Security‐aware authorization and verification based data aggregation model for wireless sensor networks

Abstract

In Wireless Sensor Network (WSN), the sensor nodes aggregate the environment and transmit the aggregated data to the Cluster Head (CH) or aggregator. Even though various data aggregation model is introduced, the resourceconstrained issues in WSN are complex to solve in the research community. Therefore, the authorization and verification-based data aggregation model is proposed in this research to perform the secure data transmission. The proposed network model contains three functioning blocks, such as sensor nodes, aggregators, and data centers, respectively. The proposed data aggregation model involves five different phases, setup and key generation phase, signing, verification, authorization, and data aggregation phase. The sensor node creates the ID and private key to perform the data communication between the Cluster Head and data center. The data center generates the control message and transfers the message to CH and the sensor node. Finally, the data aggregation is carried out using the trimodel Least Mean Square (LMS) filter to achieve the data aggregation in WSN. Moreover, the proposed authorization and verification-based data aggregation model obtained a lower prediction error of 0.0526 and consumed higher energy of 0.5567 J with the computational and the communication cost as 0.008 second, and 0.0139 second, respectively.

Traffic aware cyclic sleep‐based power consumption model for a passive optical network

“…The network modeling is an important tool to assess the performance of a network process or network node in the presence of traffic load and the process tuning parameters such as references 13,14, In PON, also many studies have tried to model the power consumption and the traffic arrival process of the ONU using different approaches such as component‐based power modeling, 15 queuing theory, 16 discrete‐time Markov chain (DTMC), 17,18 and semi‐Markov chain 19 . The first approach only considers the power consumption of different ONU components and is not much affective.…”

“…Using the stationary distribution given in Equations ( 7) to (10) and the fact that P 4 i¼1 u i is always 1 the system of equation is solved to obtain the steady-state probability distribution for each state in Equations ( 11) to (14).…”

An optimized novel public cloud system to secure the medical record from third parties

“…Digital communication has become a crucial aspect in modern life 1 ; however, security plays a significant role in broadcasting the data 2 . Hence, cryptography is the familiar aspect of the cloud model to protect medical data against harmful attacks 3 .…”

“…Digital communication has become a crucial aspect in modern life 1 ; however, security plays a significant role in broadcasting the data. 2 Hence, cryptography is the familiar aspect of the cloud model to protect medical data against harmful attacks. 3 However, this model has met several problems because of the crypto algorithm's extensive data and slow key generation model.…”

“…7 However, security is the primary concern for carrying on medical services through the wireless environment. 8 This key generation concept can avoid Symbols and Abbreviations: DL, Deep learning; ML, Machine learning; IoT, Internet of Things; ABIDE, African buffalo-based International Data Encryption; CS, Cloud server; MRI, Magnetic resonance imaging; ABO, African buffalo optimization; IDE, International data encryption; SA-DS, Secure Authentication based data sharing; MWO, Modified whale optimization; a m n , General symptoms for each disease; n, Cloud database parameter; d p , The particular disease of the affected patient; z (1) 1 , z (2) 2 , z (3) 3 , z (4) 4 , Encryption process; h ′ , Hash function of the public cloud system; h d , Healthcare data card of the patient; r ′ , Randomly selected value; S ′ n , Medical data record; 𝛽 ′ , Actual healthcare information; 𝛼 ′ , Collected healthcare information; a ′ d , c ′ d , Healthcare information from the cloud database; P k+1 , Exploitation performance; e k , User detail; lg 1 F I G U R E 1 Public cryptosystem the third person in the cloud environment by locking the user details. 9 Hence, the closed details are only visible to the medical specialist who can have authenticated access.…”