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Talkout : Protecting mental health application with a lightweight message encryption
Published 2022“…However, the increased security breaches of recent mental health applications that leaked the patient's profile. …”
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Academic Exercise -
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Adaptive security architecture for protecting RESTful web services in enterprise computing environment
Published 2018“…A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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Adaptive security architecture for protecting RESTful web services in enterprise computing environment
Published 2018“…A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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Applications of deep learning algorithms for supervisory control and data acquisition intrusion detection system
Published 2022“…In this paper, we have examined and presented the most recent research on developing robust IDSs using Deep Learning (DL) algorithms, including Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Stacked Autoencoders (SAE), and Deep Belief Networks (DBN). …”
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A Review on Attack Graph Analysis for IoT Vulnerability Assessment: Challenges, Open Issues, and Future Directions
Published 2024“…In this review, core modeling techniques for IoT vulnerability assessment are highlighted, such as Markov Decision Processes (MDP), Feature Pyramid Networks (FPN), K-means clustering, and logistic regression models, along with other techniques involving genetic algorithms like fast-forward (FF), contingent fast-forwards (CFF), advanced reinforcement-learning algorithms, and HARMs models. …”
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SUDOKU HELPER
Published 2015“…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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A Study On AI-Driven Solutions for Cloud Security Platform
Published 2024“…Cognitive tasks comprise integration, computational cost, and the ethical effect of the algorithm are identified and discussed. Real-world applications and possibilities for further development, such as federated learning and XAI, are also described in order to give recommendations for the effective application of AI-based cloud security. …”
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A new mobile botnet classification based on permission and API calls
Published 2024Conference Paper -
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On protecting data storage in mobile cloud computing paradigm
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A comparative analysis of anti-phishing website techniques: identifying optimal approaches to enhance cybersecurity
Published 2023“…The research consists of analysing the characteristics of phishing websites, extracting their essential features using the wrapper method, and classifying websites as phishing or legitimate using supervised and unsupervised learning algorithms. The study evaluates and compares the efficacy of multiple machine learning algorithms, including the Autoencoder classifier, Extreme Gradient Boost (XGBoost), and Random Forest classifier, using metrics such as accuracy, precision, recall, and F1-score. …”
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Final Year Project / Dissertation / Thesis -
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Deep Learning Based Face Attributes Recognition
Published 2018“…The automated face identification application is helpful in assisting forensic to survey an area with the implementation of Machine Learning (ML). …”
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Study of machine learning in computer vision using Raspberry Pi
Published 2024text::Final Year Project -
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A New Mobile Botnet Classification based on Permission and API Calls
Published 2024Proceedings Paper -
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Glass break detection system using deep auto encoders with fuzzy rules induction algorithm
Published 2019“…This leads to the inability to differentiate glass break from environmental sounds (such as the sound of striking objects, heavy sounds and shouted sounds) that are similar in their amplitude threshold and frequency pattern. Machine learning based acoustic audio classification has been popular in security surveillance applications. …”
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