Differences in the definition of cyber child pornography have been complicating the prosecution of cyber child pornographers around the world. The reality is that jurisdictional problems will likely continue for a while longer. Combating the problem of cyber child pornography requires a multi-faceted defense. The technical approach to combating cyber child pornography consists of enhancing routers with a classification system combining the stochastic learning-based weak estimator (SLWE) with a linear classifier. This classification system along with a Bloom filter with counters which keep track of source Internet Protocol (IP) address reputation will be tested using “sanitized” datasets provided by the Toronto, Ontario police department. A positive outcome is expected. Cyber child pornography is an increasingly visible problem in society today. With the growth in home Personal Computer (PC) usage and available access to the World Wide Web, child pornographers have found a convenient venue for sharing horrific pictures of children being sexually abused. The methods currently employed by law enforcement agencies to combat cyber child pornography may be considered primitive and inefficient. This paper reviews the major social, legal, and technological issues facing citizens, lawmakers, and the police regarding cyber child pornography. A source address reputation system based on Bloom filters and novel classification system utilizing a stochastic weak estimator, coupled with a linear classifier is proposed as a technological solution in identifying offensive online material. References