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Multimedia Forensics has become important in the last few years. There are two main interests, namely source identification and forgery detection. Source identification focuses on identifying the source digital devices (cameras, mobile phones, camcorders, etc) using the media produced by them, while forgery detection attempts to discover evidence of tampering by assessing the authenticity of the digital media (audio clips, video clips, images, etc). In this paper, we propose a novel source camera identification method based on detection and matching of dustspot characteristics that settle in front of the imaging sensor create a persistent pattern in all captured images of digital single lens reflex camera . To prevent false detections, lens parameter dependent characteristics of dust spots are also taken into consideration. Experimental results show that the proposed detection scheme can be used in identification of the source digital single lens reflex camera at low false positive rates, even under heavy compression and down sampling.

Real time tasks scheduling on a distributed system is a complex problem. The existing real time tasks scheduling techniques are primarily based on partitioned and global scheduling. In partitioned based scheduling the tasks are assigned on a dedicated processor. The advantages of partitioned based approach is existing uni-processor scheduling techniques can be used; no migration overheads but task assignment is NP hard problem and optimal utilization of processing nodes is not possible. In global scheduling all tasks are maintained in a single tasks queue and allocated to multiple processing nodes. The advantage of global scheduling is optimal utilization of processing nodes but suffer from high migration and preemption overheads. This paper proposed cluster based real time tasks scheduling on a distributed system which is a hybrid scheduling approach where processing nodes group into cluster and scheduling using global scheduling. The simulation result shows that the proposed scheduling increases the tasks acceptance ratio, resource utilization as compared to partitioned and global scheduling and reduces migration as well as preemption overheads.