Energy efficient data aggregation of moving object in Wireless Sensor Networks

Pourpeighambar, Seyed Babak; Aminian, Mehdi; Sabaei, Masoud

doi:10.1109/atnac.2011.6096670

Cited by 8 publications

(5 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…From Equations (2) and (3), it is clearly shown that the energy consumed for data transmission increases as the packet size increases and the square or biquadratic of distance, while the energy consumed for reception is only proportional to the packet size [39].…”

Section: System Models and Assumptionsmentioning

confidence: 99%

A Randomized Watermarking Technique for Detecting Malicious Data Injection Attacks in Heterogeneous Wireless Sensor Networks for Internet of Things Applications

Alromih

Al-Rodhaan

Tian

2018

Sensors

View full text Add to dashboard Cite

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.

show abstract

Section: System Models and Assumptionsmentioning

confidence: 99%

A Randomized Watermarking Technique for Detecting Malicious Data Injection Attacks in Heterogeneous Wireless Sensor Networks for Internet of Things Applications

Alromih

Al-Rodhaan

Tian

2018

Sensors

View full text Add to dashboard Cite

show abstract

“…From equations (2) and (3), it is clearly shown that the energy consumed for data transmission increases as the packet size increase and square or biquadratic of distance, while energy consumed for reception is only proportional to the packet size [26]. In this paper, we consider an adversary model that is similar to the one used in [12,27].…”

Section: Radio Energy Dissipation Modelmentioning

confidence: 99%

A Randomized Watermarking Technique for Detecting Malicious Data Injection Attacks in Heterogeneous Wireless Sensor Networks for Internet of Things Applications

Alromih

Al-Rodhaan

Tian

2018

Preprint

View full text Add to dashboard Cite

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 like 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 get rid of 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 proved that it improves the security and energy consumption of the system as it mitigates some of the limitations in the existing works.

show abstract

“…In our previous work in [2] we have introduced the algorithm for aggregation the FS data model using RD theory named RDAC (Rate Distortion in Aggregation considering Correlation) using spatial correlation. Also, in our previous study [20], we proposed aggregation protocol based on DAMORD mathematical model and evaluated it in various simulation scenarios. Cluster-based aggregation is performed using RD theory with only considering spatial correlation between the data in this study [20].…”

Section: Back Ground and Previous Workmentioning

confidence: 99%

“…Also, in our previous study [20], we proposed aggregation protocol based on DAMORD mathematical model and evaluated it in various simulation scenarios. Cluster-based aggregation is performed using RD theory with only considering spatial correlation between the data in this study [20].…”

Section: Back Ground and Previous Workmentioning

confidence: 99%

DAMORD: an aggregation algorithm for mobile point source using rate‐distortion theory in wireless sensor networks

Aminian

Sabaei

Akbari

2014

Int J Communication

Self Cite

View full text Add to dashboard Cite

By rapid advances in the development of electronic components and with declining cost of sensor network deployment, we are witnessing the amazing growth of these networks. The energy consumption constraints have imposed the importance and necessity of new concepts such as data aggregation. In this paper, a new method is proposed for aggregating the data received from the mobile point source in a sensor network. In this method called DAMORD (Data Aggregation for Mobile Object using Rate-Distortion), by using RD theory and considering spatial and temporal correlation, we can reduce the load of data transmitted to base station with considering the maximum distortion that can be tolerated by the user. To the best of our knowledge, nobody has yet used the RD theory for the data aggregation of mobile object in the sensor networks. A mathematical model followed by detailed model verification demonstrated the efficiency of the proposed method under different conditions.

show abstract

Energy efficient data aggregation of moving object in Wireless Sensor Networks

Cited by 8 publications

References 15 publications

A Randomized Watermarking Technique for Detecting Malicious Data Injection Attacks in Heterogeneous Wireless Sensor Networks for Internet of Things Applications

A Randomized Watermarking Technique for Detecting Malicious Data Injection Attacks in Heterogeneous Wireless Sensor Networks for Internet of Things Applications

A Randomized Watermarking Technique for Detecting Malicious Data Injection Attacks in Heterogeneous Wireless Sensor Networks for Internet of Things Applications

DAMORD: an aggregation algorithm for mobile point source using rate‐distortion theory in wireless sensor networks

Contact Info

Product

Resources

About