Integrating cutting-edge information and communication technology with a power system's physical components is the objective of a cyber-physical power system (CPPS). The purpose of this integration is to improve power generation, transmission, and distribution efficiency, dependability, and security. Cyberattacks on CPPS might have disastrous effects since it could affect vital infrastructure. Strong cyber security measures, including frequent system monitoring, network segmentation, access controls, encryption, and intrusion detection and prevention systems, are crucial to reduce the danger of cyberattacks. This article addresses the impact and detection of different types of cyberattacks on the WAC application of CPPS in MATLAB/SIMULINK. Three data-driven techniques, namely Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbour (KNN), are used to analyse and detect three distinct attack scenarios as coordinated attack (CA), false data injection attack (FDIA), and denial of service attack (DOSA). On the WSCC 3 machine 9 bus system, the effectiveness of several classifiers is verified.