• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.555-562
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• 2009

In malware accident investigation, the most important thing is detection of malicious code. Signature based anti-virus softwares have been used in most of the accident. Malware can easily avoid signature based detection by using packing or encryption method. Because of this, packed file detection is also important. Detection methods can be divided into signature based detection and entropy based detection. Signature based detection can not detect new packing. And entropy based detection has a problem with false positive. We provides detection method using entropy statistics of entry point section and 'write' properties of essential characteristic of packed file. And then, we show packing detection tool and evaluate its performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3258-3279
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• 2019

Recently, ransomware has earned itself an infamous reputation as a force to reckon with in the cybercrime landscape. However, cybercriminals are adopting other unconventional means to seamlessly attain proceeds of cybercrime with little effort. Cybercriminals are now acquiring cryptocurrencies directly from benign Internet users without the need to extort a ransom from them, as is the case with ransomware. This paper investigates advances in the cryptovirology landscape by examining the state-of-the-art cryptoviral attacks. In our approach, we perform digital autopsy on the malware's source code and execute the different malware variants in a contained sandbox to deduce static and dynamic properties respectively. We examine three cryptoviral attack structures: browser-based crypto mining, memory resident crypto mining and cryptoviral extortion. These attack structures leave a trail of digital forensics evidence when the malware interacts with the file system and generates noise in form of network traffic when communicating with the C2 servers and crypto mining pools. The digital forensics evidence, which essentially are IOCs include network artifacts such as C2 server domains, IPs and cryptographic hash values of the downloaded files apart from the malware hash values. Such evidence can be used as seed into intrusion detection systems for mitigation purposes.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.1
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• pp.107-122
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• 2014

The DDoS attacks and the APT attacks occurred by the zombie computers simultaneously attack target systems at a fixed time, caused social confusion. These attacks require many zombie computers running attacker's commands, and unknown malware that can bypass detecion of the anti-virus products is being executed in those computers. A that time, many methods have been proposed for the detection of unknown malware against the anti-virus products that are detected using the signature. This paper proposes a method of unknown malware detection using digital forensic techniques and describes the results of experiments carried out on various samples of malware and normal files.

• Convergence Security Journal
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• v.10 no.3
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• pp.61-68
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• 2010

Recently a malware is increasing for leaking personal data, credit information, financial information, etc. The secondary damage is also rapidly increasing such as the illegal use of stolen name, financial fraud, etc. But when a system is infected by a malware of leaking information, the existing malware evidence collection tools do not provide evidences conveniently or sometimes cannot provide necessary evidences. So security officials have much difficulty in responding to malwares. This paper analyzes the current status and problems of the existing malware evidence collection tools and suggests new ways to improve those problems.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.3
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• pp.519-529
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• 2019

Nowadays, intelligent Android malware applies anti-analysis techniques to hide malicious behaviors and make it difficult for anti-virus vendors to detect its presence. Malware can use background components to hide harmful operations, use activity-alias to get around with automation script, or wipe the logcat to avoid forensics. During our study, several static analysis tools can not extract these hidden components like main activity, and dynamic analysis tools also have problem with code coverage due to partial execution of android malware. In this paper, we design and implement a system to analyze intelligent malware that uses anti-analysis techniques to improve detection rate of evasive malware. It extracts the hidden components of malware, runs background components like service, and generates all the intent events defined in the app. We also implemented a real-time logging system that uses modified logcat to block deleting logs from malware. As a result, we improve detection rate from 70.9% to 89.6% comparing other container based dynamic analysis platform with proposed system.

• The Journal of Society for e-Business Studies
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• v.17 no.3
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• pp.117-128
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• 2012

There was a large scale of DDoS(Distributed Denial of Service) attacks mostly targeted at Korean government web sites and cooperations's on March 4, 2010(3.4 DDoS attack) after 7.7 DDoS on July 7, 2009. In these days, anyone can create zombie PCs to attack someone's website with malware development toolkits and farther more improve their knowledge of hacking skills as well as toolkits because it has become easier to obtain these toolkits on line, For that trend, it has been difficult for computer security specialists to counteract DDoS attacks. In this paper, we will introduce an essential control list to prevent malware infection with live forensics techniques after analysis of monitoring network systems and PCs. Hopefully our suggestion of how to coordinate a security monitoring system in this paper will give a good guideline for cooperations who try to build their new systems or to secure their existing systems.

• Journal of the Korea Convergence Society
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• v.8 no.5
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• pp.37-43
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• 2017

A registry is a hierarchy database which is designed to store information necessary for operating system and application programs in Windows operating system, and it is involved in all activities such as booting, logging, service execution, application execution, and user behavior. Digital forensic is widely used. In recent years, malicious codes have penetrated into systems in a way that is not recognized by the user, and valuable information is leaked or stolen, causing financial damages. Therefore, this study proposes a method to detect malicious code by using a shareware application without using expensive digital forensic program, so as to analysis hacking methods and prevent hacking damage in advance.

• Convergence Security Journal
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• v.7 no.3
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• pp.95-100
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• 2007

Alternate Data Streams (ADS) in NTFS originally has developed to provide compatibility with Macintosh Hierarchical File System. However, it is being used by the malware writers in order to support hiding malwares or data for the purpose of anti-forensics. Therefore identifying if hidden ADSs exist and extracting them became one of the most important component in computer forensics. This paper proposes a method to detect ADSs using MFT information. Experiment reveals that proposed method is better in performance and detection rate then others. This method supports not only identification of ADSs which are being used by the operating systems but also investigation of both live systems and evidence images. Therefore it is appropriate for using forensic purpose.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.2
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• pp.407-416
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• 2018

Instagram is a Social Network Service(SNS) that has recently become popular among people of all ages and it makes people to construct social relations and share hobbies, daily routines, and useful information. However, since the uploaded information can be accessed by arbitrary users and it is easily shared with others, frauds, stalking, misrepresentation, impersonation, an infringement of copyright and malware distribution are reported. For this reason, it is necessary to analyze Instagram from a view of digital forensics but the research involved is very insufficient. So in this paper, We performed reverse engineering and dynamic analysis of Instagram from a view of digital forensics in the Android environment. As a result, we checked three database files that contain user behavior analysis data such as chat content, chat targets, posted photos, and cookie information. And we found the path to save 4 files and the xml file to save various data. Also we propose ways to use the above results in digital forensics.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.2
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• pp.87-94
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• 2017

Microsoft Office is an office suite of applications developed by Microsoft. Recently users with malicious intent customize Office files as a container of the Malware because MS Office is most commonly used word processing program. To attack target system, many of malicious office files using a variety of skills and techniques like macro function, hiding shell code inside unused area, etc. And, people usually use two techniques to detect these kinds of malware. These are Signature-based detection and Sandbox. However, there is some limits to what it can afford because of the increasing complexity of malwares. Therefore, this paper propose methods to detect malicious MS office files in Computer forensics' way. We checked Macros and potential problem area with structural analysis of the MS Office file for this purpose.