Image forgery detection is an approach for detection and localization of forged component from a manipulated image. To find manipulation or tampering in the original image, an adequate number of features are required to classify the given image is either a forged or non-forged. To achieve this convolutional neural network (CNN) based pre-trained AlexNet model's deep features have been utilized which are efficient and effective, as compared to the existing state-of-the-art approaches on publicly available benchmark dataset MICC-F220. The experiment result shows that the proposed approach using a pre-trained AlexNet model based deep features with Support Vector Machine (SVM) classifier has achieved 93.94% accuracy.