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An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks.

Pirbhulal S, Zhang H, Mukhopadhyay SC, Li C, Wang Y, Li G, Wu W, Zhang YT - Sensors (Basel) (2015)

Bottom Line: Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc.Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security.However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Shenzhen 518055, China. sandeep@siat.ac.cn.

ABSTRACT
Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.

No MeSH data available.


Related in: MedlinePlus

Amount of data transmission in bits with same percentage of resource utilization for different methods.
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sensors-15-15067-f006: Amount of data transmission in bits with same percentage of resource utilization for different methods.

Mentions: Figure 6 explains that our proposed algorithm can transmit a higher number of bits than PSKA, DES and RSA by using same number of resources due to the use of a simple and efficient key generation mechanism in our proposed algorithm. As complex key generation procedures waste more resources, our proposed algorithm eliminates the need of time consuming and inefficient methods for data authentication in BSN, resulting in low utilization of resources. Hence, it can be stated that our proposed algorithm is a cost effective approach for securing BSN.


An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks.

Pirbhulal S, Zhang H, Mukhopadhyay SC, Li C, Wang Y, Li G, Wu W, Zhang YT - Sensors (Basel) (2015)

Amount of data transmission in bits with same percentage of resource utilization for different methods.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541821&req=5

sensors-15-15067-f006: Amount of data transmission in bits with same percentage of resource utilization for different methods.
Mentions: Figure 6 explains that our proposed algorithm can transmit a higher number of bits than PSKA, DES and RSA by using same number of resources due to the use of a simple and efficient key generation mechanism in our proposed algorithm. As complex key generation procedures waste more resources, our proposed algorithm eliminates the need of time consuming and inefficient methods for data authentication in BSN, resulting in low utilization of resources. Hence, it can be stated that our proposed algorithm is a cost effective approach for securing BSN.

Bottom Line: Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc.Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security.However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Shenzhen 518055, China. sandeep@siat.ac.cn.

ABSTRACT
Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.

No MeSH data available.


Related in: MedlinePlus