Preserving integrity in online social networks Page 1 92 COMMUNICATIONS OF THE ACM |
FEBRUARY 2022 | VOL. 65 | NO. 2 review articles THE GOAL OF online social networks is to …

With the growing amount of pornography content over Internet and cases of Child Sex
Abuse (CSA) material possession and distribution, there is a rising demand for automatic …

Recent literature has explored automated pornographic detection–a bold move to replace
humans in the tedious task of moderating online content. Unfortunately, on scenes with high …

Nowadays, the growing number of cases of possession and distribution of Child Sexual
Abuse (CSA) material pose a significant challenge for Law Enforcement Agencies (LEAs). In …

Over the past two decades, the nature of child pornography in terms of generation,
distribution and possession of images drastically changed, evolving from basically covert …

The creation of manipulated multimedia content involving human characters has reached in
the last years unprecedented realism, calling for automated techniques to expose …

Countless cybercrime instances have shown the need for detecting and blocking obscene
material from social media sites. Deep learning methods (DLMs) outperformed in …

Convolutional neural network (CNN) models are typically composed of several gigabytes of
data, requiring dedicated hardware and significant processing capabilities for proper …

Deep learning-based methods have been proven excellent performance in detecting
pornographic images/videos flooded on social media. However, in a dearth of huge yet well …

In detecting sensitive media, violence is one of the hardest to define objectively, and thus, a
significant challenge to detect automatically. While many studies were conducted in …