• IEIE Transactions on Smart Processing and Computing
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• v.5 no.2
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• pp.94-99
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• 2016

Application layer attacks have for years posed an ever-serious threat to network security, since they always come after a technically legitimate connection has been established. In recent years, cyber criminals have turned to fully exploiting the web as a medium of communication to launch a variety of forbidden or illicit activities by spreading malicious automated software (auto-ware) such as adware, spyware, or bots. When this malicious auto-ware infects a network, it will act like a robot, mimic normal behavior of web access, and bypass the network firewall or intrusion detection system. Besides that, in a private and large network, with huge Hypertext Transfer Protocol (HTTP) traffic generated each day, communication behavior identification and classification of auto-ware is a challenge. In this paper, based on a previous study, analysis of auto-ware communication behavior, and with the addition of new features, a method for classification of HTTP auto-ware communication is proposed. For that, a Not Only Structured Query Language (NoSQL) database is applied to handle large volumes of unstructured HTTP requests captured every day. The method is tested with real HTTP traffic data collected through a proxy server of a private network, providing good results in the classification and detection of suspicious auto-ware web access.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.294-300
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• 2006

This case study shows constructing the knowledge-based system using a rule-based approach for detecting transactions regarding money laundering in the Korea Financial Intelligence Unit (KoFIU). To better manage the explosive increment of low risk suspicious transactions reporting from financial institutions and to conjugate data converged into the KoFIU from various organizations, the adoption of a knowledge-based system is definitely required. We designed and constructed the knowledge-based system for anti-money laundering by committing experts of each specific financial industry co-worked with a knowledge engineer. The outcome of the knowledge base implementation shows that the knowledge-based system is filtering STRs in the primary analysis step efficiently and so has made great contribution to improve efficiency and effectiveness of the analysis process. It can be said that establishing the foundation of the knowledge base under the entire framework of the knowledge-based system for consideration of knowledge creation and management is indeed valuable.

• The Korean Journal of Pain
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• v.9 no.1
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• pp.98-101
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• 1996

Background: Lumbar epidural steroid injection for relief of low back pain and sciatica has become a popular procedure. further, cervical epidural steroid injection with nerve block (CESNB) is known to be effective for the management of acute and chronic pain of neck, shoulder and arm. However, many anesthesiologists are not familiar with CESNB. Methods: Charts of 34 patients who had undergone 60 cervical epidural steroid injections over a three year period, 1993 to 1995, were reviewed. We studied the followings: initial visit and department, injected interspaces, personal characteristics, indications for injection and complications. Results: Patients' first visits were mainly to orthopaedics (11 patients) and neurosurgery (10 patients). Epidural injection sites were: C7-T1 interspace (29 patients) and C6-C7 interspace (6 patients). Mean age of patients were 50.1 years. range 21~73 years. There were twenty male and fourteen female patients. Complications varied from dizziness after CESNB (1 patient). loss of consciousness with transient apnea (2 patients), and local infection with suspicious meningitis (1 patient). Conclusion: We conclude from the above data that CESNB is a good, safe and conservative form of therapeutic procedure in the management of patients suffering from cervical radiculopathy, and neck and shoulder pain.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.352-359
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• 2021

The purpose of this study is to design and build fake news discrimination systems and methods using fact-checking guidelines. In other words, the main content of this study is the system for identifying fake news using Artificial Intelligence -based Fact-checking guidelines. Specifically planned guidelines are needed to determine fake news that is prevalent these days, and the purpose of these guidelines is fact-checking. Identifying fake news immediately after seeing a huge amount of news is inefficient in handling and ineffective in handling. For this reason, we would like to design a fake news identification system using the fact-checking guidelines to create guidelines based on pattern analysis against fake news and real news data. The model will monitor the fact-checking guideline model modeled to determine the Fact-checking target within the news article and news articles shared on social networking service sites. Through this, the model is reflected in the fact-checking guideline model by analyzing news monitoring devices that select suspicious news articles based on their user responses. The core of this research model is a fake news identification device that determines the authenticity of this suspected news article. So, we propose news article identification methods with fact-checking guideline on Artificial Intelligence & Bigdata. This study will help news subscribers determine news that is unclear in its authenticity.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.800-806
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• 2019

This paper presents a laboratory experiment on data acquisition technique that applied to the gamma radiation scanning coupled with computed tomography (CT) technique for inspection of broken nozzle inside the vertical vessel. The acquisition technique was developed to inspect a large diameter vessel when suspicious problem location is not easily accessed. This technique allows the installation of gamma radiation source (Cesium 137, Cs-137), and detectors (Sodium Iodine. NaI(Tl)) from the accessible location to the required location and performs the scanning by designed pattern. To demonstrate the designed technique, top opened tank which installed with six cut steel pipes diameter of 76.2 mm (3") at a certain position was selected. They were assumed to be a gas riser pipes inside the vessel. Three studied cases were performed, (a) projection of well installed six pipes, (b) projection of one out of six broken pipe and (c) one of nozzle was assumed to be failure and fell down until one out of six pipes was broken and obstructed by nozzle. Results clearly indicated the capability of developed technique to distinguish between normal situation case and abnormal situation cases.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.27-33
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• 2019

One of serious security threats is a botnet-based attack. A botnet in general consists of numerous bots, which are computing devices with networking function, such as personal computers, smartphones, or tiny IoT sensor devices compromised by malicious codes or attackers. Such botnets can launch various serious cyber-attacks like DDoS attacks, propagating mal-wares, and spreading spam e-mails over the network. To establish a botnet, attackers usually inject malicious URLs into web source codes stealthily by using data hiding methods like Javascript obfuscation techniques to avoid being discovered by traditional security systems such as Firewall, IPS(Intrusion Prevention System) or IDS(Intrusion Detection System). Meanwhile, it is non-trivial work in practice for software developers to manually find such malicious URLs which are hidden in numerous web source codes stored in web servers. In this paper, we propose a security defense system to discover such suspicious, malicious URLs hidden in web source codes, and present experiment results that show its discovery performance. In particular, based on our experiment results, our proposed system discovered 100% of URLs hidden by Javascript encoding obfuscation within sample web source files.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.27-35
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• 2002

A knowledge-based image retrieval technique is image searching methods using some features from the queried image. The materials in this study are automobile head lamps. The input data is composed of characters and images which have various pattern. The numbers, special symbols, and general letters are under the category of the character. The image informations are made up of the distribution of pixel data, statistical analysis, and state of pattern which are useful for the knowledge data. In this paper, we implemented a retrieval system for the scientific crime detection at traffic accident using the proposed multi knowledge-based image retrieval technique. The values for the multi knowledge-based image features were extracted from color and gray scale each. With this 22 features, we improved the retrieval efficiency about the color information and pattern information. Visual basic, crystal report and MS access DB were used for this application. We anticipate the efficient scientific detection for the traffic accident and the tracking of suspicious vehicle.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4511-4515
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• 2012

Background: In the Middle East, including Iran, breast cancer is the most frequent malignancy among women. Without treatment, a malignant breast tumor advances in stage, diminishing a woman's chances of survival. In this study we aimed to gain insight into the causes of delay in seeking treatment in patients with breast cancer. Methods: The participants in this qualitative, content analysis study were 10 women in whom a diagnosis of breast cancer in the stages of II b, III or IIV had been made. They were selected from patients of a major oncology clinic in Kerman, Iran. Data were collected by means of semi-structured interviews that lasted between 20 to 30 minutes. Sampling was discontinued when data saturation was achieved. Content analysis was conducted by classifying the data into themes and sub-themes. Results: The results of our study revealed several factors that interfered with patients' professional consultation seeking and prompt treatment. These factors included; lack of knowledge, fear of being diagnosed with cancer, not seeing oneself at risk, mental preoccupation and wrong diagnosis by physicians. Conclusions: This study suggests that women and even physicians need further information about breast cancer symptoms. Women need encouragement to seek medical advice when they encounter suspicious symptoms. Additionally, women may benefit from awareness of the pros of early detection and reassurance about the improvements in the success of breast cancer treatment.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.847-858
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• 2015

Deep-sea fishery in the Antarctic Ocean has been actively progressed by the developed countries including Korea. In order to prevent the environmental destruction of the Antarctic Ocean, related countries have established the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) and have monitored any illegal unreported or unregulated fishing. Fishing of tooth fish, an expensive fish, in the Antarctic Ocean has increased recently and high catches per unit effort (CPUE) of fishing boats, which is suspicious for an illegal activity, have been frequently reported. The data of CPUEs in a fishing area of the Antarctic Ocean often show an extreme Distribution or a mixture of two extreme distributions. This paper proposes an algorithm to detect an outlier of CPUEs by using the mixture of two extreme distributions. The parameters of the mixture distribution are estimated by the EM algorithm. Log likelihood value and posterior probabilities are used to detect an outlier. Experiments show that the proposed algorithm to detect outlier of the data can be adopted instead of simple criteria such as a CPUE is greater than 1.

• Journal of the Korean Society of Radiology
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• v.84 no.1
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• pp.34-50
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• 2023

In 2019, the American College of Radiology announced Lung CT Screening Reporting & Data System (Lung-RADS) 1.1 to reduce lung cancer false positivity compared to that of Lung-RADS 1.0 for effective national lung cancer screening, and in December 2022, announced the new Lung-RADS 1.1, Lung-RADS^Ⓡ 2022 improvement. The Lung-RADS^Ⓡ 2022 measures the nodule size to the first decimal place compared to that of the Lung-RADS 1.0, to category 2 until the juxtapleural nodule size is < 10 mm, increases the size criterion of the ground glass nodule to 30 mm in category 2, and changes categories 4B and 4X to extremely suspicious. The category was divided according to the airway nodules location and shape or wall thickness of atypical pulmonary cysts. Herein, to help radiologists understand the Lung-RADS^Ⓡ 2022, this review will describe its advantages, disadvantages, and future improvements.