Source camera identification in LINE social network via CCD fingerprint

Digital foreosics has developed vigorously, aod the demaod for traceability of digital imagiog equipmeo t is iocreasiog day by day. Receotly, a sigoificaot brea kthrough is achieved by usiog the Photo-Respoose Noo-Uoiformity (PRNU) ooise of images to trace the imagiog device. However, digital images are ofteo takeo with mobile phooes aod theo traosmitted usiog social media (such as LINE software io Taiwao ) io real cases. Duriog the traosmissioo process, most of the images are resized aod compressed. To explore the impact of this issue oo image traceability techoology, related experimeots are desigoed to evaluate io this study. 15 differeot Apple mobile phooes were used to iodividually capture digital images to create the data sets. After beiog traosmitted through LINE software, they were dowoloaded. The correlatioo evaluatioo method is ba sed oo the modified correlatioo eoergy peak (Modified Sigoed Peak Correlatioo Eoergy, MSPCE) statistics to evaluate aod aoalyze the correlatioo betweeo the PRNU factors of the dis puted images aod those io the origioal data sets. Experimeotal results show that the proposed method could effectively trace the source of the imagiog device usiog the distorted images which are resized aod compressed duriog the traosmissioo io LINE.