• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.873-877
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• 2009

본 논문에서는 상황기반 개인정보보호 통합 에이전트를 패키지 형태로 공공기관에 공급 공공기관 내부의 개인정보 관리 시스템에 적용되는 피싱 차단 시스템에 대해서 설계하였다. 이러한 시스템은 공공기관 내부 직원의 개인정보 관리 에이전트로 적용과 상황기반 개인정보보호 통합 에이전트로서 금융기관 등의 솔루션에 적용 가능하다. 주요 내용으로는 피싱 유형과 방법을 분석하고 피싱(Phishing) 웹사이트를 탐지, 차단하는 알고리즘을 원천적으로 개발하여 구현하였다.

• 정보화사회
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• s.171
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• pp.64-67
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• 2004

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.2
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• pp.293-302
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• 2015

With the attack information collected during SMS phishing investigation, this paper will propose SMS phishing profiling model applying criminal profiling. Law enforcement agencies have used signature analysis by apk file hash and analysis of C&C IP address inserted in the malware. However, recently law enforcement agencies are facing the challenges such as signature diversification or code obfuscation. In order to overcome these problems, this paper examined 169 criminal cases and found out that 89% of serial number in cert.rsa and 80% of permission file was reused in different cases. Therefore, the proposed SMS phishing profiling model is mainly based on signature serial number and permission file hash. In addition, this model complements the conventional file hash clustering method and uses code similarity verification to ensure reliability.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.138-142
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• 2009

We propose an effective voice-phishing detection algorithm based on discriminative weight training. The detection of voice phishing is performed based on a Gaussian mixture model (GMM) incorporaiting minimum classification error (MCE) technique. Actually, the MCE technique is based on log-likelihood from the decoding parameter of the SMV(Selectable Mode Vocoder) directly extracted from the decoding process in the mobile phone. According to the experimental result, the proposed approach is found to be effective for the voice phishing detection.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.67-70
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• 2013

스마트폰 보급은 현대인들에게 시간적, 공간적 제약에서 벗어나 언제 어디서나 무선 인터넷을 사용하여 모바일 뱅킹, 결재, 증권거래 등 원하는 서비스를 이용할 수 있게 해주었다. 사용자들은 이를 이용하여 다양한 정보들을 검색, 저장, 이용한다. 그러나 무선 인터넷의 순기능과는 반대로 최근 모바일 기기의 보안취약점을 이용한 악성애플리케이션 및 각종 공격으로 사용자 개인정보탈취의 위협이 증가하고 있다. 사회공학공격의 일종인 피싱(Phishing)은 신뢰받는 기관을 사칭하여 만들어놓은 가짜사이트에 사용자로부터 자신의 개인정보 및 금융정보를 입력하게끔 유도하여 사용자정보를 탈취하는 방법으로 최근 SMS를 이용하여 정부 및 금융기관을 사칭한 문자를 보내 피싱사이트로 접속을 유도하는 피해사례가 증가하고 있다. 본 논문에서는 국내 피싱사이트의 유형을 분석하고 피싱사이트로 접근을 유도하는 방법 중 하나인 SMS를 이용한 피싱을 방지 할 수 있는 시스템을 고안한다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1225-1229
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• 2013

In this paper, we studied threats and risks that users might enter their passwords without awareness onto phishing and pharming sites, and particularly showed that it was highly likely to leak the secret information of multiple passwords by user experiments. The novel methodology of verifying those threats and risks is the major contribution of this paper. We will extend this work for further verification of our findings.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1348-1375
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• 2018

Support Vector Machine (SVM) is a well-known machine learning classification algorithm, which has been widely applied to many data mining problems, with good accuracy. However, SVM classification speed decreases with increase in dataset size. Some applications, like video surveillance and intrusion detection, requires a classifier to be trained very quickly, and on large datasets. Hence, this paper introduces two filter-based instance selection techniques for optimizing SVM training speed. Fast classification is often achieved at the expense of classification accuracy, and some applications, such as phishing and spam email classifiers, are very sensitive to slight drop in classification accuracy. Hence, this paper also introduces two wrapper-based instance selection techniques for improving SVM predictive accuracy and training speed. The wrapper and filter based techniques are inspired by Cuckoo Search Algorithm and Bat Algorithm. The proposed techniques are validated on three popular e-fraud types: credit card fraud, spam email and phishing email. In addition, the proposed techniques are validated on 20 other datasets provided by UCI data repository. Moreover, statistical analysis is performed and experimental results reveals that the filter-based and wrapper-based techniques significantly improved SVM classification speed. Also, results reveal that the wrapper-based techniques improved SVM predictive accuracy in most cases.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.201-204
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• 2013

From 2009 to the present, smart phone users has been steadily increasing. And through the use of smart phone applications, smart phone user can perform easily what they want to do whenever and wherever. However, new types of financial fraud such as phishing, pharming and smishing are appeared exploiting these advantages. Accordingly in this paper, I propose to prevent social issues like phishing, pharming and smishing for the technical way using mobile hypervisor.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.156-159
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• 2019

The damage from voice phishing reaches one trillion won in the past 5 years following report of Business Korea on August 28, 2018. Voice phishing and mobile phone scams are recognized as a top concern not only in Korea but also in over the world in recent years. In this paper, we propose an efficient system to identify the caller and alert or prevent of dangerous to users. Our system includes a mobile application and web server using client and server architecture. The main purpose of this system is to automatically display the information of unidentified callers when a user receives a call or message. A mobile application installs on a mobile phone to automatically get the caller phone number and send it to the server through web services to verify. The web server applies a machine learning to a global phone book with Blacklist and Whitelist to verify the phone number getting from the mobile application and returns the result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.6139-6160
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• 2018

For ease of use and access, web browsers are now being used to access and modify sensitive data and systems including critical control systems. Due to their computational capabilities and network connectivity, browsers are vulnerable to several types of attacks, even when fully updated. Browsers are also the main target of phishing attacks. Many browser attacks, including phishing, could be prevented or mitigated by using site-, user-, and device-specific security configurations. However, we discovered that all major browsers expose disparate security configuration procedures, option names, values, and semantics. This results in an extremely hard to secure web browsing ecosystem. We analyzed more than a 1000 browser security configuration options in three major browsers and found that only 13 configuration options had syntactic and semantic similarity, while 4 configuration options had semantic similarity, but not syntactic similarity. We: a) describe the results of our in-depth analysis of browser security configuration options; b) demonstrate the complexity of policy-based configuration of web browsers; c) describe a knowledge-based solution that would enable organizations to implement highly-granular and policy-level secure configurations for their information and operational technology browsing infrastructures at the enterprise scale; and d) argue for necessity of developing a common language and semantics for web browser configurations.