• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.24-32
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• 2021

Recently, ransomware attacks have been infected through various channels such as e-mail, phishing, and device hacking, and the extent of the damage is increasing rapidly. However, existing known malware (static/dynamic) analysis engines are very difficult to detect/block against novel ransomware that has evolved like Advanced Persistent Threat (APT) attacks. This work proposes a method for modeling ransomware malicious behavior based on graph databases and detecting novel multi-complex malicious behavior for ransomware. Studies confirm that pattern detection of ransomware is possible in novel graph database environments that differ from existing relational databases. Furthermore, we prove that the associative analysis technique of graph theory is significantly efficient for ransomware analysis performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.203-205
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• 2022

As digital transformation and remote work environment advanced by Covid-19 become more common, the scale of leakage damage to industrial secrets and personal information caused by information leakage attacks is increasing. Recently, advanced and persistent information leakage attacks have become a serious security threat because they do not quickly leak large amounts of information, but continuously leak small amounts of information over a long period of time. In this study, we propose a framework for detecting advanced and persistent information leakage attacks based on traffic characteristics. The proposed method can effectively detect advanced and persistent information leakage attacks using traffic patterns, packet sizes, and metadata, even if the payload is encrypted.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.217-218
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• 2023

내부자 위협이란, 조직의 보안 및 데이터, 시스템에 대한 내부 정보에 접근하는 현 임직원 및 전 임직원, 계약자와 같이, 동일한 조직 내부의 사람들로부터 발생하는 위협을 의미한다. 일반적으로 내부자들은 업무를 위하여, 시스템에 대한 합법적인 접근 권한을 가지며, 만약 이러한 권한이 오남용되는 경우에는 조직에 매우 심각한 피해를 입힐 수 있다. 이러한 내부자 위협은 외부로부터의 위협보다 방어 및 탐지가 훨씬 어려운 한계점이 있으며, 그 피해 규모가 매우 방대하다는 문제점도 존재한다. 이에 따라, 본 논문에서는 내부자 위협을 탐지하기 위하여, 이메일을 통한 기밀정보를 유출하는 유형의 위협에 대응하는 방안을 제안한다. 제안하는 방안은 조직 내에서 이메일을 발신하는 경우를 대상으로, 파일이 포함된 이메일에 발신자를 식별하기 위하여, 파일에 키 값 및 서명을 삽입하며, 발신되는 이메일을 모니터링하여 첨부된 파일의 유형을 파악함으로써, 동적 그래프를 통하여 시각화한다. 내부 시스템 및 네트워크에서의 보안관제 담당자 및 관리자는 시각화된 그래프를 확인함으로써, 직관적으로 정보 유출을 파악하고 대응할 수 있을 것으로 판단된다. 본 논문에서 제안하는 방안을 통하여, 조직 내의 내부자 위협을 탐지할 수 있으며, 데이터 유출 사고가 발생하는 경우, 유출자를 빠르게 식별하고 초기에 대응할 수 있을 것으로 판단된다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1141-1151
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• 2018

In an APT attack, the communication stage between infected hosts and C&C(Command and Control) server is the key stage for intrusion into the attack target. Attackers can control multiple infected hosts by the C&C Server and direct intrusion and exploitation. If the C&C Server is exposed at this stage, the attack will fail. Therefore, in recent years, the Domain Generation Algorithm (DGA) has replaced DNS in C&C Server with a short time interval for making detection difficult. In particular, it is very difficult to verify and detect all the newly registered DNS more than 5 million times a day. To solve these problems, this paper proposes a model to judge DGA-DNS detection by the morphological similarity analysis of normal DNS and DGA-DNS, and to determine the sign of APT attack through it, then we verify its validity.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.2
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• pp.411-421
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• 2015

These days, a conversion of the fast-advancing ICT (Information and Communications Technologies) and the IoT (Internet of Things) has been in progress. However, these conversion Technology could lead to many of the security threat existing in the ICT environment. The security threats of car in the IoT environment could cause the property damage and casualty. There are the inadequate preparations for the car security and the difficulty of detection for the security threats by itself. In this paper, we proposed the decision-making framework for the anomaly detection and found out what are the threats of car in the IoT environment. The discrimination of the factor, path and type of threats from the attack against the car should take priority over the self-inspection and the swift handling of the attack on control system.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.153-169
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• 2018

Previous e-financial anomalies analysis and detection technology collects large amounts of electronic financial transaction logs generated from electronic financial business systems into big-data-based storage space. And it detects abnormal transactions in real time using detection rules that analyze transaction pattern profiling of existing customers and various accident transactions. However, deep analysis such as attempts to access e-finance by insiders of financial institutions with large scale of damages and social ripple effects and stealing important information from e-financial users through bypass of internal control environments is not conducted. This paper analyzes the management status of e-financial security programs of financial companies and draws the possibility that they are allies in security control of insiders who exploit vulnerability in management. In order to efficiently respond to this problem, it will present a comprehensive e-financial security management environment linked to insider threat monitoring as well as the existing e-financial transaction detection system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.61-68
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• 2021

In the past, radars have been classified into fire control radars, detection radars, tracking radars, and image acquisition radars according to the characteristics of the mission. However, multi-function radars perform various tasks within a single system, such as target detection, tracking, identification friend or foe, jammer detection and response. Therefore, efficient resource management is essential to operate multi-function radars with limited resources. In particular, the target threat for tracking the detected target and the method of selecting the tracking cycle based on this is an important issue. If focus on tracking a threat target, Radar can't efficiently manage the targets detected in other areas, and if you focus on detection, tracking performance may decrease. Therefore, effective scheduling is essential. In this paper, we propose the TaP (Time and Priority) algorithm, which is a multi-functional radar scheduling scheme, and a software design method to construct it.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.449-451
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• 2021

Cyber-attacks targeting endpoints have developed sophisticatedly into targeted and intelligent attacks, Advanced Persistent Threat (APT) targeting the Industrial Internet of Things (IIoT) has increased accordingly. Machine learning-based Endpoint Detection and Response (EDR) solutions combine and complement rule-based conventional security tools to effectively defend against APT attacks are gaining attention. However, universal EDR solutions have a high false positive rate, and needs high-level analysts to monitor and analyze a tremendous amount of alerts. Therefore, the process of optimizing machine learning-based EDR solutions that consider the characteristics and vulnerabilities of IIoT environment is essential. In this study, we analyze the flow and impact of IIoT targeted APT cases and compare the method of machine learning-based APT detection EDR solutions.

• Information Systems Review
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• v.9 no.1
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• pp.121-137
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• 2007

Several security systems(firewall, intrusion detection system, vaccine for malicious codes and so on), whose purposes are to prevent the external information security threat, have gathered more technological concerns. However, they are little effective for the area of defending the internal information security threat which occurs more frequently and results in much more monetary damages. In this paper, a system for internal surveillance and control on the use of information systems is suggested and described with its architecture, features, necessary functions and development methods. And a case system is introduced to show the reality of this paper.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.3
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• pp.491-498
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• 2014

Recently, cyber terror has been occurred frequently based on advanced persistent threat(APT) and it is very difficult to detect these attacks because of new malwares which cannot be detected by anti-virus softwares. This paper proposes and verifies the algorithms to detect the advanced persistent threat previously through real-time network monitoring and combinatorial analysis of big data log. In the future, APT attacks can be detected more easily by enhancing these algorithms and adapting big data platform.