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Optimized fuzzy logic by Genetic algorithm for identifying the situation of social network users
seyyed mohammad safi
Sharif University of Technology
Corresponding Author
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Today, mobile social networks and smartphones are highly developed and widely used. Owing to the transfer of vast amounts of data, information, and communication between users, such networks have addressed privacy as a fundamental issue. Recently, there has been a growing interest in identifying the privacy requirements of each user to act independently and dynamically according to the situations and conditions. This paper seeks to meet the privacy requirements of users by identifying their situation. For this purpose, we define a number of significant parameters in compliance with the conditions of users. Also, after inferring the current exact situation of the user, the fuzzy logic is automatically utilized to specify the privacy settings based on the conditions. To increase the accuracy in the identification of user situation, this method employs the genetic algorithm for selecting the coefficients of optimal input parameters in the fuzzy system. In this way, the fuzzy system is able to make a more accurate identification of the user situation. Compared to a similar method, the proposed method shows a better accuracy in identifying the user situation and, as a result, better performance in correctly setting the privacy.
Keywords
mobile social networks, identify situation, fuzzy logic, privacy, genetic algorithm
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This preprint is under consideration at EURASIP Journal on Wireless Communications and Networking. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Optimized fuzzy logic by Genetic algorithm for identifying the situation of social network users
seyyed mohammad safi
Sharif University of Technology
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 31 Dec, 2020
No community comments so far
Editor assigned
On 12 Dec, 2020
Submission checks complete
On 12 Dec, 2020
Editor invited
On 12 Dec, 2020
First submitted
On 09 Dec, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Systems and Networking
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Today, mobile social networks and smartphones are highly developed and widely used. Owing to the transfer of vast amounts of data, information, and communication between users, such networks have addressed privacy as a fundamental issue. Recently, there has been a growing interest in identifying the privacy requirements of each user to act independently and dynamically according to the situations and conditions. This paper seeks to meet the privacy requirements of users by identifying their situation. For this purpose, we define a number of significant parameters in compliance with the conditions of users. Also, after inferring the current exact situation of the user, the fuzzy logic is automatically utilized to specify the privacy settings based on the conditions. To increase the accuracy in the identification of user situation, this method employs the genetic algorithm for selecting the coefficients of optimal input parameters in the fuzzy system. In this way, the fuzzy system is able to make a more accurate identification of the user situation. Compared to a similar method, the proposed method shows a better accuracy in identifying the user situation and, as a result, better performance in correctly setting the privacy.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.