References
- Daniel Bilar "Opcodes as predictor for malware" Int. J. Electronic Security and Digital Forensic, 1(2), 2007.
- Dahl, George E., et al. "Large-scale malware classification using random projections and neural networks." 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2013.
- R.F. Nogueira, R. de Alencar Lotufo and R.C. Machado, "Fingerprint Liveness Detection Using Convolutional Neural Networks," IEEE Transactions on Information Forensics and Security, vol. 11, no. 6, pp. 1206-1213, 2016. https://doi.org/10.1109/TIFS.2016.2520880
- 김원진, 이경수, 박은수, 김정민, 김학일 (2016). Convolutional Neural Networks 특징을 이용한 지문 이미지의 위조여부 판별 및 시각화. 정보보호학회논문지, 26(5), 1259-1267. https://doi.org/10.13089/JKIISC.2016.26.5.1259
- 남승수, 서창호, 최대선 (2016). 모바일환경에서 위조서명에 강건한 딥러닝 기반의 핑거서명검증 연구. 정보보호학 회논문지, 26(5), 1161-1170.
- 홍성은, 임우빈, 박준우, 양현승 (2016). 얼굴과 의복 정보를 활용한 딥러닝 기반 신원인식. 대한전자공학회 학술대회, 2204-2207.
- David Umphress and Glen Williams. Identity verification through keyboard characteristics. International Journal of Man-Machine Studies, 23(3):263. 273, 1985.
- Zheng, Nan, et al., You are how you touch: User verification on smartphones via tapping behaviors, Network Protocols (ICNP), 2014 IEEE 22nd International Conference on. IEEE, 2014.
- Yinlong Qian, et al, "Deep Learning for Steganalysis via Convolutional Neural Networks", Proceedings of SPIE Media Watermarking, Security, and Forensics, vol. 9409, 2015.
- Lionel Pibre et al. "Deep learning is a good steganalysis tool when embedding key is reused for different images, even if there is a cover sourcemismatch", Proceedings of Media Watermarking, Security, and Forensics, 2016.
- 김현재, 이재구, 김규완, 백상현, 윤성로 (2016). 딥러닝을 이용한 범용적 스테그아날리시스. 한국 정보과학회 학술발표논문집, 1004-1006.
- OneM2M Alliance, "Onem2m: Standards for m2m and the internet of things.", 2014.
- OIC, "IoTivity 1.1.1", 2016
- Linyi Tian, "Lightweight m2m (oma lwm2m)." OMA device management working group (OMA DM WG), Open Mobile Alliance, 2012.