Recent research in replica attacks in wireless sensor networks focuses on detecting and preventing malicious nodes that replicate legitimate sensor identities to disrupt network security and data integrity. Advanced detection mechanisms leverage graph-based models, trust management systems, and lightweight cryptographic techniques to identify cloned nodes efficiently. Machine learning and distributed verification methods are increasingly used to enhance detection accuracy while reducing communication and computation overhead. These approaches aim to ensure network resilience, maintain data authenticity, and strengthen defense mechanisms against node replication in resource-constrained and large-scale WSN environments.