Cyber Hacking Breaches Prediction and Detection Using Machine Learning

Abstract: A Cyber hacking breaches and prediction using machine learning is one of the emerging technologies and it has been a quite challenging tasks to recognize breaches detection and prediction using computer algorithms. Making malware detection more responsive, scalable, and efficient than traditional systems that call for human involvement is the main goal of applying machine learning for breaches and prediction. Various types of cyber hacking attacks any of them will harm a person’s information and financial reputation. Data from governmental and non – profit organizations, such as user and company information, may be compromised, posing a risk to their finances and reputation. The information can be collected from websites that can be triggered by cyber-attack. Organizations like the healthcare industry are able to contain sensitive data that needs to kept discreet and safe. Identity theft, fraud, and other loses may be caused by data breaches. The finding indicates that 70% of breaches affect numerous organizations, including the healthcare industry. The analysis displays the likelihood of a data breach. Due to increased usage of computer applications, the security for hosts and network is leading to the risk of data breaches. Machine learning methods can be used to find these assaults.

Keywords: Cybersecurity, Data Breaches, Machine Learning, Malware Detection, Breach Prediction, Cyber Hacking, Anomaly Detection, Network Security, Artificial Intelligence (AI), Intrusion Detection Systems (IDS), Risk Analysis, Identity Theft, Healthcare Data Security, Threat Intelligence.