• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.449-460
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• 2021

ASVspoof 2017 deals with detection of replay attacks and aims to classify real human voices and fake voices. The spoofed voice refers to the voice that reproduces the original voice by different types of microphones and speakers. data augmentation research on image data has been actively conducted, and several studies have been conducted to attempt data augmentation on voice. However, there are not many attempts to augment data for voice replay attacks, so this paper explores how audio modification through data augmentation techniques affects the detection of replay attacks. A total of 7 data augmentation techniques were applied, and among them, dynamic value change (DVC) and pitch techniques helped improve performance. DVC and pitch showed an improvement of about 8% of the base model EER, and DVC in particular showed noticeable improvement in accuracy in some environments among 57 replay configurations. The greatest increase was achieved in RC53, and DVC led to an approximately 45% improvement in base model accuracy. The high-end recording and playback devices that were previously difficult to detect were well identified. Based on this study, we found that the DVC and pitch data augmentation techniques are helpful in improving performance in the voice spoofing detection problem.

• ETRI Journal
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• v.36 no.5
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• pp.865-875
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• 2014

Voice phishing (vishing) uses social engineering, based on people's trust in telephone services, to trick people into divulging financial data or transferring money to a scammer. In a vishing attack, a scammer often modifies the telephone number that appears on the victim's phone to mislead the victim into believing that the phone call is coming from a trusted source, since people typically judge a caller's legitimacy by the displayed phone number. We propose a system named iVisher for detecting a concealed incoming number (that is, caller ID) in Session Initiation Protocol-based Voice-over-Internet Protocol initiated phone calls. Our results demonstrate that iVisher is capable of detecting a concealed caller ID without significantly impacting upon the overall call setup time.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06d
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• pp.215-218
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• 2011

VoIP(Voice over Internet Protocol) 서비스는 기존의 음성전화 서비스(Public Switched Telephone Network, PSTN)와 달리 IP 프로토콜을 이용한 저렴한 통신비용 등의 장점이 있는 음성통신 기술로써, 기존의 아날로그 음성전화 서비스를 대신하는 서비스이며, 새로운 인터넷 융합서비스로 많은 사용자가 이용하고 있다. 하지만 VoIP 서비스가 인터넷망을 이용함으로 IP Spoofing, DoS (Denial of Server) / DDoS(Distributed Denial of Service), 등의 여러 가지 보안의 문제점을 가지고 있다. VoIP 서비스에서 DDoS 공격은 Proxy 서버 등에 대량의 공격 메시지를 보냄으로써 서버의 자원을 고갈시켜 정상적인 서비스를 하지 못하게 한다. DoS, DDoS 공격 중 Invite Flooding 공격은 1분에 수천 개의 Invite 메시지를 보내 회선의 자원을 고갈시키는 공격이다. 특히 IP/Port 위조하여 공격 경우 공격 패킷 탐지하기 어려우므로 차단할 수 없다. 따라서 본 논문에서는 VoIP의 DoS/DDoS 중 하나인 Invite Flooding 공격 시 SIP Proxy Server에서 메시지 분산시키는 방법과 MAC Address와 사용자 번호 등 IP 이외의 고정적인 사용자 정보를 확인하여 공격을 탐지하고, 공격 Agent에 감염된 Phone을 공격차단서비스로 보내 복구시키는 방법을 제안한다.