With the increased development and reliance on multimedia data, the importance of attributing the device or camera of origin in the form of source camera identification (SCI) has gained traction in cybersecurity, specifically within digital multimedia forensics. Photo-Response Non-Uniformity (PRNU) is a popular and widely used method for extracting a unique and reliable sensor pattern fingerprint for SCI purposes. The usage of PRNU in distinguishing cameras across different manufacturers and models has proven to be successful; however, we demonstrate that current approaches fail to distinguish cameras amongst the same manufacturers and models. As such, in this paper, we propose a new algorithm that focuses on emphasizing the pixels that contribute to the sensor noise in the PRNU pattern to distinguish cameras of the same type. Unlike other similarity metrics used in the process of SCI, we utilize the Jaccard coefficient in order to provide a proportion value of matching pixel locations shared between the noise patterns of two devices. Our experimental results show that our method can successfully determine the device origin of an image from cameras of identical type across Apple iPhone 6, FujiFilm, Panasonic, and Sony cameras.