Mandal, K. ., Gong, G. ., Fan, X. ., & Aagaard, M. . (2014). Optimal Parameters for the WG Stream Cipher Family. Cryptography and Communications, 6, 117-135. (Original work published 2014)
Reference author: K. Mandal
First name
K.
Last name
Mandal
Altawy, R. ., Rohit, R. ., He, M. ., Mandal, K. ., Yang, G. ., & Gong, G. . (2017). Towards a Cryptographic Minimal Design: The sLiSCP Family of Permutations. To Appear at IEEE Transactions on Computers. CACR Technical Report cacr2017-04, University of Waterloo.
Mandal, K. ., Fan, X. ., & Gong, G. . (2016). Design and Implementation of Warbler Family of Lightweight Pseudorandom Number Generators for Smart Devices. (Original work published 2016)
Mandal, K. ., & Gong, G. . (2016). Feedback Reconstruction and Implementations of Pseudorandom Number Generators from Composited De Bruijn Sequences. IEEE Transactions on Computers, 65, 2725-2738. (Original work published 2016)
Mandal, K. ., & Gong, G. . (2016). Filtering Nonlinear Feedback Shift Registers using Welch-Gong Transformations for Securing RFID Applications. ICST Transactions on Security Safety, 16. (Original work published 2016)
Mandal, K. ., Yang, B. ., Guang, G. ., & Aagaard, M. . (2016). On ideal t-tuple distribution of filtering de. Bruijn sequence generators. Chengdu, China. (Original work published 2016)
Tan, Y. ., Mandal, K. ., Wu, T. ., & Gong, G. . (2016). Security Analysis of TUAK Algorithms for 4G-LTE Authentication and Key Agreement. Waikoloa, Hawaii, USA. (Original work published 2016)
Mandal, K. ., Tan, Y. ., Wu, T. ., & Gong, G. . (2015). A comprehensive security analysis of the TUAK algorithm set. IEEE Transactions on Information Forensics and Security. (Original work published 2015)
Mandal, K. ., & Gong, G. . (2018). On Ideal t-Tuple Distribution of Orthogonal Functions in Filtering De Bruijn Generators. Journal of Advances in Mathematics of Communications. Retrieved from http://cacr.uwaterloo.ca/techreports/2018/cacr2018-09.pdf (Original work published 2018)
Mandal, K. ., Gong, G. ., & Liu, C. . (2018). NIKE-based Fast Privacy-preserving High-dimensional Data Aggregation for Mobile Devices. Submitted to IEEE Transaction on Dependable and Secure Computing, Technical Report, University of Waterloo. (Original work published 2018)