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ISSN 1004-9037
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Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
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      30 November 2020, Volume 35 Issue 6   
    Article

    1. ANALYSIS OF SPAM IDENTIFICATION USING ARTIFICIAL INTELLIGENCE
    Vijay kumar1, Pratik Ranjan2, Abha kumari3, Raj Anwit4
    Journal of Data Acquisition and Processing, 2020, 35 (6): 1551-1556 . 

    Abstract

    There has been a correlation between security concerns and the rise of the artificial intelligence industry. Given its propensity to mine huge data for insights, In the domains of spam, machine learning has become widely used, fraud, and malicious file identification. Malicious attackers, on the other hand, have a strong incentive to avoid these techniques. Attackers are limited to using a "black box" assault because they don't know the exact details of the machine type. This study presents an overview of machine learning-based spam detection techniques for Internet of Things devices.

    Keyword

    Spam, Machine, IOT, Detection, Security, AI.


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ISSN 1004-9037

         

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