• Title/Summary/Keyword: Computer Virus Vaccine

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A Design and Implementation of a Solution for Real Detection of Information Leakage by Keylogging Attack (키로깅을 통한 정보유출 실시간 탐지 솔루션 설계 및 구현)

  • Choi, In Young;Choi, Ji Hun;Lee, Won Yeoul
    • Journal of Korea Multimedia Society
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    • v.17 no.10
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    • pp.1198-1204
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    • 2014
  • Most of vaccine type security solutions detect intrusion of computer virus or malicious code. However, they almost don't have functionalities of the information leakage detection. In particular, information leakage through keylogging attact cannot be detected. In this paper, we design and implement a solution to detect the leakage of information through keylogging attact. Proposed solution detects the user-specified information in real time. To detect the leakage of user-specified information, the solution extracts the payload field from each outbound packet and compares with user-specified information. We design the solution to reduce the effect on the packet transmission delay time due to packet monitoring operation. And we design a simple user interface. By proposed solution, user can response to intrusion or information leakage immediately because he or she can perceives a leakage of information in real time.

Core Promoter Mutation of ntC1731T and G1806A of Hepatitis B Virus Increases HBV Gene Expression (B형 간염 바이러스의 ntC1731T 및 G1806A의 core 프로모터 돌연변이에 의한 HBV 유전자 발현 증가 분석)

  • Cho, Ja Young;Yi, Yi Kyaw;Seong, Mi So;Cheong, JaeHun
    • Journal of Life Science
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    • v.32 no.2
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    • pp.94-100
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    • 2022
  • Chronic infection by hepatitis B virus (HBV) greatly increases the risk for liver cirrhosis and hepatocellular carcinoma (HCC). The outcome of HBV infection is shaped by the complex interplay of the mode of transmission, host genetic factors, viral genotype, adaptive mutations, and environmental factors. The pregenomic RNA transcription of HBV for their replication is regulated by the core promoter activation. Core promoter mutations have been the reason for acute liver failure and are associated with HCC development. We obtained HBV genes from a patient in Myanmar who was infected with HBV and identified gene variations in the core promoter region. For measuring the relative transactivation activity of the core promoter, we prepared the core-promoter reporter construct. Among the gene variations of the core promoter, the mutations of C1731T and G1806A were associated with increase in the transactivation of the HBV core promoter. Through computer analysis for searching for a tentative transcription factor binding site, we showed that the mutations of C1713T and G1806A newly created C/EBPβ and XBP1-responsive elements of the core promoter, respectively. The ectopic expression of C/EBPβ largely increased the HBV core promoter containing the C1713T mutation and that of XBP1 activated the M95 promoter containing the G1806A mutation. Our efforts to treat and prevent HBV infections are hampered by the emergence of drug-resistant mutations and vaccine-escape mutations. Our results provide the biological properties and clinical significance of specific HBV core promoter mutations.

A Study on the Cerber-Type Ransomware Detection Model Using Opcode and API Frequency and Correlation Coefficient (Opcode와 API의 빈도수와 상관계수를 활용한 Cerber형 랜섬웨어 탐지모델에 관한 연구)

  • Lee, Gye-Hyeok;Hwang, Min-Chae;Hyun, Dong-Yeop;Ku, Young-In;Yoo, Dong-Young
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.10
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    • pp.363-372
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    • 2022
  • Since the recent COVID-19 Pandemic, the ransomware fandom has intensified along with the expansion of remote work. Currently, anti-virus vaccine companies are trying to respond to ransomware, but traditional file signature-based static analysis can be neutralized in the face of diversification, obfuscation, variants, or the emergence of new ransomware. Various studies are being conducted for such ransomware detection, and detection studies using signature-based static analysis and behavior-based dynamic analysis can be seen as the main research type at present. In this paper, the frequency of ".text Section" Opcode and the Native API used in practice was extracted, and the association between feature information selected using K-means Clustering algorithm, Cosine Similarity, and Pearson correlation coefficient was analyzed. In addition, Through experiments to classify and detect worms among other malware types and Cerber-type ransomware, it was verified that the selected feature information was specialized in detecting specific ransomware (Cerber). As a result of combining the finally selected feature information through the above verification and applying it to machine learning and performing hyper parameter optimization, the detection rate was up to 93.3%.