Monitor for Detection and Prevention of Fake Agents
Data mining gives good monitoring environment in data sharing applications. In different number of data sharing applications discuss about noisy objects and without noisy objects. In previous system data leakages with fake objects, those objects are created here with fake agents. These situations are discussed about using some random operations specification process. Random fake objects show the results like as a data loss problems. Now, the authors are introduce the new techniques like guilt aversion agents implementation. Guilt aversion agents detect the selfish behavior content identification and different attacks detects. Using Guilt model analysis find out noisy objects.