Paper Info
Title
Light-Weight Security and Data Provenance for Multi-Hop Internet of Things.
Abstract
Due to the limited resources and scalability, the security protocols for the Internet of Things (IoT) need to be light-weighted. The cryptographic solutions are not feasible to apply on small and low-energy devices of IoT because of their energy and space limitations. In this paper, a light-weight protocol to secure the data and achieving data provenance is presented for the multi-hop IoT network. The Received Signal Strength Indicator (RSSI) of communicating IoT nodes are used to generate the link fingerprints. The link fingerprints are matched at the server to compute the correlation coefficient. Higher the value of correlation coefficient, higher the percentage of the secured data transfers. Lower value gives the detection of adversarial node in between a specific link. Data provenance has also been achieved by comparison of packet header with all the available link fingerprints at the server. The time complexity is computed at the node and server level, which is O(1). The energy dissipation is calculated for the IoT nodes and overall network. The results show that the energy consumption of the system presented in this paper is 52-53 mJ for each IoT node and 313.626 mJ for the entire network. The RSSI values are taken in real time from MICAz motes and simulations are performed on MATLAB for adversarial node detection, data provenance, and time-complexity. Experimental results show that up to 97% correlation is achieved when no adversarial node is present in the IoT network.
Year
DOI
Venue
2018
10.1109/ACCESS.2018.2850821
IEEE ACCESS
Keywords
Field
DocType
IoT,link-fingerprints,light-weight,provenance,security,multi-hop
Authentication,Cryptographic protocol,Computer science,Cryptography,Server,Computer network,Header,Time complexity,Energy consumption,Scalability
Journal
Volume
ISSN
Citations 
6
2169-3536
1
PageRank 
References 
Authors
0.48
0
2
Name
Order
Citations
PageRank
Mohsin Kamal182.59
Muhammad Tariq23912.56