Power Efficient Data Fusion Assurance Scheme for Sensor Network Using Silent Negative Voting

Abstract

Security is a very important issue when designing or deploying any network or protocol. The nature of large, ad-hoc, wireless sensor networks presents significant challenges in designing security schemes. One or several sensors then collect the detection results from other sensors. The collected data must be processed by the sensor to reduce the transmission burden before they are transmitted to the base station. This process is called data fusion. Data fusion Nodes will fuses the collected data from nearby sensor nodes before they are sent to the base station. If a fusion node is compromised, then the base station cannot ensure the correctness of the fusion data sent to it. Various methods are proposed, that deal with providing an assured data transfer to the Base Station.In this paper a novel power-efficient data fusion assurance scheme has been proposed using silent negative voting mechanism. The proposed scheme has been compared with the direct voting based fusion assurance scheme. The proposed scheme produced very well with better power efficiency and lower network overhead.

A multi-level study for trust management models assessment in VANETs

“…Multiple techniques for DFT assessment were adopted in the literature mainly the: beta distribution (Sharma et al, 2016), witnesses (Du et al, 2003) and heuristics (Hall and McMullen, 2004;Suciu et al, 2015) as depicted in Table 4. Du et al (2003), Pai and Han (2008) as well as Umashankar and Chandrasekar (2010) were based on witnesses' personal opinions for data fusion result's verification in WSNs. They assumed that the fusion result should be aproved by multiple witnesses.…”

“…They assumed that the fusion result should be aproved by multiple witnesses. Pai and Han (2008) assumed that a witness may only vote by agree or disagree while Umashankar and Chandrasekar (2010) supposed that witnesses should only vote when an erroneous result is detected. The aim of the authors is to reduce the system's overhead by reducing the number of transmitted messages.…”

“…This solution requires a high communication overhead to forward all of the proofs. Nonethless, Pai and Han (2008) and Umashankar and Chandrasekar (2010) assumed that only one valid copy should be transmitted to the base station whenever the fusion node misbehaves. Pai and Han (2008) supposed that witnesses vote by agree or disagree whereas Umashankar and Chandrasekar (2010) suggested that they keep silent until they detect a weird result in order to reduce the communication overhead compared with Du et al (2003) and Pai and Han (2008).…”

Internet-of-Things and Information Fusion: Trust Perspective Survey

“…Multiple information sources such as sensors generate information which is collected by sink node(s), where the information fusion processes take place. These processes may include transformation, reduction, integration, or replacement [8,14,15,16]. Finally, an output is generated that is hopefully more useful than that provided by any individual information source.…”

“…Information fusion phases can be applied on sensors-generated information to ensure data reliability [8,14,15,16]. Information fusion techniques can combine data from multiple data sources to increase data reliability.…”