Abstract
Child exploitation through the use of the Internet as a delivery and exchange tool is a growing method of abuse towards children. It is shown that a Stochastic Learning Weak Estimator learning algorithm and a Maximum Likelihood Estimator learning algorithm can be applied against Linear Classifiers to identify and filter illicit pornographic images. In this paper, these two learning algorithms were combined with distance algorithms such as the Non-negative Vector Similarity Coefficient-based Distance algorithm, Euclidian Distance, and a Weighted Euclidian Distance algorithm. Experimental results showed that classification accuracies and the network overhead did have a significant effect on routing devices.
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© 2010 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Ibrahim, A., Martin, M.V. (2010). Detecting and Preventing the Electronic Transmission of Illicit Images and Its Network Performance. In: Goel, S. (eds) Digital Forensics and Cyber Crime. ICDF2C 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 31. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11534-9_14
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DOI: https://doi.org/10.1007/978-3-642-11534-9_14
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