• Journal of Digital Convergence
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• v.10 no.9
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• pp.1-13
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• 2012

This study aims to analyze actual conditions of the present national defense information network operation, the structure and management of the system, communication lines, security equipments for the lines, the management of network and software, stored data and transferred data and even general vulnerable factors of our army tactical C4I system. Out of them, by carrying out an extensive analysis of the army tactical C4I system, likely to be the core of future information warfare, this study suggested plans adaptive to better information security, based on the vulnerable factors provided. Firstly, by suggesting various information security factor technologies, such as VPN (virtual private network), IPDS (intrusion prevention & detection system) and firewall system against virus and malicious software as well as security operation systems and validation programs, this study provided plans to improve the network, hardware (computer security), communication lines (communication security). Secondly, to prepare against hacking warfare which has been a social issue recently, this study suggested plans to establish countermeasures to increase the efficiency of the army tactical C4I system by investigating possible threats through an analysis of hacking techniques. Thirdly, to establish a more rational and efficient national defense information security system, this study provided a foundation by suggesting several priority factors, such as information security-related institutions and regulations and organization alignment and supplementation. On the basis of the results above, this study came to the following conclusion. To establish a successful information security system, it is essential to compose and operate an efficient 'Integrated Security System' that can detect and promptly cope with intrusion behaviors in real time through various different-type security systems and sustain the component information properly by analyzing intrusion-related information.

• Biomolecules & Therapeutics
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• v.22 no.6
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• pp.532-539
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• 2014

Peripheral neuropathy induced by human immunodeficiency virus (HIV) infection and antiretroviral therapy is not only difficult to distinguish in clinical practice, but also difficult to relieve the pain symptoms by analgesics because of the severity of the disease at the later stage. Hence, to explore the mechanisms of HIV-related neuropathy and find new therapeutic options are particularly important for relieving neuropathic pain symptoms of the patients. In the present study, primary cultured embryonic rat dorsal root ganglion (DRG) neurons were used to determine the neurotoxic effects of HIV-gp120 protein and/or antiretroviral drug dideoxycytidine (ddC) and the therapeutic actions of insulin-like growth factor-1 (IGF-1) on gp120- or ddC-induced neurotoxicity. DRG neurons were exposed to gp120 (500 pmol/L), ddC ($50{\mu}mol/L$), gp120 (500 pmol/L) plus ddC ($50{\mu}mol/L$), gp120 (500 pmol/L) plus IGF-1 (20 nmol/L), ddC ($50{\mu}mol/L$) plus IGF-1 (20 nmol/L), gp120 (500 pmol/L) plus ddC ($50{\mu}mol/L$) plus IGF-1 (20 nmol/L), respectively, for 72 hours. The results showed that gp120 and/or ddC caused neurotoxicity of primary cultured DRG neurons. Interestingly, the severity of neurotoxicity induced by gp120 and ddC was different in different subpopulation of DRG neurons. gp120 mainly affected large diameter DRG neurons (> $25{\mu}m$), whereas ddC mainly affected small diameter DRG neurons (${\leq}25{\mu}m$). IGF-1 could reverse the neurotoxicity induced by gp120 and/or ddC on small, but not large, DRG neurons. These data provide new insights in elucidating the pathogenesis of HIV infection- or antiretroviral therapy-related peripheral neuropathy and facilitating the development of novel treatment strategies.

• Journal of Platform Technology
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• v.9 no.3
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• pp.3-17
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• 2021

Advanced persistent threat (APT) attacks are attacks aimed at a particular entity as a set of latent and persistent computer hacking processes. These APT attacks are usually carried out through various methods, including spam mail and disguised banner advertising. The same name is also used for files, since most of them are distributed via spam mail disguised as invoices, shipment documents, and purchase orders. In addition, such Infostealer attacks were the most frequently discovered malicious code in the first week of February 2021. CDR is a 'Content Disarm & Reconstruction' technology that can prevent the risk of malware infection by removing potential security threats from files and recombining them into safe files. Gartner, a global IT advisory organization, recommends CDR as a solution to attacks in the form of attachments. There is a program using CDR techniques released as open source is called 'Dangerzone'. The program supports the extension of most document files, but does not support the extension of HWP files that are widely used in Korea. In addition, Gmail blocks malicious URLs first, but it does not block malicious URLs in mail systems such as Naver and Daum, so malicious URLs can be easily distributed. Based on this problem, we developed a 'Dangerzone' program that supports the HWP extension to prevent APT attacks, and a Chrome extension that performs URL checking in Naver and Daum mail and blocking banner ads.

• 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%.