• Journal of the Korea Society of Computer and Information
• /
• v.25 no.11
• /
• pp.131-138
• /
• 2020

Malware is generally recognized as a computer program that penetrates another computer system and causes malicious behavior intended by the developer. In cyberspace, it is also used as a cyber weapon to attack adversary. The most important factor that a malware must have as a cyber weapon is that it must achieve its intended purpose before being detected by the other's detection system. It requires a lot of time and expertise to create a single malware to avoid the other's detection system. We propose the framework that automatically generates variant malware when a binary code type malware is input using the DCM technique. In this framework, the sample malware was automatically converted into variant malware, and it was confirmed that this variant malware was not detected in the signature-based malware detection system.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.28 no.6
• /
• pp.1463-1474
• /
• 2018

Fuzzing is one of the software testing techniques that find security flaws by inputting invalid values or arbitrary values into the program and various methods have been suggested to increase the efficiency of such fuzzing. In this paper, focusing on the existence of field with high relevance to coverage and software crash, we propose a new method for intensively fuzzing corresponding field part while performing field based fuzzing. In this case, we use a deep learning model called Variational Autoencoder(VAE) to learn the statistical characteristic of input values measured in high coverage and it showed that the coverage of the regenerated files are uniformly higher than that of simple variation. It also showed that new crash could be found by learning the statistical characteristic of the files in which the crash occurred and applying the dropout during the regeneration. Experimental results showed that the coverage is about 10% higher than the files in the queue of the AFL fuzzing tool and in the Hwpviewer binary, we found two new crashes using two crashes that found at the initial fuzzing phase.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.32 no.5
• /
• pp.869-879
• /
• 2022

Through this study, we discovered that among three types of compressed data blocks generated through the Deflate algorithm, No-Payload Non-Compressed Block type (NPNCB) which has no literal data can be randomly generated and inserted between normal compressed blocks. In the header of the non-compressed block, there is a data area that exists only for byte alignment, and we called this area as DBA (Disposed Bit Area), where an attacker can hide various malicious codes and data. Finally we found the vulnerability that hides malicious codes or arbitrary data through inserting NPNCBs with infected DBA between normal compressed blocks according to a pre-designed attack scenario. Experiments show that even though contaminated NPNCB blocks were inserted between normal compressed blocks, commercial programs decoded normally contaminated zip file without any warning, and malicious code could be executed by the malicious decoder.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.7
• /
• pp.111-123
• /
• 2013

To verify software vulnerability, the method of conjecturing software structure and then testing the software based on the conjectured structure has been highlighted. To utilize the method, an efficient way to conjecture software structure is required. The popular graph and tree methods such as DFG(Data Flow Graph), CFG(Control Flow Graph) and CFA(Control Flow Automata) have a serious drawback. That is, they cannot express software in a hierarchical fashion. In this paper, we propose a method to overcome the drawback. The proposed method applies various input data to a binary code, generate CFG's based on the code output and construct a HCFG (Hierarchical Control Flow Graph) to express the generated CFG's in a hierarchical structure. The components required for HCFG and progressive algorithm to construct HCFG are also proposed. The proposed method is verified through constructing the software architecture of an open SMTP(Simple Mail Transfer Protocol) server program. The structure generated by the proposed method and the real program structure are compared and analyzed.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.17 no.2
• /
• pp.116-121
• /
• 2014

In order to study the improvement of the multi stage regeneration cycles, muti-stage processes were applied to the cycles, respectively or together. The kinds of the cycles are multi stage reheater cycle (MS) and multi stage reheater regeneration cycle (MSR). Working fluid used was R134a and R245fa. Temperature of the heat source was $65^{\circ}C$, $75^{\circ}C$, and $85^{\circ}C$, and temperature of the heat sink was $5^{\circ}C$. Optimization simulation was conducted for improving the gross power and efficiency with multi stage reheater regeneration cycle for ocean thermal energy conversion(OTEC) with changing of a heat source, kind of the working fluid, and type of the cycle. Performance analysis of the various components was simulated by using the Aspen HYSYS for analysis of the thermodynamic cycle. R245fa shows better performance than R134a. This paper showed the most suitable working fluid with changing of a heat source and the kinds of working cycle. Compared to each other, MS showed better performance at gross power and MSR showed higher cycle efficiency.