Title
A Randomized Watermarking Technique for Detecting Malicious Data Injection Attacks in Heterogeneous Wireless Sensor Networks for Internet of Things Applications.
Abstract
Using Internet of Things (IoT) applications has been a growing trend in the last few years. They have been deployed in several areas of life, including secure and sensitive sectors, such as the military and health. In these sectors, sensory data is the main factor in any decision-making process. This introduces the need to ensure the integrity of data. Secure techniques are needed to detect any data injection attempt before catastrophic effects happen. Sensors have limited computational and power resources. This limitation creates a challenge to design a security mechanism that is both secure and energy-efficient. This work presents a Randomized Watermarking Filtering Scheme (RWFS) for IoT applications that provides en-route filtering to remove any injected data at an early stage of the communication. Filtering injected data is based on a watermark that is generated from the original data and embedded directly in random places throughout the packet's payload. The scheme uses homomorphic encryption techniques to conceal the report's measurement from any adversary. The advantage of homomorphic encryption is that it allows the data to be aggregated and, thus, decreases the packet's size. The results of our proposed scheme prove that it improves the security and energy consumption of the system as it mitigates some of the limitations in the existing works.
Year
DOI
Venue
2018
10.3390/s18124346
SENSORS
Keywords
Field
DocType
Internet of Things (IoT),wireless sensor network (WSN),data integrity,watermark,data injection attack
Digital watermarking,Injection attacks,Internet of Things,Computer network,Electronic engineering,Watermark,Data integrity,Engineering,Wireless sensor network
Journal
Volume
Issue
ISSN
18
12.0
1424-8220
Citations 
PageRank 
References 
0
0.34
18
Authors
3
Name
Order
Citations
PageRank
Arwa Alromih101.01
Mznah Al-Rodhaan230622.90
Yuan Tian3142.25