• Title/Summary/Keyword: malicious code

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Detecting ShellCode Using Entropy (엔트로피를 이용한 ShellCode 탐지 방법)

  • Kim, Woosuk;Kang, Sunghoon;Kim, Kyungshin;Kim, Seungjoo
    • KIPS Transactions on Computer and Communication Systems
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    • v.3 no.3
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    • pp.87-96
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    • 2014
  • Hackers try to achieve their purpose in a variety of ways, such as operating own website and hacking a website. Hackers seize a large amount of private information after they have made a zombie PC by using malicious code to upload the website and it would be used another hacking. Almost detection technique is the use Snort rule. When unknown code and the patterns in IDS/IPS devices are matching on network, it detects unknown code as malicious code. However, if unknown code is not matching, unknown code would be normal and it would attack system. Hackers try to find patterns and make shellcode to avoid patterns. So, new method is needed to detect that kinds of shellcode. In this paper, we proposed a noble method to detect the shellcode by using Shannon's information entropy.

An Analysis Technique for Encrypted Unknown Malicious Scripts (알려지지 않은 악성 암호화 스크립트에 대한 분석 기법)

  • Lee, Seong-Uck;Hong, Man-Pyo
    • Journal of KIISE:Information Networking
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    • v.29 no.5
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    • pp.473-481
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    • 2002
  • Decryption of encrypted malicious scripts is essential in order to analyze the scripts and to determine whether they are malicious. An effective decryption technique is one that is designed to consider the characteristics of the script languages rather than the specific encryption patterns. However, currently X-raying and emulation are not the proper techniques for the script because they were designed to decrypt binary malicious codes. In addition to that, heuristic techniques are unable to decrypt unknown script codes that use unknown encryption techniques. In this paper, we propose a new technique that will be able to decrypt malicious scripts based on analytical approach. we describe its implementation.

A Study proposal for URL anomaly detection model based on classification algorithm (분류 알고리즘 기반 URL 이상 탐지 모델 연구 제안)

  • Hyeon Wuu Kim;Hong-Ki Kim;DongHwi Lee
    • Convergence Security Journal
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    • v.23 no.5
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    • pp.101-106
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    • 2023
  • Recently, cyberattacks are increasing in social engineering attacks using intelligent and continuous phishing sites and hacking techniques using malicious code. As personal security becomes important, there is a need for a method and a solution for determining whether a malicious URL exists using a web application. In this paper, we would like to find out each feature and limitation by comparing highly accurate techniques for detecting malicious URLs. Compared to classification algorithm models using features such as web flat panel DB and based URL detection sites, we propose an efficient URL anomaly detection technique.

A Study of Detecting Malicious Files using Similarity between Machine Code in Deleted File Slices (삭제된 파일 조각에서 기계어 코드 유사도를 이용한 악의적인 파일 탐지에 대한 연구)

  • Lee, Dong-Ju;Lee, Suk-Bong;Kim, Min-Soo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.16 no.6
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    • pp.81-93
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    • 2006
  • A file system is an evidence resource of cyber crime in computer forensics. Therefore the methods of recovering the file system and searching important information have been offered. However, the methods for finding a malicious fie in free blocks or slack spaces have not been suggested. In this paper, we propose an investigation method to find a maliciously executable fragmented file. After estimating if a file is executable with a machine code rate, we conclude it could be malicious by comparing a similarity of instruction sequences. To examine instruction sequences, we also propose a method of profiling malicious files using file and a method of comparing the continued scores. As the results, we could exactly pick out the malicious execution files, such as buffer overflow attack program, at fitting threshold level.

Malicious Code Injection Vulnerability Analysis in the Deflate Algorithm (Deflate 압축 알고리즘에서 악성코드 주입 취약점 분석)

  • Kim, Jung-hoon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.5
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    • pp.869-879
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    • 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.

Mepelyzer : Malicious App Identification Mechanism based on Method & Permission Similarity Analysis of Server-Side Polymorphic Mobile Apps (Mepelyzer : 서버 기반 다형상 모바일 앱에 대한 메소드 및 퍼미션 유사도 기반 악성앱 판별)

  • Lee, Han Seong;Lee, Hyung-Woo
    • Journal of the Korea Convergence Society
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    • v.8 no.3
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    • pp.49-61
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    • 2017
  • Recently, convenience and usability are increasing with the development and deployment of various mobile applications on the Android platform. However, important information stored in the smartphone is leaked to the outside without knowing the user since the malicious mobile application is continuously increasing. A variety of mobile vaccines have been developed for the Android platform to detect malicious apps. Recently discovered server-based polymorphic(SSP) malicious mobile apps include obfuscation techniques. Therefore, it is not easy to detect existing mobile vaccines because some other form of malicious app is newly created by using SSP mechanism. In this paper, we analyze the correlation between the similarity of the method in the DEX file constituting the core malicious code and the permission similarity measure through APK de-compiling process for the SSP malicious app. According to the analysis results of DEX method similarity and permission similarity, we could extract the characteristics of SSP malicious apps and found the difference that can be distinguished from the normal app.

Cloud-based malware QR Code detection system (클라우드 기반 악성 QR Code 탐지 시스템)

  • Kim, Dae-Woon;Jo, Young-Tae;Kim, Jong-Min
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.9
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    • pp.1227-1233
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    • 2021
  • QR Code has been used in various forms such as simple business cards and URLs. Recently, the influence of Corona 19 Fundemik has led to the use of QR Codes to track travel routes through visits and entry / exit records, and QR Code usage has skyrocketed. In this way, most people have come to use it in the masses and are constantly under threat. In the case of QR Code, you do not know what you are doing until you execute it. Therefore, if you undoubtedly execute a QR Code with a malicious URL inserted, you will be directly exposed to security threats. Therefore, this paper provides a cloud-based malware QR Code detection system that can make a normal connection only when there is no abnormality after determining whether it is a malicious QR Code when scanning the QR Code.

Analysis and Countermeasure for BadUSB Vulnerability (BadUSB 취약점 분석 및 대응 방안)

  • Seo, Jun-Ho;Moon, Jong-Sub
    • IEMEK Journal of Embedded Systems and Applications
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    • v.12 no.6
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    • pp.359-368
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    • 2017
  • As the BadUSB is a vulnerability, in which a hacker tampers the firmware area of a USB flash drive. When the BadUSB device is plugged into the USB port of a host system, a malicious code acts automatically. The host system misunderstands the act of the malicious behavior as an normal behaviour for booting the USB device, so it is hard to detect the malicious code. Also, an antivirus software can't detect the tampered firmware because it inspects not the firmware area but the storage area. Because a lot of computer peripherals (such as USB flash drive, keyboard) are connected to host system with the USB protocols, the vulnerability has a negative ripple effect. However, the countermeasure against the vulnerability is not known now. In this paper, we analyze the tampered area of the firmware when a normal USB device is changed to the BadUSB device and propose the countermeasure to verify the integrity of the area when the USB boots. The proposed method consists of two procedures. The first procedure is to verify the integrity of the area which should be fixed even if the firmware is updated. The verification method use hashes, and the target area includes descriptors. The second procedure is to verify the integrity of the changeable area when the firmware is updated. The verification method use code signing, and the target area includes the function area of the firmware. We also propose the update protocol for the proposed structure and verify it to be true through simulation.

A study of extended processor trace decoder structure for malicious code detection (악성코드 검출을 위한 확장된 프로세서 트레이스 디코더 구조 연구)

  • Kang, Seungae;Kim, Youngsoo;Kim, Jonghyun;Kim, Hyuncheol
    • Convergence Security Journal
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    • v.18 no.5_1
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    • pp.19-24
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    • 2018
  • For a long time now, general-purpose processors have provided dedicated hardware / software tracing modules to provide developers with tools to fix bugs. A hardware tracer generates its enormous data into a log that is used for both performance analysis and debugging. Processor Trace (PT) is a new hardware-based tracing feature for Intel CPUs that traces branches executing on the CPU, which allows the reconstruction of the control flow of all executed code with minimal labor. Hardware tracer has been integrated into the operating system, which allows tight integration with its profiling and debugging mechanisms. However, in the Windows environment, existing studies related to PT focused on decoding only one flow in sequence. In this paper, we propose an extended PT decoder structure that provides basic data for real-time trace and malicious code detection using the functions provided by PT in Windows environment.

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Image-Based Machine Learning Model for Malware Detection on LLVM IR (LLVM IR 대상 악성코드 탐지를 위한 이미지 기반 머신러닝 모델)

  • Kyung-bin Park;Yo-seob Yoon;Baasantogtokh Duulga;Kang-bin Yim
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.34 no.1
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    • pp.31-40
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    • 2024
  • Recently, static analysis-based signature and pattern detection technologies have limitations due to the advanced IT technologies. Moreover, It is a compatibility problem of multiple architectures and an inherent problem of signature and pattern detection. Malicious codes use obfuscation and packing techniques to hide their identity, and they also avoid existing static analysis-based signature and pattern detection techniques such as code rearrangement, register modification, and branching statement addition. In this paper, We propose an LLVM IR image-based automated static analysis of malicious code technology using machine learning to solve the problems mentioned above. Whether binary is obfuscated or packed, it's decompiled into LLVM IR, which is an intermediate representation dedicated to static analysis and optimization. "Therefore, the LLVM IR code is converted into an image before being fed to the CNN-based transfer learning algorithm ResNet50v2 supported by Keras". As a result, we present a model for image-based detection of malicious code.