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A Novel Security Algorithm RPBB31 for Securing the Social Media Analyzed Data using Machine Learning Algorithms

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Abstract

The present world data is most important in public because without data cannot live in the world. This data is big data and that data daily increases through Social Media like “Twitter, Facebook, Youtube, WhatsApp, Instagram, LinkedIn”, etc.., because this media only share public opinion very fast through the net. From this media, more people used especially Twitter. Thus media are used to analyze the public opinion of the tweets and predict the future through Machine Learning Algorithm. This analyzed data should make it polarity score. This score data has very little security because, this score can change the score and affected the future, so apply the existing security algorithms is Salsa and ChaCha. The Salsa algorithm is diagonal values moved to the first row. The ChaCha algorithm is diagonal values moved to the first column. The existing algorithms do not have good security because they focused only on performance, not security. So, the novel security algorithm is RPBB31. This algorithm has seven stages. The 1st stage is to find the secret key N, n, and p values from the matrix. The 2nd stage is to apply the secret key in PN(n) operation. The 3rd stage operation of PN(n) up to n = 1. The 4th stage is all PN(n) operations make their single line. The 5th stage is to pair the values and swap the values in the matrix. The 6th stage is column operations in the matrix. The 7th stage is again Step 4 values used to swap but “0th" cell value start from reverse in the matrix. In world cricket is the most famous game. In all social media Millions of people are following in different manner, especially in indian cricketer are more famous in India and world. In some point of time it may lead to match fixing, betting. To overcome this kind of issue the four datasets chosen. The proposed algorithm has provide good security and performance while compare to existing algorithms.

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Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

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Funding

There was no financial support received from any organization for carrying out this work.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Kommuri Pratap Reddy Institute of Technology, Ghanpur Village, Ghatkesar (M), Malkajigirl Dist., Hyderabad, Telangana, India

    Bagath Basha Chan Batcha

  2. Department of Computer Science and Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Mission’s Research Foundation (Deemed to Be University), Paiyanoor, Chengalpattu District, Tamil Nadu, India

    Rajaprakash Singaravelu

  3. Department of Electrical and Electronics Engineering, Kongu Engineering College (Autonomous), Perundurai, Erode, Tamil Nadu, India

    Meenakumari Ramachandran

  4. Department of Electronics and Communication Engineering, Kongu Engineering College (Autonomous), Perundurai, Erode, Tamil Nadu, India

    Suresh Muthusamy

  5. Department of Mechanical Engineering, Government Engineering College, Patan, Gujarat, India

    Hitesh Panchal

  6. Department of Electrical and Electronics Engineering, Sri Krishna College of Engineering and Technology (Autonomous), Coimbatore, Tamil Nadu, India

    Kokilavani Thangaraj

  7. Department of Electrical and Electronics Engineering, Bannari Amman Institute of Technology (Autonomous), Sathyamangalam, Erode, Tamil Nadu, India

    Ashokkumar Ravindaran

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  1. Bagath Basha Chan Batcha
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  2. Rajaprakash Singaravelu
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  3. Meenakumari Ramachandran
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  4. Suresh Muthusamy
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  5. Hitesh Panchal
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  6. Kokilavani Thangaraj
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  7. Ashokkumar Ravindaran
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Contributions

BBCB: Drafting the manuscript. RS: Drafting the manuscript. MR: Supervision. SM: Supervision. HP: Assisting in drafting the manuscript. KT: project administration. AR: project administration.

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Correspondence to Suresh Muthusamy.

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The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. To the best of my knowledge and belief any actual, perceived or potential conflicts between my duties as an employee and my private and/or business interests have been fully disclosed in this form in accordance with the requirements of the journal.

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Batcha, B.B.C., Singaravelu, R., Ramachandran, M. et al. A Novel Security Algorithm RPBB31 for Securing the Social Media Analyzed Data using Machine Learning Algorithms. Wireless Pers Commun 131, 581–608 (2023). https://doi.org/10.1007/s11277-023-10446-9

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