Jeyamohan Neera
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View article: Explainable and Uncertainty Aware AI-Based Ransomware Detection
Explainable and Uncertainty Aware AI-Based Ransomware Detection Open
Ransomware poses a serious and evolving threat, demanding detection methods that can adapt to new attack vectors while maintaining transparency and reliability. This study proposes a comprehensive framework that integrates data augmentatio…
View article: A Trustworthy and Untraceable Centralised Payment Protocol for Mobile Payment
A Trustworthy and Untraceable Centralised Payment Protocol for Mobile Payment Open
Current mobile payment schemes gather detailed information about purchases customers make. This data can then be used to infer a customer’s spending behaviour, potentially violating their privacy. To tackle this problem, we propose an untr…
View article: A Local Differential Privacy based Hybrid Recommendation Model with BERT and Matrix Factorization
A Local Differential Privacy based Hybrid Recommendation Model with BERT and Matrix Factorization Open
Many works have proposed integrating sentiment analysis with collaborative filtering algorithms to improve the accuracy of recommendation systems. As a result, service providers collect both reviews and ratings, which is increasingly causi…
View article: Private and Utility Enhanced Recommendations With Local Differential Privacy and Gaussian Mixture Model
Private and Utility Enhanced Recommendations With Local Differential Privacy and Gaussian Mixture Model Open
Recommendation systems rely heavily on users behavioural and preferential data (e.g. ratings, likes) to produce accurate recommendations. However, users experience privacy concerns due to unethical data aggregation and analytical practices…
View article: Private and Utility Enhanced Recommendations with Local Differential\n Privacy and Gaussian Mixture Model
Private and Utility Enhanced Recommendations with Local Differential\n Privacy and Gaussian Mixture Model Open
Recommendation systems rely heavily on users behavioural and preferential\ndata (e.g. ratings, likes) to produce accurate recommendations. However, users\nexperience privacy concerns due to unethical data aggregation and analytical\npracti…
View article: Local Differentially Private Matrix Factorization with MoG for Recommendations
Local Differentially Private Matrix Factorization with MoG for Recommendations Open