• Biomedical Science Letters
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• v.27 no.4
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• pp.195-207
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• 2021

Methicillin-resistant Staphylococcus aureus (MRSA) is a bacterial pathogen capable of causing human diseases, such as soft tissue infection, bacteremia, endocarditis, toxic shock syndrome, pneumonia, and sepsis. Although the incidence rate of diseases caused by MRSA has declined in recent years, these diseases still pose a clinical threat due to their consistently high morbidity and mortality rates. However, the role of virulence factors in staphylococcal infections remains incompletely understood. Methicillin resistance, which confers resistance to all β-lactam antibiotics in cellular islets, is mediated by the mecA gene in the staphylococcal cassette chromosome mec (SCCmec). Differences in SCCmec types and differences in their sizes and structures serve epidemiological purposes and are used to differentiate between hospital-associated (HA)-MRSA and community-associated (CA)-MRSA. Some virulence factors of S. aureus are also providing a distinction between HA-MRSA and CA-MRSA. These factors vary depending on the presence of toxins, adhesion, immune evasion, and other virulence determinants. In this review, we summarized an overview of MRSA such as resistance mechanisms, SCCmec types, HA- and CA-MRSA, and virulence factors that enhance pathogenicity or MRSA epidemiology, transmission, and genetic diversity.

• Journal of Korea Multimedia Society
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• v.25 no.6
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• pp.878-885
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• 2022

Research in the field of computer vision based on deep learning is being actively conducted. However, deep learning-based models have vulnerabilities in adversarial attacks that increase the model's misclassification rate by applying adversarial perturbation. In particular, in the case of FGSM, it is recognized as one of the effective attack methods because it is simple, fast and has a considerable attack success rate. Meanwhile, as one of the efforts to visualize deep learning models, Grad-CAM enables visual explanation of convolutional neural networks. In this paper, I propose a method to generate adversarial examples with high attack success rate by applying Grad-CAM to FGSM. The method chooses fixels, which are closely related to labels, by using Grad-CAM and add perturbations to the fixels intensively. The proposed method has a higher success rate than the FGSM model in the same perturbation for both targeted and untargeted examples. In addition, unlike FGSM, it has the advantage that the distribution of noise is not uniform, and when the success rate is increased by repeatedly applying noise, the attack is successful with fewer iterations.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.288-294
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• 2021

There are various ways to be infected with malicious code due to the increase in Internet use, such as the web, affiliate programs, P2P, illegal software, DNS alteration of routers, word processor vulnerabilities, spam mail, and storage media. In addition, malicious codes are produced more easily than before through automatic generation programs due to evasion technology according to the advancement of production technology. In the past, the propagation speed of malicious code was slow, the infection route was limited, and the propagation technology had a simple structure, so there was enough time to study countermeasures. However, current malicious codes have become very intelligent by absorbing technologies such as concealment technology and self-transformation, causing problems such as distributed denial of service attacks (DDoS), spam sending and personal information theft. The existing malware detection technique, which is a signature detection technique, cannot respond when it encounters a malicious code whose attack pattern has been changed or a new type of malicious code. In addition, it is difficult to perform static analysis on malicious code to which code obfuscation, encryption, and packing techniques are applied to make malicious code analysis difficult. Therefore, in this paper, a method to detect malicious code through dynamic analysis and static analysis using Trojan-type Downloader/Dropper malicious code was showed, and suggested to malicious code detection and countermeasures.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1279-1290
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• 2021

As vehicle technology has grown, autonomous driving that does not require driver intervention has developed. Accordingly, CAN security, an network of in-vehicles, has also become important. CAN shows vulnerabilities in hacking attacks, and machine learning-based IDS is introduced to detect these attacks. However, despite its high accuracy, machine learning showed vulnerability against adversarial examples. In this paper, we propose a adversarial CAN frame generation method to avoid IDS by adding noise to feature and proceeding with feature selection and re-packet for physical attack of the vehicle. We check how well the adversarial CAN frame avoids IDS through experiments for each case that adversarial CAN frame generated by all feature modulation, modulation after feature selection, preprocessing after re-packet.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.267-280
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• 2023

The relationship between the state and taxation starts from the establishment of the state. The most important element is the concept of "tax compliance". Tax compliance can be considered as the harmony of state-society relations. However, the concept of tax non-compliance occurs when taxpayers do not fulfill their tax-related tasks as required. Tax noncompliance is just one of the costs that occur in tax systems, and is named "tax compliance cost" in the literature. This study focuses on tax compliance costs because tax compliance costs are the ones taxpayers are personally obliged to deal with. For this purpose, the study investigates costs accruing from tax systems, including efficiency, planning, application, and compliance costs. According to the analysis results, it was concluded that the main reason for fraud in the tax systems is high compliance costs and that tax compliance directly impacts social wealth. Besides, the existence of conditions conducive to tax evasion and tax avoidance in a country, short-term tax policies, belief in the unfairness and inequality of tax systems, inadequacy of audits conducted by tax authorities, insufficiency of pressure and deterrence mechanisms, constantly changing legislation, and the attitudes and perceptions regarding the illegitimacy of the government determine tax compliance.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.193-203
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• 2022

After the everyday use of systems and applications of artificial intelligence in our world. Consequently, machine learning technologies have become characterized by exceptional capabilities and unique and distinguished performance in many areas. However, these applications and systems are vulnerable to adversaries who can be a reason to confer the wrong classification by introducing distorted samples. Precisely, it has been perceived that adversarial examples designed throughout the training and test phases can include industrious Ruin the performance of the machine learning. This paper provides a comprehensive review of the recent research on adversarial machine learning. It's also worth noting that the paper only examines recent techniques that were released between 2018 and 2021. The diverse systems models have been investigated and discussed regarding the type of attacks, and some possible security suggestions for these attacks to highlight the risks of adversarial machine learning.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.199-203
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• 2022

The article aims at studying the institution of human rights and civil freedoms with due regard to the anthropological approach in the theory of law. To the greatest extent, the provisions of non-classical legal science are confirmed in the Anglo-Saxon legal family, which endows the judge with law-making functions. In this regard, the role of a person in the legal sphere is increasing. The main research method was deduction used to study the anthropological approach to the institution of human rights and freedoms. The article also utilizes the inductive method, the method of systematic scientific analysis, comparative legal and historical methods. To solve the task set, the authors considered the legal foundations and features of human rights and freedoms in the modern world. The article proves that the classical legal discourse, represented by various types of interpretation, reduces the rule of law to the analysis of its logical structure and does not answer the questions posed. It is concluded that the prerequisite for the anthropological approach in the theory of law is the use of human-like concepts in modern legislation (guilt, justice, peculiar ferocity, child abuse, willful evasion, conscientiousness).

• Journal of Digestive Cancer Research
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• v.10 no.2
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• pp.65-73
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• 2022

A breakthrough in immunotherapy has changed the outlook for metastatic colorectal cancer (mCRC) treatment as the immune surveillance evasion mechanism of tumor cells has been continuously elucidated. Immune checkpoint inhibitors (ICI), such as pembrolizumab, nivolumab, and ipilimumab, which block immune checkpoint receptors or ligands have been approved for the treatment of mismatch repair deficient (dMMR)/microsatellite instability-high (MSI-H) mCRC based on numerous clinical studies. However, 50% of dMMR/MSI-H mCRC and most mismatch repair proficient/microsatellite stable mCRC remained unresponsive to current immunotherapy. Clinical trials on combination therapy that adds various treatments, such as target agents, chemotherapy, or radiation therapy to ICI, have been actively conducted to overcome this immunotherapy limitation. Further studies on safety and efficacy are needed although several trials presented promising data. Additionally, dMMR/MSI-H, tumor mutation burden, and programmed cell death ligand-1 expression have been studied as biomarkers for predicting the treatment response to immunotherapy, but the discovery and validation of more sensitively predictable biomarkers remained necessary. Thus, this study aimed to review recent studies on immunotherapy in mCRC, summarize the efficacy and limitation of immunotherapy, and describe the biomarkers that predict treatment response.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.249-257
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• 2024

This study analyzes the current status and prospects of Iran's air defense network, focusing on the Russian-made S-300 system, and derives implications for the development of South Korea's air defense network. Iran's air defense network exhibits strengths such as long-range detection and interception capabilities, multi-target processing, high-altitude interception, and electronic warfare response. However, it also reveals weaknesses, including lack of mobility, difficulty in detecting low-altitude targets, obsolescence, training level of operating personnel, and vulnerability to electronic warfare. Real-world cases confirm these weaknesses, making the system susceptible to enemy evasion tactics, swarm drone attacks, and electronic warfare. Drawing from Iran's case, South Korea should establish a multi-layered defense system, strengthen low-altitude air defense and electronic warfare capabilities, foster the domestic defense industry for technological self-reliance, and enhance international cooperation. By addressing these aspects, South Korea can establish a robust air defense network and firmly protect its national security. Future research should aim to secure and analyze materials from the Iranian perspective for a more objective evaluation of Iran's air defense network and continuously track Iran's efforts to improve its air defense network and the trend of strengthening drone forces to predict changes in the Middle East security situation.

• IMMUNE NETWORK
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• v.22 no.1
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• pp.2.1-2.22
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• 2022

Targeting immune evasion via immune checkpoint pathways has changed the treatment paradigm in cancer. Since CTLA-4 antibody was first approved in 2011 for treatment of metastatic melanoma, eight immune checkpoint inhibitors (ICIs) centered on PD-1 pathway blockade are approved and currently administered to treat 18 different types of cancers. The first part of the review focuses on the history of CTLA-4 and PD-1 discovery and the preclinical experiments that demonstrated the possibility of anti-CTLA-4 and anti-PD-1 as anti-cancer therapeutics. The approval process of clinical trials and clinical utility of ICIs are described, specifically focusing on non-small cell lung cancer (NSCLC), in which immunotherapies are most actively applied. Additionally, this review covers the combination therapy and novel ICIs currently under investigation in NSCLC. Although ICIs are now key pivotal cancer therapy option in clinical settings, they show inconsistent therapeutic efficacy and limited responsiveness. Thus, newly proposed action mechanism to overcome the limitations of ICIs in a near future are also discussed.