit software vulnerabilities and attack system assets, ii) the construction of a state transition diagram which is usable to protect, mitigate, and remove vulnerabilities of security threat locations. The identification Process of application specific security requirements consist of i) the analysis of the functional requirements of the software, which are decomposed into a DFD(Data Flow Diagram; the identification of the security threat location; and the appliance of the corresponding state transition diagram into the security threat locations, ii) the construction of the application specific state transition diagram, iii) the construction of security requirements based on the rule of the identification of security requirements. The proposed method is helpful to identify the security requirements easily at an early phase of software development.

Model Verification of a Safe Security Authentication Protocol Applicable to RFID System (RFID 시스템에 적용시 안전한 보안인증 프로토콜의 모델검증)

  • Bae, WooSik;Jung, SukYong;Han, KunHee
    • Journal of Digital Convergence
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    • v.11 no.4
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    • pp.221-227
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    • 2013
  • RFID is an automatic identification technology that can control a range of information via IC chips and radio communication. Also known as electronic tags, smart tags or electronic labels, RFID technology enables embedding the overall process from production to sales in an ultra-small IC chip and tracking down such information using radio frequencies. Currently, RFID-based application and development is in progress in such fields as health care, national defense, logistics and security. RFID structure consists of a reader that reads tag information, a tag that provides information and the database that manages data. Yet, the wireless section between the reader and the tag is vulnerable to security issues. To sort out the vulnerability, studies on security protocols have been conducted actively. However, due to difficulties in implementation, most suggestions are concerned with theorem proving, which is prone to vulnerability found by other investigators later on, ending up in many troubles with applicability in practice. To experimentally test the security of the protocol proposed here, the formal verification tool, CasperFDR was used. To sum up, the proposed protocol was found to be secure against diverse attacks. That is, the proposed protocol meets the safety standard against new types of attacks and ensures security when applied to real tags in the future.

Power Shift and Media Empowerment (언론의 정치권력화 - 재벌 정책 보도의 정권별 비교 연구)

  • Kim, Dong-Yule
    • Korean journal of communication and information
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    • v.45
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    • pp.296-340
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    • 2009
  • The power of media has always been problematic in the countries of full press freedom. Originally, the media used to be an effective vehicle for communication within human beings. However, it exerts an overwhelming power toward human society. Through applying the well-known four dog models in terms of media function, this study attempts to examine how the press media in South Korea transformed themselves into another powerful independent organization or institution after regime shift in 1987. The whole editorials of four sampled newspapers were analyzed through frame analysis model. The ChosunIlbo, known as a conservative and pro-government paper, shows to take the role of supporting chaebol policies under Roh TaeWoo Administration. However, it criticizing sharply against the chaebol policies of Roh MooHyun Administration. The JoongangIlbo, known as a pro-chaebol paper, appears anti-government position through the entire four administrations in terms of chaebol policies. Particularly, it reveals hostile editorial coverage during the Roh MooHyun Administration. However, KyunghyangShinmun, currently known as a liberal paper, viewed somewhat complicated positions (see text in more detail) because of its ownership turbulence during the past twenty years. On the other hand, Hangyoreh, regarded as a progressive paper, keeps in supportive attitude consistently against the four sampled administrations as far as regulating each government policies for chaebols.

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Protective Effects on Gastric Lesion of Ursolic acid (Ursolic acid의 위 손상에 대한 방어 효과)

  • Kim, Sun Whoe;Hwang, In Young;Lee, Sun Yi;Jeong, Choon Sik
    • Journal of Food Hygiene and Safety
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    • v.31 no.4
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    • pp.286-293
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    • 2016
  • This study is an experiment for gastric protective effects of ursolic acid. In order to identify the effects of ursolic acid on gastrointestinal disorder, acute and chronic gastritis were also observed using HCl ethanol and indomethacin-induced gastric lesion models, respectively. As for gastric acid, it was also identified through proton pump ($H^+/K^+-ATPase$) inhibiting activity. In regards to protective factor for gastric damage, prostaglandin $E_2$ ($PGE_2$) was quantitatively analyzed. Antibacterial activity experiment was done on Helicobacter pylori (H.pylori), which is known to be the causing factor of chronic gastritis, gastric ulcer and gastric cancer. By making use of AGS cell, it was confirmed that ursolic acid was involved in apoptosis of gastric cancer cell through 4',6-diamidino-2-phenylindol (DAPI) staining and flow cytometry analysis. As a result, ursolic acid reduced gastric lesions caused by HCl ethanol and indomethacin. Ursolic acid inhibited acid secretion by inhibiting proton pump ($H^+/K^+-ATPase$), which is the gastric acid secreting enzyme involved at the final phase of gastric acid secretion. And ursolic acid was identified with gastric mucosa protection effects by increasing the concentration of $PGE_2$, a protective factor of gastric mucosa preservation. The antibacterial activity on H. pylori, which is aggressive factor in gastrointestinal disorder, ursolic acid showed inhibitory effects on H. pylori colonization. In the DAPI nuclear staining, unlike the control group, shape of the nucleus has deformed, and has been observed either shrinked cell or chromatin condensation phenomenon. In the Flow cytometry assay, confirmed the growth rate of apoptosis in a concentration-dependent manner.

Rare Malware Classification Using Memory Augmented Neural Networks (메모리 추가 신경망을 이용한 희소 악성코드 분류)

  • Kang, Min Chul;Kim, Huy Kang
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.4
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    • pp.847-857
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    • 2018
  • As the number of malicious code increases steeply, cyber attack victims targeting corporations, public institutions, financial institutions, hospitals are also increasing. Accordingly, academia and security industry are conducting various researches on malicious code detection. In recent years, there have been a lot of researches using machine learning techniques including deep learning. In the case of research using Convolutional Neural Network, ResNet, etc. for classification of malicious code, it can be confirmed that the performance improvement is higher than the existing classification method. However, one of the characteristics of the target attack is that it is custom malicious code that makes it operate only for a specific company, so it is not a form spreading widely to a large number of users. Since there are not many malicious codes of this kind, it is difficult to apply the previously studied machine learning or deep learning techniques. In this paper, we propose a method to classify malicious codes when the amount of samples is insufficient such as targeting type malicious code. As a result of the study, we confirmed that the accuracy of 97% can be achieved even with a small amount of data by applying the Memory Augmented Neural Networks model.

A Study on security characteristics and vulnerabilities of BAS(Building Automation System) (BAS의 보안 특성 및 취약점에 관한 연구)

  • Choi, Yeon-Suk
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.4
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    • pp.669-676
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    • 2017
  • Recently, due to the importance of information security, security vulnerability analysis and various information protection technologies and security systems are being introduced as a countermeasure against cyber-attacks in new as well as existing buildings, and information security studies on high-rise buildings are also being conducted. However, security system introduction and research are generally performed from the viewpoint of general IT systems and security policies, so there is little consideration of the infrastructure of the building. In particular, the BAS or building infrastructure, is a closed system, unlike typical IT systems, but has unique structural features that accommodate open functions. Insufficient understanding of these system structures and functions when establishing a building security policy makes the information security policies for the BAS vulnerable and increases the likelihood that all of the components of the building will be exposed to malicious cyber-attacks via the BAS. In this paper, we propose an architecture reference model that integrates three different levels of BAS structure (from?) different vendors. The architectures derived from this study and the security characteristics and vulnerabilities at each level will contribute to the establishment of security policies that reflect the characteristics of the BAS and the improvement of the safety management of buildings.

A Study on the Detection Model of Illegal Access to Large-scale Service Networks using Netflow (Netflow를 활용한 대규모 서비스망 불법 접속 추적 모델 연구)

  • Lee, Taek-Hyun;Park, WonHyung;Kook, Kwang-Ho
    • Convergence Security Journal
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    • v.21 no.2
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    • pp.11-18
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    • 2021
  • To protect tangible and intangible assets, most of the companies are conducting information protection monitoring by using various security equipment in the IT service network. As the security equipment that needs to be protected increases in the process of upgrading and expanding the service network, it is difficult to monitor the possible exposure to the attack for the entire service network. As a countermeasure to this, various studies have been conducted to detect external attacks and illegal communication of equipment, but studies on effective monitoring of the open service ports and construction of illegal communication monitoring system for large-scale service networks are insufficient. In this study, we propose a framework that can monitor information leakage and illegal communication attempts in a wide range of service networks without large-scale investment by analyzing 'Netflow statistical information' of backbone network equipment, which is the gateway to the entire data flow of the IT service network. By using machine learning algorithms to the Netfllow data, we could obtain the high classification accuracy of 94% in identifying whether the Telnet service port of operating equipment is open or not, and we could track the illegal communication of the damaged equipment by using the illegal communication history of the damaged equipment.

An Interpretable Log Anomaly System Using Bayesian Probability and Closed Sequence Pattern Mining (베이지안 확률 및 폐쇄 순차패턴 마이닝 방식을 이용한 설명가능한 로그 이상탐지 시스템)

  • Yun, Jiyoung;Shin, Gun-Yoon;Kim, Dong-Wook;Kim, Sang-Soo;Han, Myung-Mook
    • Journal of Internet Computing and Services
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    • v.22 no.2
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    • pp.77-87
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    • 2021
  • With the development of the Internet and personal computers, various and complex attacks begin to emerge. As the attacks become more complex, signature-based detection become difficult. It leads to the research on behavior-based log anomaly detection. Recent work utilizes deep learning to learn the order and it shows good performance. Despite its good performance, it does not provide any explanation for prediction. The lack of explanation can occur difficulty of finding contamination of data or the vulnerability of the model itself. As a result, the users lose their reliability of the model. To address this problem, this work proposes an explainable log anomaly detection system. In this study, log parsing is the first to proceed. Afterward, sequential rules are extracted by Bayesian posterior probability. As a result, the "If condition then results, post-probability" type rule set is extracted. If the sample is matched to the ruleset, it is normal, otherwise, it is an anomaly. We utilize HDFS datasets for the experiment, resulting in F1score 92.7% in test dataset.

Extraction and Taxonomy of Ransomware Features for Proactive Detection and Prevention (사전 탐지와 예방을 위한 랜섬웨어 특성 추출 및 분류)

  • Yoon-Cheol Hwang
    • Journal of Industrial Convergence
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    • v.21 no.9
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    • pp.41-48
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    • 2023
  • Recently, there has been a sharp increase in the damages caused by ransomware across various sectors of society, including individuals, businesses, and nations. Ransomware is a malicious software that infiltrates user computer systems, encrypts important files, and demands a ransom in exchange for restoring access to the files. Due to its diverse and sophisticated attack techniques, ransomware is more challenging to detect than other types of malware, and its impact is significant. Therefore, there is a critical need for accurate detection and mitigation methods. To achieve precise ransomware detection, an inference engine of a detection system must possess knowledge of ransomware features. In this paper, we propose a model to extract and classify the characteristics of ransomware for accurate detection of ransomware, calculate the similarity of the extracted characteristics, reduce the dimension of the characteristics, group the reduced characteristics, and classify the characteristics of ransomware into attack tools, inflow paths, installation files, command and control, executable files, acquisition rights, circumvention techniques, collected information, leakage techniques, and state changes of the target system. The classified characteristics were applied to the existing ransomware to prove the validity of the classification, and later, if the inference engine learned using this classification technique is installed in the detection system, most of the newly emerging and variant ransomware can be detected.

A Categorization Method based on RCBAC for Enhanced Contents and Social Networking Service for User (사용자를 위한 향상된 콘텐츠 및 소셜 네트워킹 서비스 제공을 위한 RCBAC 기반 분류 방법)

  • Cho, Eun-Ae;Moon, Chang-Joo;Park, Dae-Ha
    • Journal of Digital Contents Society
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    • v.13 no.1
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    • pp.101-110
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    • 2012
  • Recently, social network sites are very popular with the enhancement of mobile device function and distribution. This gives rise to the registrations of the people on the social network sites and the usage of services on the social sites is also getting active. However, social network sites' venders do not provide services enough compared to the demand of users' to share contents from diverse roots by users effectively. In addition, the personal information can be revealed improperly in processes sharing policies and it is obvious that it raises a privacy invasion problem when users access the contents created from diverse devices according to the relationship by policies. However, the existing methods for the integration management of social network are weak to solve this problem. Thus, we propose a model to preserve user privacy, categorize contents efficiently, and give the access control permissions at the same time. In this paper, we encrypt policies and the trusted third party classifies the encrypted policies when the social network sites share the generated contents by users. In addition, the proposed model uses the RCBAC model to manage the contents generated by various devices and measures the similarity between relationships after encrypting when the user policies are shared. So, this paper can contribute to preserve user policies and contents from malicious attackers.