• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.260-280
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• 2020

Cyber-attacks emerge in a more intelligent way, and various security technologies are applied to respond to such attacks. Still, more and more people agree that individual response to each intelligent infringement attack has a fundamental limit. Accordingly, the cyber threat intelligence analysis technology is drawing attention in analyzing the attacker group, interpreting the attack trend, and obtaining decision making information by collecting a large quantity of cyber-attack information and performing relation analysis. In this study, we proposed relation analysis factors and developed a system for establishing cyber threat intelligence, based on malicious code as a key means of cyber-attacks. As a result of collecting more than 36 million kinds of infringement information and conducting relation analysis, various implications that cannot be obtained by simple searches were derived. We expect actionable intelligence to be established in the true sense of the word if relation analysis logic is developed later.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.1-13
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• 2022

As the information and communication environment develops, the environment of military facilities is also development remarkably. In proportion to this, cyber threats are also increasing, and in particular, APT attacks, which are difficult to prevent with existing signature-based cyber defense systems, are frequently targeting military and national infrastructure. It is important to identify attack groups for appropriate response, but it is very difficult to identify them due to the nature of cyber attacks conducted in secret using methods such as anti-forensics. In the past, after an attack was detected, a security expert had to perform high-level analysis for a long time based on the large amount of evidence collected to get a clue about the attack group. To solve this problem, in this paper, we proposed an automation technique that can classify an attack group within a short time after detection. In case of APT attacks, compared to general cyber attacks, the number of attacks is small, there is not much known data, and it is designed to bypass signature-based cyber defense techniques. As an attack model, we used MITRE ATT&CK® which modeled many parts of cyber attacks. We design an impact score considering the versatility of the attack techniques and proposed a group similarity score based on this. Experimental results show that the proposed method classified the attack group with a 72.62% probability based on Top-5 accuracy.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.165-171
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• 2018

The most threatening attack that has become a hot topic of recent IT security is APT Attack.. So far, there is no way to respond to APT attacks except by using artificial intelligence techniques. Here, we have implemented a machine learning algorithm for analyzing cyber threat data using machine learning method, using a data set that collects cyber attack cases using Scikit Learn, a big data machine learning framework. The result showed an attack classification accuracy close to 70%. This result can be developed into the algorithm of the security control system in the future.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.91-97
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• 2020

Recently, phishing attacks targeting those involved in defense, security and unification have been on the rise. In particular, hacking attack organization Kimsuky has been engaged in activities to collect important information from public organizations through phishing attacks since 2013. In this paper, profiling analysis of phishing mail attack organization was performed. Through this process, we estimated the purpose of the attack group and suggested countermeasures.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.3
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• pp.417-430
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• 2024

As modern technology advances and the proliferation of the internet continues, cyber threats are also on the rise. To effectively counter these threats, the importance of utilizing Cyber Threat Intelligence (CTI) is becoming increasingly prominent. CTI provides information on new threats based on data from past cyber incidents, but the complexity of data and changing attack patterns present significant analytical challenges. To address these issues, this study aims to utilize graph data that can comprehensively represent multidimensional relationships. Specifically, the study constructs a heterogeneous graph based on malware data, and uses the metapath2vec node embedding technique to more effectively identify cyber attack groups. By analyzing the impact of incorporating topology information into traditional malware data, this research suggests new practical applications in the field of cyber security and contributes to overcoming the limitations of CTI analysis.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.3
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• pp.561-566
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• 2013

We propose an efficient exponentiation method which is resistant against some side channel attacks in $T_2(p)$, Torus-Based-Cryptosystem. It is more efficient than the general exponentiation method in $T_2(p)$ and is resistant against SPA by using that the difference of squaring and multiplication costs is negligible. Moreover, we can randomize a message in exponentiation step using the characteristic of quotient group which naturally protects against the first DPA.

• Convergence Security Journal
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• v.16 no.3_2
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• pp.33-42
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• 2016

While evolving information-oriented society provides a lot of benefits to the human life, new types of threats have been increasing. Particularly, cyber terrorism, happen on the network that is composed of a computer system and information communication network, and the mean and scale of damage has reached a serious level. In other words, it is hard to locate cyber terror since it occurs in the virtual space, not in the real world, so identifying "Who is attacking?" (Non-visibility, non-formulas), or "Where the attack takes place?" (trans-nation) are hard. Hackers, individuals or even a small group of people, who carried out the cyber terror are posing new threats that could intimidate national security and the pace and magnitude of threats keep evolving. Scale and capability of North Korea's cyber terrorism are assessed as world-class level. Recently, North Korea is focusing on strengthen their cyber terrorism force. So improving a response system for cyber terror is a key necessity as North Korea's has emerged as a direct threat to South Korean security. Therefore, Korea has to redeem both legal and institutional systems immediately to perform as a unified control tower for preemptive response to cyber terrors arise from North Korea and neighboring countries.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.392-394
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• 2014

요즘 인터넷을 통하여 많은 사이버 공격이 일어나고 있다. 이에 대응하기 위하여 우리는 네트워크 패킷을 저장할 수 있는 사이버 블랙박스 시스템을 개발하고 사이버 블랙박스 시스템에서 수집한 많은 네트워크 패킷을 분석할 수 있는 효율적인 공격 원인 분석 알고리즘을 제안한다. 공격원인 분석 알고리즘을 통하여 우리는 사이버 공격에 발생했을 때 공격의 유입점이 어디이고 어떤 경로를 통해서 공격이 이루어졌는지 알 수 있다. 그 뿐만 아니라 숨겨진 피해자 발견 알고리즘을 통하여 알려진 피해자뿐만 아니라 알려지지 않은 다른 피해자를 찾을 수 있다.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.15-26
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• 2022

Various subjects are carrying out cyberattacks using a variety of tactics and techniques. Additionally, cyberattacks for political and economic purposes are also being carried out by groups which is sponsored by its nation. To deal with cyberattacks, researchers used to classify the malware family and the subjects of the attack based on malware signature. Unfortunately, attackers can easily masquerade as other group. Also, as the attack varies with subject, techniques, and purpose, it is more effective for defenders to identify the attacker's purpose and goal to respond appropriately. The essential goal of cyberattacks is to threaten the information security of the target assets. Information security is achieved by preserving the confidentiality, integrity, and availability of the assets. In this paper, we relabel the attacker's goal based on MITRE ATT&CK® in the point of CIA triad as well as classifying cyber security reports to verify the labeling method. Experimental results show that the model classified the proposed CIA label with at most 80% probability.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.92-99
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• 2013

As a recent cyber attack has a characteristic that is intellectual, advanced, and complicated attack against precise purpose and specified object, it becomes extremely hard to recognize or respond when accidents happen. Since a scale of damage is very large, a corresponding system about this situation is urgent in national aspect. Existing data center or integration security framework of computer lab is evaluated to be a behind system when it corresponds to cyber attack. Therefore, this study suggests a better sophisticated next generation convergence security framework in order to prevent from attacks based on advanced persistent threat. Suggested next generation convergence security framework is designed to have preemptive responses possibly against APT attack consisting of five hierarchical steps in domain security layer, domain connection layer, action visibility layer, action control layer and convergence correspondence layer. In domain connection layer suggests security instruction and direction in domain of administration, physical and technical security. Domain security layer have consistency of status information among security domain. A visibility layer of Intellectual attack action consists of data gathering, comparison, decision, lifespan cycle. Action visibility layer is a layer to control visibility action. Lastly, convergence correspond layer suggests a corresponding system of before and after APT attack. An introduction of suggested next generation convergence security framework will execute a better improved security control about continuous, intellectual security threat.