International Journal of Sustainable Devlopment in field of IT

AI in Cybersecurity: A Comprehensive Review of Threat Detection and Prevention Mechanisms

2025-02-02T12:34:15+00:00

The rise of cyber threats has led to the adoption of AI-driven security solutions for threat detection, intrusion prevention, and malware analysis. This review examines ML techniques used in cybersecurity, including anomaly detection, adversarial ML, and automated threat intelligence. We analyze real-world applications in network security, phishing detection, and endpoint protection, while discussing challenges related to adversarial attacks, explainability, and data privacy in AI-driven cybersecurity systems.

NLP for Sentiment Analysis: A Review of Techniques and Real-World Applications

2025-02-02T12:35:54+00:00

Natural Language Processing (NLP) has been instrumental in understanding human emotions through sentiment analysis across social media, customer reviews, and financial markets. This paper explores traditional approaches like lexicon-based methods and machine learning classifiers, as well as deep learning-based sentiment analysis using Transformer models such as BERT and RoBERTa. We discuss challenges related to multilingual sentiment analysis, sarcasm detection, and domain-specific adaptability, highlighting future research directions to enhance sentiment classification accuracy.

Quantum Machine Learning: A Review of Emerging Trends and Computational Advantages

2025-02-02T12:37:38+00:00

Quantum Machine Learning (QML) is an emerging field that leverages quantum computing to enhance ML algorithms. This review explores foundational QML concepts, including quantum annealing, variational quantum circuits, and quantum kernel methods. We analyze potential applications in optimization, cryptography, and drug discovery, while discussing limitations such as quantum hardware constraints and the scalability of quantum algorithms. The paper also highlights recent advancements in hybrid quantum-classical models and their implications for future AI development.