TY - CHAP
T1 - 3-Party Adversarial Cryptography
AU - Meraouche, Ishak
AU - Dutta, Sabyasachi
AU - Sakurai, Kouichi
N1 - Funding Information:
Sabyasachi Dutta was financially supported by the National Institute of Information and Communications Technology (NICT), Japan, under the NICT International Invitation Program during his stay at Kyushu University where the initial phase of the research work was carried out.
Funding Information:
Ishak Meraouche is supported by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan for his studies at Kyushu University.
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - The domain of Artificial Intelligence (AI) has seen an outstanding growth during the last two decades. It has proven its efficiency in handling complex domains including speech recognition, image recognition and many more. One interesting and evolving branch that was put forward years ago but have seen a good growth only during the past few years is encryption using AI. After Google announced that it has succeeded teaching neural networks encryption in the presence of Eavesdroppers, research in this particular area has seen a rapid spread of interest among different researchers all over the world to develop new Neural Networks capable of operating different cryptographic tasks. In this paper, we take initial steps to achieve secure communication among more than two parties using neural network based encryption. We forward the idea of two party symmetric encryption scheme of Google to a multi party Encryption scheme. In this paper we will focus on a 3-Party case.
AB - The domain of Artificial Intelligence (AI) has seen an outstanding growth during the last two decades. It has proven its efficiency in handling complex domains including speech recognition, image recognition and many more. One interesting and evolving branch that was put forward years ago but have seen a good growth only during the past few years is encryption using AI. After Google announced that it has succeeded teaching neural networks encryption in the presence of Eavesdroppers, research in this particular area has seen a rapid spread of interest among different researchers all over the world to develop new Neural Networks capable of operating different cryptographic tasks. In this paper, we take initial steps to achieve secure communication among more than two parties using neural network based encryption. We forward the idea of two party symmetric encryption scheme of Google to a multi party Encryption scheme. In this paper we will focus on a 3-Party case.
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U2 - 10.1007/978-3-030-39746-3_27
DO - 10.1007/978-3-030-39746-3_27
M3 - Chapter
AN - SCOPUS:85083454633
T3 - Lecture Notes on Data Engineering and Communications Technologies
SP - 247
EP - 258
BT - Lecture Notes on Data Engineering and Communications Technologies
PB - Springer Science and Business Media Deutschland GmbH
ER -