• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.49-57
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• 2010

We extended a general attack tree to apply cyber attack model for network vulnerability analysis. We defined an extended cyber attack tree (E-CAT) which extends the general attack tree by associating each node of the tree with a transition of attack that could have contributed to the cyber attack. The E-CAT resolved the limitation that a general attack tree can not express complex and sophisticate attacks. Firstly, the Boolean expression can simply express attack scenario with symbols and codes. Secondary, An Attack Generation Probability is used to select attack method in an attack tree. A CONDITION-composition can express new and modified attack transition which a aeneral attack tree can not express. The E-CAT is possible to have attack's flexibility and improve attack success rate when it is applied to cyber attack model.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.185-188
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• 2002

This paper proposes a efficient way to use Database that is constructed about attack-pattern. For IDS that activate confrontation, we reconstruct by Layered Attack Tree after constructing attack pattern by Attack Tree. And then this paper has designed IDS that Layered Attack Tree is applied, verified them.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.3
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• pp.67-74
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• 2011

In this paper, we presented a dynamic cyber attack tree which can describe an attack scenario flexibly for an active cyber attack model could be detected complex and transformed attack method. An attack tree provides a formal and methodical route of describing the security safeguard on varying attacks against network system. The existent attack tree can describe attack scenario as using vertex, edge and composition. But an attack tree has the limitations to express complex and new attack due to the restriction of attack tree's attributes. We solved the limitations of the existent attack tree as adding an threat occurrence probability and 2 components of composition in the attributes. Firstly, we improved the flexibility to describe complex and transformed attack method, and reduced the ambiguity of attack sequence, as reinforcing composition. And we can identify the risk level of attack at each attack phase from child node to parent node as adding an threat occurrence probability.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.56-62
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• 2021

The surge in generic attacks execution against cipher text on the computer network has led to the continuous advancement of the mechanisms to protect information integrity and confidentiality. The implementation of explicit decision tree machine learning algorithm is reported to accurately classifier generic attacks better than some multi-classification algorithms as the multi-classification method suffers from detection oversight. However, there is a need to improve the accuracy and reduce the false alarm rate. Therefore, this study aims to improve generic attack classification by implementing two hybridized decision tree algorithms namely Naïve Bayes Decision tree (NBTree) and Logistic Model tree (LMT). The proposed hybridized methods were developed using the 10-fold cross-validation technique to avoid overfitting. The generic attack detector produced a 99.8% accuracy, an FPR score of 0.002 and an MCC score of 0.995. The performances of the proposed methods were better than the existing decision tree method. Similarly, the proposed method outperformed multi-classification methods for detecting generic attacks. Hence, it is recommended to implement hybridized decision tree method for detecting generic attacks on a computer network.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.2
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• pp.259-266
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• 2017

In modern society, IT technology based systems are introduced and operated in various fields such as home, industry, and finance. To ensure the safety of society, IT systems introduced throughout society should be protected from cyber attacks. Understanding and checking the current security status of the system is one of the important tasks to response effectively against cyber attacks. In this paper, we analyze limitations of Game Theory and Attack Tree methodologies used to inspect for security vulnerabilities. Based on this, we propose a security vulnerability quantification method that complements the limitations of both methodologies. This provides a more objective and systematic way to inspect for security weaknesses.

• Convergence Security Journal
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• v.21 no.1
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• pp.93-100
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• 2021

Damage caused by intelligent cyber attacks not only disrupts system operations and leaks information, but also entails massive economic damage. Recently, cyber attacks have a distinct goal and use advanced attack tools and techniques to accurately infiltrate the target. In order to minimize the damage caused by such an intelligent cyber attack, it is necessary to block the cyber attack at the beginning or during the attack to prevent it from invading the target's core system. Recently, technologies for predicting cyber attack paths and analyzing risk level of cyber attack using big data or artificial intelligence technologies are being studied. In this paper, a cyber attack path analysis method using attack tree and RFI is proposed as a basic algorithm for the development of an automated cyber attack path prediction system. The attack path is visualized using the attack tree, and the priority of the path that can move to the next step is determined using the RFI technique in each attack step. Based on the proposed mechanism, it can contribute to the development of an automated cyber attack path prediction system using big data and deep learning technology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2196-2218
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• 2017

Multicast communication has been widely used in the Internet. However, multicast communication is vulnerable to DoS attack due to static router configuration. In this paper, HMC, a hopping multicast communication method based on SDN, is proposed to tackle this problem. HMC changes the multicast tree periodically and makes it difficult for the attackers to launch an accurate attack. It also decreases the probability of multicast communication being attacked by DoS and in the meanwhile, the QoS constrains are not violated. In this research, the routing problem of HMC is proven to be NP-complete and a heuristic algorithm is proposed to solve it. Experiments show that HMC has the ability to resist DoS attack on multicast route effectively. Theoretically, the multicast compromised probability can drop more than 0.6 when HMC is adopt. In addition, experiments demonstrate that HMC achieves shorter average multicast delay and better robustness compared with traditional method, and more importantly, it better defends DoS attack.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.79-85
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• 2022

Anomaly detection is a method to detect and block abnormal data flows in general users' data sets. The previously known method is a method of detecting and defending an attack based on a signature using the signature of an already known attack. This has the advantage of a low false positive rate, but the problem is that it is very vulnerable to a zero-day vulnerability attack or a modified attack. However, in the case of anomaly detection, there is a disadvantage that the false positive rate is high, but it has the advantage of being able to identify, detect, and block zero-day vulnerability attacks or modified attacks, so related studies are being actively conducted. In this study, we want to deal with these anomaly detection mechanisms, and we propose a new mechanism that performs both anomaly detection and classification while supplementing the high false positive rate mentioned above. In this study, the experiment was conducted with five configurations considering the characteristics of various algorithms. As a result, the model showing the best accuracy was proposed as the result of this study. After detecting an attack by applying the Extra Tree and Three-layer ANN at the same time, the attack type is classified using the Extra Tree for the classified attack data. In this study, verification was performed on the NSL-KDD data set, and the accuracy was 99.8%, 99.1%, 98.9%, 98.7%, and 97.9% for Normal, Dos, Probe, U2R, and R2L, respectively. This configuration showed superior performance compared to other models.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.339-342
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• 2016

스마트그리드는 기존 전력망의 비효율적인 운영, 이산화탄소 과다 배출, 전력피크의 문제를 해결하기 위한 방법으로 주목받고 있다. 하지만, 기존의 ICT가 도입되고 구조가 복잡해짐에 따라 개인정보를 침해 할 수 있는 가능성이 증가하게 되었다. 본 논문에서는 스마트그리드 내에서 개인정보를 다루는 기기, 시스템, 데이터와 같은 자산을 식별하여 공격자 입장에서의 공격 목표를 설정한 뒤, Attack Tree 방법을 통하여 세부적인 위협을 식별하였다. 분석 결과, 스마트그리드 환경은 기존의 ICT 기술이 접목되기 때문에 스마트그리드 구조상 발생할 수 있는 위협뿐 만 아니라 기존의 기술들에서 발생할 수 있는 위협도 함께 존재했다.

• Convergence Security Journal
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• v.11 no.6
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• pp.25-30
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• 2011

MANET has a weak construction in security more because it is consisted of only moving nodes and doesn't have central management system. The DDoS attack is a serious attack among these attacks which threaten wireless network. The DDoS attack has various object and trick and become intelligent. In this paper, we propose the technique to raise DDoS detection rate by classifying abnormal traffic pattern. Cluster head performs sentinel agent after nodes which compose MANET are made into cluster. The decision tree is applied to detect abnormal traffic pattern after the sentinel agent collects all traffics and it judges traffic pattern and detects attack also. We confirm high attack detection rate of proposed detection technique in this study through experimentation.