Chaos Theory on Generative Adversarial Networks for Encryption and Decryption of Data

被引：9

作者：

Purswani, Juhi ^{[1
]}

Rajagopal, Rajesh ^{[1
]}

Khandelwal, Riya ^{[1
]}

Singh, Anuraj ^{[1
]}

机构：

[1] Atal Bihari Vajpayee Indian Inst Informat Technol, Gwalior 474001, Madhya Pradesh, India

来源：

ADVANCES IN BIOINFORMATICS, MULTIMEDIA, AND ELECTRONICS CIRCUITS AND SIGNALS | 2020年 / 1064卷

关键词：

Cryptography; Generative adversarial networks; Neural networks; Chaotic maps; Security; Keras; Pseudo-random number generator;

D O I：

10.1007/978-981-15-0339-9_20

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Today's world involves sharing a tremendous amount of vital information and data over the web and cloud for almost everything. Any hacker or cyber-terrorist can get access to the data and hence the security of the data becomes extremely essential. Through this research, the possibilities of improving the cryptosystem has been explored by making use of generative adversarial networks in which our own shared key, which is generated with the help of chaotic generator has been incorporated. The key formed leads to the increase in randomness which in turn makes it even more difficult to crack it, thus making the system even more secure.

引用

页码：251 / 260

页数：10

共 12 条

[1]

Abadi M., 2016, GOOGLE BRAIN

[2] A symmetric image encryption scheme based on combination of nonlinear chaotic maps [J].

Akhavan, A. ;

Samsudin, A. ;

Akhshani, A. .

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2011, 348 (08) :1797-1813

[3]

Arvandi M., 2006, INT JOINT C NEUR NET, V21

[4]

Chauhan M., 2014, INT J SCI ENG RES, V5

[5]

Fridrich J., INT J BIFURC CHAOS

[6]

Godhavari T., 2005, IEEE IND 2005 C CHEN

[7]

Graepel T., 2013, CONFIDENTIAL MACHINE

[8]

Kanso A., 2007, LOGISTIC MAPS BINARY

[9]

Suneel M., 2009, CRYPTOGRAPHIC PSEUDO

[10]

Volna E., 2005, CRYPTOGRAPHY BASED N

← 1 2 →