• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.2
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• pp.385-395
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• 2018

With the development of Internet, cyber attack has become a major threat. To detect cyber attacks, intrusion detection system(IDS) has been widely deployed. But IDS has a critical weakness which is that it generates a large number of false alarms. One of the promising techniques that reduce the false alarms in real time is machine learning. However, there are problems that must be solved to use machine learning. So, many machine learning approaches have been applied to this field. But so far, researchers have not focused on features. Despite the features of IDS alerts are important for performance of model, the approach to feature is ignored. In this paper, we propose new feature set which can improve the performance of model and can be extracted from a single alarm. New features are motivated from security analyst's know-how. We trained and tested the proposed model applied new feature set with real IDS alerts. Experimental results indicate the proposed model can achieve better accuracy and false positive rate than SVM model with ordinary features.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1503-1514
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• 2015

Non-face-to-face real name verification policy that financial authorities announced, in order to secure a face-to-face or more of accuracy, are in principle of multi check. The business model and legal entities of Internet banks is different from existing Internet banking. Relpacing real name verification from face-to-facd to non-face-to-face while maintaining the structure of identification can not only cause inconvenience to a first time member, but also can be more vulnerable to verious security risks. In this study, to evaluate a service level of a bank of the Internet, and provide an improved identification of the structure such that the registration and use of differentiated services is performed in accordance with the evaluation. In addition, the security that may occur with respect to Bank of the Internet to establish a vulnerability and attack model, the results of the analysis of the safety of the step-by-step security attributes and services of the authentication medium of each attack model, existing the safer than Internet banking, confirmed the usefulness in user registration guide.

• The KIPS Transactions:PartC
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• v.8C no.5
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• pp.607-614
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• 2001

With a remarkable growth and expansion of Internet, the security issues emerged from intrusions and attacks such as computer viruses, denial of services and hackings to destroy information have been considered as serious threats for Internet and the private networks. To protect networks from those attacks, many vendors have developed various security systems such as firewalls, intrusion detection systems, and access control systems. However, managing those systems individually requires too much work and high cost. Thus, in order to manage integrated security management and establish consistent security management for various security products, the policy model of PN-ISMS (Policy Based Integrated Security Management System) has become very important. In this paper, present the hierarchical policy model which explore the refinement of high-level/conceptual policies into a number of more specific policies to form a policy hierarchy. A formal method of policy description was used as the basis of the mode in order to achieve precision and generality. Z-Notation was chosen for this propose. The Z-Notation is mathematical notation for expressing and communicating the specifications of computer programs. Z uses conventional notations of logic and set theory organized into expressions called schemas.

• 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 Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.437-444
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• 2008

This paper deals with the biometric template protection in the biometric system which has been widely used for personal authentication. First, we consider the structure of the biometric system and the function of its sub-systems and define the biometric template and identification(ID) information. And then, we describe the biometric template attack points of a biometric system and attack examples and provide their countermeasures. From this, we classify the vulnerability which can be protected by encryption and hashing techniques. For more detail investigation of these at real operating situations, we analyze them and suggest several protection methods for the typical application scheme of biometric systems such as local model, download model, attached model, and center model. Finally, we also handle the privacy problem which is most controversy issue related to the biometric systems and suggest some guidances of safeguarding procedures on establishing privacy sympathy biometric systems.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.5
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• pp.1153-1165
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• 2019

Recently, threats of hacking have been increasing on the national intelligence service network and key infrastructure, including the defense field. The defense information system responds to threats from the outside through the network separation, but if the defense information system is hacked, it has a serious impact on the operations of wartime or peacetime military forces. Today, cyberattacks and threats are rising to unpredictable levels and making it practically impossible to completely block and prevent hacking threats completly. So, in this study proposed a maturity model to assess the level of cyber-resilience, which is the ability to ensure the system's viability and maintain continuity through rapid response and recovery if signs of cyberattacks by the defense information system are expected or occurred. The proposed maturity model is expected to contribute to improving the cyber security level of the defense information system by assessing the level of cyber resilience of the defense information system and identifying and supplementing fields that are lacking.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.175-185
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• 2019

The security control is to protect IT system from cyber infringement by deriving valid result values in the process of gathering and analyzing various information. Currently, security control is very effective by using SIEM equipment which enables analysis of systematic and comprehensive viewpoint based on a lot of data, away from analyzing cyber threat information with only fragmentary information. However, It can also be said that cyber attacks are analyzed and coped with the manual work of security personnel. This means that even if there is excellent security equipment, the results will vary depending on the user using. In case of operating a characteristic web service including information provision, This study suggests the basic point of security control through characteristics information analysis, and proposes a model for intensive security control through the type discovery and application which enable a step-wise analysis and an effective filtering. Using this model would effectively detect, analyze and block attacks.

• The Journal of Korean Institute of Information Technology
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• v.17 no.12
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• pp.125-134
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• 2019

As the limitations of the passive recognition domain, which is not guaranteed transparency of the operation process, AI technology has a vulnerability that depends on the data. Human error is inherent because raw data for artificial intelligence learning must be processed and inspected manually to secure data quality for the advancement of AI learning. In this study, we examine the necessity of learning data management before machine learning by analyzing inaccurate cases of AI learning data and cyber security attack method through the approach from cyber security perspective. In order to verify the learning data integrity, this paper presents the direction of data-preserving artificial intelligence system, a blockchain-based learning data environment model. The proposed method is expected to prevent the threats such as cyber attack and data corruption in providing and using data in the open network for data processing and raw data collection.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.97-105
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• 2022

This paper explains trends in security technologies for ICS. Since ICS is usually applied to large-scale national main infrastructures and industry fields, minor errors caused by cyberattack could generate enormous economic cost. ICS has different characteristic with commonly used IT systems, so considering security threats of ICS separately with IT is needed for developing modern security technology. This paper introduce framework for ICS that analyzes recent cyberattack tactics & techniques and find out trends in Intrusion Detection System (IDS) which is representative technology for ICS security, and analyzes AI technologies used for IDS. Specifically, this paper explains data collection and analysis for applying AI techniques, AI models, techniques for evaluating AI Model.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.1
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• pp.71-82
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• 2024

With the advancement of information and communication technology (ICT), the use of electronic document types such as PDF, MS Office, and HWP files has increased. Such trend has led the cyber attackers increasingly try to spread malicious documents through e-mails and messengers. To counter such attacks, AI-based methodologies have been actively employed in order to detect malicious document files. The main challenge in detecting malicious HWP(Hangul Word Processor) files is the lack of quality dataset due to its usage is limited in Korea, compared to PDF and MS-Office files that are highly being utilized worldwide. To address this limitation, data augmentation have been proposed to diversify training data by transforming existing dataset, but as the usefulness of the augmented data is not evaluated, augmented data could end up harming model's performance. In this paper, we propose an effective semi-supervised learning technique in detecting malicious HWP document files, which improves overall AI model performance via quantifying the utility of augmented data and filtering out useless training data.