• 한국사이버테러정보전학회:학술대회논문집
• /
• 한국사이버테러정보전학회 2004년도 제1회 춘계학술발표대회
• /
• pp.319-324
• /
• 2004

급속하게 발전한 정보통신 인프라로 인해 인터넷보급이 확산되었으나, 대부분의 사용자들의 전문 보안 지식 부재로 인하여 그 피해가 늘고 있다. 특히 리눅스를 PC로 이용하는 사용자들이 늘어감에 따라 정보유출 등 다양한 위협에 노출되어 있으며, 이는 악의적인 목적을 가진 공격자의 좋은 목표물이 되고 있다. 본 논문에서는 리눅스 서버를 이용하는 사용자들이 손쉽게 공격자로부터의 공격을 방어할 수 있도록 효율적인 포트제어를 할 수 있는 페이크포트(FakePort)를 설계 및 개발하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제6권9호
• /
• pp.2424-2441
• /
• 2012

In this paper, we propose a fake iris detection method that combines the optical and textural features of the human eye. To extract the optical features, we used dual Purkinje images that were generated on the anterior cornea and the posterior lens surfaces based on an analytic model of the human eye's optical structure. To extract the textural features, we measured the amount of change in a given iris pattern (based on wavelet decomposition) with regard to the direction of illumination. This method performs the following two procedures over previous researches. First, in order to obtain the optical and textural features simultaneously, we used five illuminators. Second, in order to improve fake iris detection performance, we used a SVM (Support Vector Machine) to combine the optical and textural features. Through combining the features, problems of single feature based previous works could be solved. Experimental results showed that the EER (Equal Error Rate) was 0.133%.

• 융합보안논문지
• /
• 제9권4호
• /
• pp.35-41
• /
• 2009

현재 인터넷에서 사용중인 라우팅 프로토콜 중 대표적인 프로토콜인 기존의 BGP 프로토콜의 보안을 강화하는 연구들의 비교를 통해 BGP 프로토콜에 문제점으로 부각되고 있는 AS-Path, IP Fake, DRDoS 등의 BGP 프로토콜을 사용할 때 반드시 필요한 정보이지만 악의적인 공격 또는 잘못된 설정으로 인해 전세계 인터넷 망을 동작하지 못하게 할 수 있는 위협적인 사항에 대한 보안성에 대해 분석한다.

• Journal of Information Processing Systems
• /
• 제15권5호
• /
• pp.1029-1035
• /
• 2019

In recent years, artificial intelligence (AI) services have become one of the most essential parts to extend human capabilities in various fields such as face recognition for security, weather prediction, and so on. Various learning algorithms for existing AI services are utilized, such as classification, regression, and deep learning, to increase accuracy and efficiency for humans. Nonetheless, these services face many challenges such as fake news spread on social media, stock selection, and volatility delay in stock prediction systems and inaccurate movie-based recommendation systems. In this paper, various algorithms are presented to mitigate these issues in different systems and services. Convolutional neural network algorithms are used for detecting fake news in Korean language with a Word-Embedded model. It is based on k-clique and data mining and increased accuracy in personalized recommendation-based services stock selection and volatility delay in stock prediction. Other algorithms like multi-level fusion processing address problems of lack of real-time database.

• 한국컴퓨터정보학회:학술대회논문집
• /
• 한국컴퓨터정보학회 2020년도 제62차 하계학술대회논문집 28권2호
• /
• pp.199-202
• /
• 2020

본 논문에서는 가짜뉴스 탐지 모델에 워드 임베딩 기법을 접목하여 성능을 향상시키는 방법을 제안한다. 기존의 한국어 가짜뉴스 탐지 연구는 희소 표현인 빈도-역문서 빈도(TF-IDF)를 활용한 탐지 모델들이 주를 이루었다. 하지만 이는 가짜뉴스 탐지의 관점에서 뉴스의 언어적 특성을 파악하는 데 한계가 존재하는데, 특히 문맥에서 드러나는 언어적 특성을 구조적으로 반영하지 못한다. 이에 밀집 표현 기반의 워드 임베딩 기법인 Word2vec을 활용한 텍스트 전처리를 통해 문맥 정보까지 반영한 가짜뉴스 탐지 모델을 본 연구의 제안 모델로 생성한 후 TF-IDF 기반의 가짜뉴스 탐지 모델을 비교 모델로 생성하여 두 모델 간의 비교를 통한 성능 검증을 수행하였다. 그 결과 Word2vec 기반의 제안모형이 더욱 우수하였음을 확인하였다.

• Journal of Information Science Theory and Practice
• /
• 제10권1호
• /
• pp.59-72
• /
• 2022

This text discusses elements and characteristics of contemporary informational reality, that is, the ways of producing, circulating, organizing, using, and appropriating information in the current context. Initially, seven terms and concepts used to describe this reality are discussed: fake news, false testimonials, hate speech, scientific negationism, disinformation, post-truth, and infodemic. Next, an attempt is made to present a framework for such phenomena as an object of study in information science. Therefore, this scenario is characterized based on the three main models of information science study: physical, cognitive, and social. The contribution of each of them to the study of contemporary informational reality is analyzed, identifying aspects such as the bubble effect, clickbaits, confirmation bias, cults of amateurism, and post-truth culture. Finally, it presents the discussion of a possible veritistic turn in the field, in order to think about elements not covered so far by information science in its task and challenge of producing adequate understanding and diagnoses of current phenomena. In conclusion, it is argued that only accurate and comprehensive diagnoses of such phenomena will allow information science to develop services and systems capable of combating their harmful effects.

• 한국컴퓨터정보학회:학술대회논문집
• /
• 한국컴퓨터정보학회 2023년도 제68차 하계학술대회논문집 31권2호
• /
• pp.213-214
• /
• 2023

스마트폰은 앱을 통하여 사람들에게 다양하고 유용한 기능을 제공하며, 새로운 앱들이 계속해서 개발되어 출시되고 있다. 그러나 이러한 긍정적인 측면에서 불구하고, 사람들의 편리한 사용에 대한 욕구를 이용하여, 신종 앱 사기와 같은 범죄가 발생하고 있으며, 이를 악용하여 금전적으로 피해를 주거나 개인정보를 탈취하는 범죄로가 증가되는 추세이다. 이와 같은 앱으로 인한 범죄를 대응하기 위하여, 신종 앱 사기 범죄를 분석하고 해결하는 방안이 요구되는 실정이다. 따라서 본 논문에서는 신종 앱 사기 범죄에 악용되는 가짜 앱을 탐지하고, 공식 기관에서 제공하는 정보를 기반으로 가짜 앱과 공식 앱에 대한 대량의 정보를 공유하는 프레임워크를 개발한다. 개발한 프레임워크를 통하여, 정보를 공유한 사람들에게 가짜 앱에 대한 정보를 알려주고, 공식 기관의 앱을 확인하는 안전한 모바일 환경을 제공할 것으로 사료된다.

• International Journal of Computer Science & Network Security
• /
• 제21권3호
• /
• pp.127-133
• /
• 2021

Today, phishing attacks represent one of the biggest security threats targeting users of the digital world. They consist of an attempt to steal sensitive information, such as a user's identity or credit and debit card details, using various methods that include fake emails, fake websites, and fake social media messages. Protecting the user's security and privacy therefore becomes complex, especially when those users are children. Currently, children are participating in Internet activity more frequently than ever before. This activity includes, for example, online gaming, communication, and schoolwork. However, children tend to have a less well-developed knowledge of privacy and security concepts, compared to adults. Consequently, they often become victims of cybercrime. In this paper, the effects of security awareness on users who are children are investigated, looking at their ability to detect phishing attacks in social media. In this approach, two Experiments were conducted to evaluate the effects of security awareness on WhatsApp application users in their daily communication. The results of the Experiments revealed that phishing awareness training has a significant positive effect on the ability of children using WhatsApp to identify phishing messages and thereby avoid attacks.

• Journal of Information Science Theory and Practice
• /
• 제11권1호
• /
• pp.1-13
• /
• 2023

This study determines how social media users (SMUs) verify the information they come across on the Internet. It determines SMUs' perception of online fact-checking services in terms of their ease of use, usefulness, and trust. By conducting a focus group discussion and key informant interviews, themes were derived in determining fact-checking practices while a survey was further conducted to determine such perceived ease of use, usefulness, and trust in fact-checking services. The thematic analysis revealed major information verification practices, such as cross-checking and verifying with other sources, inspecting comments and reactions, and confirming from personal and social networks. The results showed that SMUs considered fact-checking services easy to use. However, a concern was raised about their usefulness stemming from the delayed action in addressing the information issues that need to be verified. As to perceived trust, it was found that SMUs have reservations about fact-checking services. Finally, it is believed that fact-checking services are expected to be credible and need to be promoted to mitigate any form of fake news, particularly on social media platforms.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권2호
• /
• pp.892-911
• /
• 2019

Biometric recognition systems have been widely used for information security. Among the most popular biometric traits, there are fingerprint and face due to their high recognition accuracies. However, the security system that uses face recognition as the login method are vulnerable to face-spoofing attacks, from using printed photo or video of the valid user. In this study, we propose a fast and robust method to detect face-spoofing attacks based on the analysis of spatial frequency differences between the real and fake videos. We found that the effect of a spoofing attack stands out more prominently in certain regions of the 2D Fourier spectra and, therefore, it is adequate to use the information about those regions to classify the input video or image as real or fake. We adopt a divide-conquer-aggregate approach, where we first divide the frequency domain image into local blocks, classify each local block independently, and then aggregate all the classification results by the weighted-sum approach. The effectiveness of the methodology is demonstrated using two different publicly available databases, namely: 1) Replay Attack Database and 2) CASIA-Face Anti-Spoofing Database. Experimental results show that the proposed method provides state-of-the-art performance by processing fewer frames of each video.