• Title/Summary/Keyword: Indicators of Compromise(IOC)

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Automatic Creation of Forensic Indicators with Cuckoo Sandbox and Its Application (Cuckoo Sandbox를 이용한 포렌식 침해지표 자동생성 및 활용 방안)

  • Kang, Boong Gu;Yoon, Jong Seong;Lee, Min Wook;Lee, Sang Jin
    • KIPS Transactions on Computer and Communication Systems
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    • v.5 no.11
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    • pp.419-426
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    • 2016
  • As the threat of cyber incident grows continuously, the need of IOC(Indicators of Compromise) is increasing to identify the cause of incidents and share it for quick response to similar incidents. But only few companies use it domestically and the research about the application of IOC is deficient compared to foreign countries. Therefore in this paper, a quick and standardized way to create IOC automatically based on the analysis result of malwares from Cuckoo Sandbox and its application is suggested.

A Study on Hacking E-Mail Detection using Indicators of Compromise (침해지표를 활용한 해킹 이메일 탐지에 관한 연구)

  • Lee, Hoo-Ki
    • Convergence Security Journal
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    • v.20 no.3
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    • pp.21-28
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    • 2020
  • In recent years, hacking and malware techniques have evolved and become sophisticated and complex, and numerous cyber-attacks are constantly occurring in various fields. Among them, the most widely used route for compromise incidents such as information leakage and system destruction was found to be E-Mails. In particular, it is still difficult to detect and identify E-Mail APT attacks that employ zero-day vulnerabilities and social engineering hacking techniques by detecting signatures and conducting dynamic analysis only. Thus, there has been an increased demand for indicators of compromise (IOC) to identify the causes of malicious activities and quickly respond to similar compromise incidents by sharing the information. In this study, we propose a method of extracting various forensic artifacts required for detecting and investigating Hacking E-Mails, which account for large portion of damages in security incidents. To achieve this, we employed a digital forensic indicator method that was previously utilized to collect information of client-side incidents.

Digital Forensic Indicators of Compromise Format(DFIOC) and Its Application (디지털 포렌식 기반의 침해 지표 포맷 개발 및 활용 방안)

  • Lee, Min Wook;Yoon, Jong Seong;Lee, Sang Jin
    • KIPS Transactions on Computer and Communication Systems
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    • v.5 no.4
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    • pp.95-102
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    • 2016
  • Computer security incident such as confidential information leak and data destruction are constantly growing and it becomes threat to information in digital devices. To respond against the incident, digital forensic techniques are also developing to help digital incident investigation. With the development of digital forensic technology, a variety of forensic artifact has been developed to trace the behavior of users. Also, a diversity of forensic tool has been developed to extract information from forensic artifact. However, there is a issue that information from forensic tools has its own forms. To solve this problem, it needs to process data when it is output from forensic tools. Then it needs to compare and analyze processed data to identify how data is related each other and interpret the implications. To reach this, it calls for effective method to store and output data in the course of data processing. This paper aims to propose DFIOC (Digital Forensic Indicators Of Compromise) that is capable of transcribing a variety of forensic artifact information effectively during incident analysis and response. DFIOC, which is XML based format, provides "Evidence" to represent various forensic artifacts in the incident investigation. Furthermore, It provides "Forensic Analysis" to report forensic analysis result and also gives "Indicator" to investigate the trace of incidence quickly. By logging data into one sheet in DFIOC format for forensic analysis process, it is capable of avoiding unnecessary data processing. Lastly, since collected information is recorded in a normalized format, data input and output becomes much easier as well as it will be convenient to use for identification of collected information and analysis of data relationship.