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Dr. Virender Khurana is a Professor in the Department of Computer Science at Vaish College Rohtak, Haryana, India. He has rich experience in computer science education, data analytics, and software systems. His research interests include artificial intelligence, data mining, and smart computing applications. He has published several research papers in reputed journals and conferences.
The increasing accessibility of educational data has revolutionised decision-making in academic institutions, facilitating evidence-based tactics that improve learning outcomes and institutional efficiency. This chapter examines data-driven decision-making in education via the incorporation of machine learning (ML) and big data analytics. This analysis explores the potential of several data sources—such as student performance records, learning management systems, attendance, and behavioural data—to yield meaningful insights for educators, administrators, and policymakers.
The cybersecurity threat landscape has grown dramatically as a result of the Internet of Things (IoT), cloud computing, software-defined networking, 5G/6G networks, and interconnected digital services. When it comes to spotting illegal activity, hostile traffic, strange behaviour, and possible security breaches, intrusion detection systems, or IDSs, are essential. Conventional signature-based intrusion detection systems (IDSs) may have trouble identifying new and quickly changing threats, but they are effective against existing attacks. By identifying patterns in network traffic, system behaviour, and security events, machine learning (ML) offers a clever substitute. The principles of machine learning-based intrusion detection, IDS architectures, data preprocessing, feature engineering, supervised and unsupervised learning, deep learning, anomaly detection, ensemble techniques, real-time detection, explainable AI, federated learning, and security challenges are all covered in this chapter. Performance evaluation, benchmark datasets, applications, case studies, and future research objectives for creating intelligent and adaptive cybersecurity systems are also covered in this chapter.