4.5 Article

Fractional chaos based-cryptosystem for generating encryption keys in Ad Hoc networks

期刊

AD HOC NETWORKS
卷 97, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.adhoc.2019.102005

关键词

Cryptosystem; Fractional-order chaotic system; Cipher; Ad Hoc network; IoT; Secure communications; Encryption

资金

  1. CONACyT/MEXICO [258880]
  2. SEP-PRODEP/MEXICO
  3. Laboratory of Characterization of Systems Based on Microwaves at FCEBUAP (CONACyT Infraestructura 2016) [270761]

向作者/读者索取更多资源

Ad Hoc networks are considered essential elements of the Internet of Things (IoT), which is a technological trend for innovative future applications. Since in IoT systems the devices are mostly connected among them, the data exchange is a vital activity in the network. In this kind of networks, not only nonsensitive data exchange is performed, but also sensitive data (digital signatures, login credentials, account numbers, personal images, and so on) are shared. Therefore, new appropriate approaches to encrypt the secret information are highly required. This paper presents an experimental setup of a fractional-chaos based-cryptosystem for ad hoc networks under the IEEE 802.15.4 standard. The proposed cryptosystem is composed of a novel chaotic pairing approach between the coordinator node and end-devices nodes to sending data into the network. More specifically, the RF-data of the IEEE 802.15.4 frame is encrypted using a fractional-order encryption key and four iterative steps. It is worth to note that the chaotic key is based on a fractional-order chaotic system, which is derived from the fractional calculus theory. Fractional-order chaotic dynamics are demonstrated using the Lyapunov method and equilibria stability. Next, the experimental validation of the cryptosystem is shown sending an encrypted image between ARM digital platforms and wireless Xbee modules. Several security analyses indicate the proposed encryption scheme has suitable statistical properties, sizeable keyspace, and high sensitivity providing secure communications. (C) 2019 Elsevier B.V. All rights reserved.

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