Dr. Niddal Hassan Imam

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Niddal Hassan imam

Niddal Imam has a PhD degree from The University of York Department of Computer Science (Cybersecurity). His research area of interest is focusing on the intersection between security and Machine Learning and cyber attacks in social media platforms. He has been working on designing adversary-aware, ML-based detectors of Twitter spam. Methods and techniques used in his research are based on Deep Learning (e.g., OCRs), Convolutional Recurrent Neural Networks (e.g. LSTM), and Text classification techniques (e.g., NLPs). Also, he has a master’s degree in computer and network security. Also, he has several technical certificates in cybersecurity and networks

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OCR post-correction for detecting adversarial text images

Journal Article Tue, 10/11/2022 - 10:44,
OCR post-correction for detecting adversarial text images. (2022). OCR post-correction for detecting adversarial text images. Journal Of Information Security And Applications 66, 103170, 2022.

An Empirical Analysis of Health-Related Campaigns on Twitter Arabic Hashtags

Journal Article Tue, 10/11/2022 - 10:44,
An Empirical Analysis of Health-Related Campaigns on Twitter Arabic Hashtags. (2022). An Empirical Analysis of Health-Related Campaigns on Twitter Arabic Hashtags. 2022 7Th International Conference On Data Science And Machine Learning …, 2022.

Adversary-Aware, Machine Learning-based Detection of Spam in Twitter Hashtags

Journal Article Tue, 10/11/2022 - 10:44,
Adversary-Aware, Machine Learning-based Detection of Spam in Twitter Hashtags. (2021). Adversary-Aware, Machine Learning-based Detection of Spam in Twitter Hashtags. University Of York, 2021.

An Approach for Detecting Image Spam in OSNs

Journal Article Tue, 10/11/2022 - 10:44,
An Approach for Detecting Image Spam in OSNs. (2019). An Approach for Detecting Image Spam in OSNs. Tto 2019: Conference For Truth And Trust Online, 2019.

A semi-supervised learning approach for tackling Twitter spam drift

Journal Article Tue, 10/11/2022 - 10:44,
A semi-supervised learning approach for tackling Twitter spam drift. (2019). A semi-supervised learning approach for tackling Twitter spam drift. International Journal Of Computational Intelligence And Applications 18 (02 …, 2019.

Detecting spam images with embedded arabic text in twitter

Journal Article Tue, 10/11/2022 - 10:44,
Detecting spam images with embedded arabic text in twitter. (2019). Detecting spam images with embedded arabic text in twitter. 2019 International Conference On Document Analysis And Recognition Workshops …, 2019.

Abdullah, Muhammad Tahmeed 103 Abed, Mourad 73 Abouhagar, Leina 157 Abu Elkhail, Abdulrahman 121

Journal Article Tue, 10/11/2022 - 10:44,
Abdullah, Muhammad Tahmeed 103 Abed, Mourad 73 Abouhagar, Leina 157 Abu Elkhail, Abdulrahman 121. Abdullah, Muhammad Tahmeed 103 Abed, Mourad 73 Abouhagar, Leina 157 Abu Elkhail, Abdulrahman 121.

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