Question: where would you go to escape detection if you wanted to do something illegal on the Internet? Hint: shush!

The background to this paper is the introduction of public access IT facilities in public libraries. These facilities have seen recorded instances of misuse alongside weaknesses in checking identities of users and in explaining Acceptable Use Policies (AUPs) to users. The FRILLS (Forensic Readiness of Local Libraries in Scotland) project, funded by the Scottish Library and Information Council, attempted to survey the situation in Scottish public libraries and develop a forensic readiness logging regime for use in them. There is in depth discussion of the use of logging in public library computer facilitie

A Careful Design for a Tool to Detect Child Pornography in P2P Networks

This paper addresses the social problem of child pornography on peer-to-peer (P2P) networks on the Internet and presents an automated system with effective computer and telematic tools for seeking out and identifying data exchanges with pedophilic content on the Internet. The paper analyzes the social and legal context in which the system must operate and describes the processes by which the system respects the rights of the persons investigated and prevents these tools from being used to establish processes of surveillance and attacks on the privacy of Internet users

Characterizing web pornography consumption from passive measurements

Web pornography represents a large fraction of the Internet traffic, with thousands of websites and millions of users. Studying web pornography consumption allows understanding human behaviors and it is crucial for medical and psychological research. However, given the lack of public data, these works typically build on surveys, limited by different factors, e.g. unreliable answers that volunteers may (involuntarily) provide. In this work, we collect anonymized accesses to pornography websites using HTTP-level passive traces. Our dataset includes about $15\,000$ broadband subscribers over a period of 3 years. We use it to provide quantitative information about the interactions of users with pornographic websites, focusing on time and frequency of use, habits, and trends. We distribute our anonymized dataset to the community to ease reproducibility and allow further studies.Comment: Passive and Active Measurements Conference 2019 (PAM 2019). 14 pages, 7 figure

A review of age estimation research to evaluate its inclusion in automated child pornography detection

The uses of artificial intelligence (AI) today seem limitless. It has helped organisations understand their customers more, provide them with better, more tailored services, and helped people with disabilities understand the world they previously could not. There are also many areas of current research for the use of AI. Aiding law-enforcement when they must analyse evidence of an indecent nature is one example where the use of AI, if successful, could enhance detection of indecent images and also reduce the workload and stress on the law enforcement staff employed in such activities. Working with indecent images of minors is particularly stressful. This paper reviews the current stage at which artificial intelligence finds itself when estimating a person’s age. By reviewing its accuracy, it is possible to evaluate the feasibility of its inclusion in an artificial-intelligence-aided evidence analysis tool. With artificial intelligence currently capable of estimating a person’s age to within a few years, its incorporation would most certainly allow photographs to be analysed and flagged if anyone is suspected of being underage

Identifying Fake News using Emotion Analysis

This paper presents research applying Emotional Analysis to “Fake News” and “Real News” articles to investigate whether or not there is a difference in the emotion used in these two types of news articles. The paper reports on a dataset for Fake and Real News that we created, and the natural language processing techniques employed to process the collected text. We use a lexicon that includes predefined words for eight emotions (anger, anticipation, disgust, fear, surprise, sadness, joy, trust) to measure the emotional impact in each of these eight dimensions. The results of the emotion analysis are used as features for machine learning algorithms contained in the Weka package to train a classifier. This classifier is then used to analyze a new document to predict/classify it to be “Fake” or “Real” News

Estimating the Size and Structure of the Underground Commercial Sex Economy in Eight Major U.S. Cities

The underground commercial sex economy (UCSE) generates millions of dollars annually, yet investigation and data collection remain under resourced. Our study aimed to unveil the scale of the UCSE in eight major US cities. Across cities, the UCSE's worth was estimated between $39.9 and$290 million in 2007, but decreased since 2003 in all but two cities. Interviews with pimps, traffickers, sex workers, child pornographers, and law enforcement revealed the dynamics central to the underground commercial sex trade -- and shaped the policy suggestions to combat it

Designing Light Filters to Detect Skin Using a Low-powered Sensor

Detection of nudity in photos and videos, especially prior to uploading to the internet, is vital to solving many problems related to adolescent sexting, the distribution of child pornography, and cyber-bullying. The problem with using nudity detection algorithms as a means to combat these problems is that: 1) it implies that a digitized nude photo of a minor already exists (i.e., child pornography), and 2) there are real ethical and legal concerns around the distribution and processing of child pornography. Once a camera captures an image, that image is no longer secure. Therefore, we need to develop new privacy-preserving solutions that prevent the digital capture of nude imagery of minors. My research takes a first step in trying to accomplish this long-term goal: In this thesis, I examine the feasibility of using a low-powered sensor to detect skin dominance (defined as an image comprised of 50% or more of human skin tone) in a visual scene. By designing four custom light filters to enhance the digital information extracted from 300 scenes captured with the sensor (without digitizing high-fidelity visual features), I was able to accurately detect a skin dominant scene with 83.7% accuracy, 83% precision, and 85% recall. The long-term goal to be achieved in the future is to design a low-powered vision sensor that can be mounted on a digital camera lens on a teen\u27s mobile device to detect and/or prevent the capture of nude imagery. Thus, I discuss the limitations of this work toward this larger goal, as well as future research directions