• Journal of Positioning, Navigation, and Timing
• /
• v.9 no.3
• /
• pp.215-220
• /
• 2020

This paper deal with estimating the direction of arrival (DOA) of GNSS signal using two antennae for spoofing detection. A technique for estimating the azimuth angle of a received signal by applying the interferometer method to the GPS carrier signal is proposed. The experiment assumes two antennas placed on the earth's surface and estimates the azimuth angle when only GPS signal are received without spoofing signal. The proposed method confirmed the availability through GPS satellite placement simulation and experiments using a dual antenna GPS receiver. In this case of using dual antenna, an azimuth angle ambiguity of the received signal occurs with respect to the baseline between two antennas. For this reason, the accurate azimuth angle estimation is limits, but it can be used for deception by cross-validating the ambiguity.

• Journal of Positioning, Navigation, and Timing
• /
• v.7 no.3
• /
• pp.139-146
• /
• 2018

In recent years, a satellite navigation signal authentication technique has been introduced to determine the spoofing of commercial C/A code using the cross-correlation mode of GPS P(Y) code received at two receivers. This paper discusses the technical considerations in the implementation and application of authentication system simulator hardware to achieve the above technique. The configuration of the simulator consists of authentication system and user receiver. The synchronization of GPS signals received at two devices, data transmission and reception, and codeless correlation of P(Y) code were implemented. The simulation test result verified that spoofing detection using P(Y) codeless correlation could be achieved.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.2B
• /
• pp.118-123
• /
• 2007

This paper studied the transmission control protocol over IP network to enhance the performance of the GSO satellite communication networks. The focus of this study is how to reduce the long round trip time and the transmission data rates over satellite link in the bidirectional satellite network. To do it, this study applied the caching and spoofing technology. The spoofing technology is used to reduce the required time for the link connection during communication. The caching technology is to improve the transmission bandwidth efficiency in the high transmission data rate link The tests and measurements in this study was performed in the commercial GSO communication satellite network and the terrestrial Internet network. The results of this paper show that the studied protocol in this paper highly enhance the performance of the bidirectional satellite communication network compare to the using TCP/IP satellite network protocol.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.2
• /
• pp.187-194
• /
• 2021

This paper presents a margin-based face liveness detection method with behavioral confirmation to prevent spoofing attacks using deep learning techniques. The proposed method provides a possibility to prevent biometric person authentication systems from replay and printed spoofing attacks. For this work, a set of real face images and fake face images was collected and a face liveness detection model is trained on the constructed dataset. Traditional face liveness detection methods exploit the face image covering only the face regions of the human head image. However, outside of this region of interest (ROI) might include useful features such as phone edges and fingers. The proposed face liveness detection method was experimentally tested on the author's own dataset. Collected databases are trained and experimental results show that the trained model distinguishes real face images and fake images correctly.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2009.04a
• /
• pp.1482-1485
• /
• 2009

DDoS 공격은 네트워크 보안에 큰 피해를 미치는 공격기법의 하나로써, 국내외로 많은 피해를 유발하고 있으며, 최근에도 DDoS 공격에 의한 피해는 빈번하게 보고되고 있다. DDoS 공격은 실제 공격에 앞서 웜과 악성 BOT을 이용하여 공격을 직접 수행할 호스트를 감염시킨다. 웜과 악성 BOT이 타깃 호스트를 감염시키기 전에 반드시 수행하는 것이 취약점에 대한 스캐닝이다. 본 논문에서는 웜과 악성 BOT의 스캐닝 행위에 초점을 맞추어 DDoS 공격으로부터 안전한 네트워크를 구축하기 위한 역 IP spoofing을 이용한 DDoS 웜 스캐닝 트래픽의 처리기법을 제안한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.11a
• /
• pp.651-654
• /
• 2021

Face anti-spoofing (FAS) techniques play a significant role in the defense of facial recognition systems against spoofing attacks. Existing FAS methods achieve the great performance depending on annotated additional modalities. However, labeling these high-cost modalities need a lot of manpower, device resources and time. In this work, we proposed to use self-transforming modalities instead the annotated modalities. Three different modalities based on frequency domain and temporal domain are applied and analyzed. Intuitive visualization analysis shows the advantages of each modality. Comprehensive experiments in both the CNN-based and transformer-based architecture with various modalities combination demonstrate that self-transforming modalities improve the vanilla network a lot. The codes are available at https://github.com/chenmou0410/FAS-Challenge2021.

• Proceedings of the Korean Information Science Society Conference
• /
• 2010.06a
• /
• pp.7-8
• /
• 2010

• Convergence Security Journal
• /
• v.16 no.7
• /
• pp.21-29
• /
• 2016

Our society is currently exposed to environment of various information that is exchanged real time through networks. Especially regarding medical policy, the government rushes to practice remote medical treatment to improve the quality of medical services for citizens. The remote medical practice requires establishment of medical information based on big data for customized treatment regardless of where patients are. This study suggests establishment of regional medical cluster along with defense and protection cooperation models that in case service availability is harmed, and attacks occur, the attacks can be detected, and proper measures can be taken. For this, the study suggested forming networks with nationwide local government hospitals as regional virtual medical cluster bases by the same medical information system. The study also designed a mutual cooperation security model that can real time cope with IP Spoofing attack that can occur in the medical cluster and DDoS attacks accordingly, so that the limit that sole system and sole security policy have can be overcome.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.5
• /
• pp.1726-1743
• /
• 2014

DDoS (Distributed Denial of Service) has been a continuous threat to the cyber world with the growth in cyber technology. This technical evolution has given rise to a number of ultra-sophisticated ways for the attackers to perform their DDoS attack. In general, the attackers who generate the denial of service, use the vulnerabilities of the TCP. Some of the vulnerabilities like SYN (synchronization) flooding, and IP spoofing are used by the attacker to create these Distributed Reflected Denial of Service (DrDoS) attacks. An attacker, with the assistance of IP spoofing creates a number of attack packets, which reflects the flooded packets to an attacker's intended victim system, known as the primary target. The proposed scheme, Efficient Spoofed Flooding Defense (ESFD) provides two level checks which, consist of probing and non-repudiation, before allocating a service to the clients. The probing is used to determine the availability of the requested client. Non-repudiation is taken care of by the timestamp enabled in the packet, which is our major contribution. The real time experimental results showed the efficiency of our proposed ESFD scheme, by increasing the performance of the CPU up to 40%, the memory up to 52% and the network bandwidth up to 67%. This proves the fact that the proposed ESFD scheme is fast and efficient, negating the impact on the network, victim and primary target.

• Journal of Broadcast Engineering
• /
• v.24 no.6
• /
• pp.1113-1121
• /
• 2019

In this paper, we propose the face anti-spoofing method based on combination of luminance and chrominance with convolutional neural networks. The proposed method extracts luminance and chrominance features independently from live and fake faces by using stacked convolutional neural networks and auxiliary networks. Unlike previous methods, an attention module has been adopted to adaptively combine extracted features instead of simply concatenating them. In addition, we propose a new loss function, called the contrast loss, to learn the classifier more efficiently. Specifically, the contrast loss improves the discriminative power of the features by maximizing the distance of the inter-class features while minimizing that of the intra-class features. Experimental results demonstrate that our method achieves the significant improvement for face anti-spoofing compared to existing methods.