Lightweight and privacy-preserving agent data transmission for mobile Healthcare

Author(s):  
Shunrong Jiang ◽  
Xiaoyan Zhu ◽  
Ripei Hao ◽  
Haotian Chi ◽  
Hui Li ◽  
...  
2019 ◽  
Vol 162 ◽  
pp. 106866 ◽  
Author(s):  
Rihab Boussada ◽  
Balkis Hamdane ◽  
Mohamed Elhoucine Elhdhili ◽  
Leila Azouz Saidane

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1358 ◽  
Author(s):  
Gyanendra Prasad Joshi ◽  
Eswaran Perumal ◽  
K. Shankar ◽  
Usman Tariq ◽  
Tariq Ahmad ◽  
...  

In recent times, vehicular ad hoc networks (VANET) have become a core part of intelligent transportation systems (ITSs), which aim to achieve continual Internet connectivity among vehicles on the road. The VANET has been used to improve driving safety and construct an ITS in modern cities. However, owing to the wireless characteristics, the message transmitted through the network can be observed, altered, or forged. Since driving safety is a major part of VANET, the security and privacy of these messages must be preserved. Therefore, this paper introduces an efficient privacy-preserving data transmission architecture that makes use of blockchain technology in cluster-based VANET. The cluster-based VANET architecture is used to achieve load balancing and minimize overhead in the network, where the clustering process is performed using the rainfall optimization algorithm (ROA). The ROA-based clustering with blockchain-based data transmission, called a ROAC-B technique, initially clusters the vehicles, and communication takes place via blockchain technology. A sequence of experiments was conducted to ensure the superiority of the ROAC-B technique, and several aspects of the results were considered. The simulation outcome showed that the ROAC-B technique is superior to other techniques in terms of packet delivery ratio (PDR), end to end (ETE) delay, throughput, and cluster size.


IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 87169-87177
Author(s):  
Xiaoshuai Zhang ◽  
Chao Liu ◽  
Stefan Poslad ◽  
Kok Keong Chai

Author(s):  
Pooja Gupta ◽  
Ashish Kumar

The paper proposes a framework to improve the privacy preserving data mining. The approach adopted provides security at both the ends i.e. at the data transmission time as well as in the data mining process using two phases. The secure data transmission is handled using elliptic curve cryptography (ECC) and the privacy is preserved using k-anonymity. The proposed framework ensures highly secure environment. We observed that the framework outperforms other approaches [8] discussed in the literature at both ends i.e. at security and privacy of data. Since most of the approaches have considered either secure transmission or privacy preserving data mining but very few have considered both. We have used WEKA 3.6.9 for experimentation and analysis of our approach. We have also analyzed the case of k-anonymity when the numbers of records in a group are less than k (hiding factor) by inserting fake records. The obtained results have shown the pattern that the insertion of fake records leads to more accuracy as compared to full suppression of records. Since, full suppression may hide important information in cases where records are less than k, on the other hand in the process of fake records insertion; records are available even if number of records in a group is less than k.


2021 ◽  
Vol 15 (1) ◽  
pp. 1-23
Author(s):  
Peng Li ◽  
Chao Xu ◽  
He Xu

In order to solve the problem that the privacy preserving algorithm based on slicing technology is incapable of dealing with packet loss, this paper presents the redundancy algorithm for privacy preserving. The algorithm guarantees privacy by combining disturbance data and ensures redundancy via carrying hidden data. It also selects the routing tree that is generated by the CTP protocol as the routing path for data transmission. Through division at the source node, the method adds hidden information and disturbance data. This algorithm uses hidden data and adds perturbation data to improve the privacy preserving. Nonetheless, it can restore the original data when data are partly lost. According to the simulation via TOSSIM (TinyOS simulator), in the case of partial packet loss, the algorithm can completely restore the original data. Furthermore, the authors compared accuracy of proposed algorithm, probability of data reduction, data fitting degree, communication overhead, and PLR. As a result, it improves the reliability and privacy of data transmission while ensuring data redundancy.


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