stdClass Object
(
    [id] => 17086
    [paper_index] => 202507-02-023209
    [title] => AI-POWERED PHISHING DETECTION: A NEW APPROACH FOR EMAIL SECURITY
    [description] => 
    [author] => Rishabh Sharma, Dr. Tapsi Nagpal
    [googlescholar] => 
    [doi] => 
    [year] => 2025
    [month] => July
    [volume] => 10
    [issue] => 7
    [file] => fm/jpanel/upload/2025/July/202507-02-023209.pdf
    [abstract] => Phishing continues to be a critical threat to email security, exploiting human vulnerabilities and bypassing traditional detection systems. This paper presents an AI-powered solution leveraging machine learning and NLP to analyze email content and metadata for phishing indicators. We introduce Cyri, a local-processing conversational assistant that detects semantic cues such as urgency, threats, and emotional manipulation. Cyri’s integration with email clients ensures real-time, privacy-preserving analysis. Experiments demonstrate improved detection accuracy and user comprehension, offering a practical, scalable advancement in phishing defense.
    [keywords] => Phishing, Artificial Intelligence, Machine Learning, NLP, Semantic Features, Email Security.
    [doj] => 2025-07-23
    [hit] => 
    [status] => 
    [award_status] => P
    [orderr] => 41
    [journal_id] => 2
    [googlesearch_link] => 
    [edit_on] => 
    [is_status] => 1
    [journalname] => EPRA International Journal of Research & Development (IJRD)
    [short_code] => IJSR
    [eissn] =>  2455-7838 (Online)
    [pissn] => - -
    [home_page_wrapper] => images/products_image/2-n.png
)
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