Anomaly Detection in Wireless Sensor Networks Using Machine Learning: Review

The security-enhanced information systems are of fundamental exigency for modern connected entities in the modern day, owing to its rapidly evolving digital world and more sophisticated cyber-attacks. There is a vast new target for cybercriminals owing to the widespread use of Internet of Things (IoT) devices, cloud computing services, and other networked technologies [1], [2]. As a result, implementing reliable and flexible cybersecurity solutions is more critical than ever before. Attack detection systems are crucial for the protection of digital assets and private data. These systems serve as sentries, always keeping an eye out for suspicious activities and reacting swiftly to any dangers they detect. Because of how well they protect against data theft, service outages, and monetary losses, they are an essential part of cybersecurity plans [3], [4].