Online Child Predator Detection Using ML (Research Paper (original) (raw)

Online Child Predator Detection Using ML

International Journal of Scientific Research in Science and Technology, 2023

Professionals in the field need a comprehensive understanding of the risks and practices associated with online sex grooming to safeguard young individuals from online sex offenders. While the Internet offers numerous positive aspects, one of the most detrimental issues is its potential for facilitating online sexual exploitation. Originally designed as a communication tool, the Internet inadvertently provides access to promiscuous content for countless children, often in a covert manner. The objective of our task is to identify and flag potential predators through analysis of comments and online media accounts, with the intention of reporting such instances to the appropriate cyber cell administrator. Recent public surveys indicate that approximately one in five young people actively search for sexual content online each year (Finkelhor, Mitchell, & Wolak, 2000; Mitchell, Finkelhor, & Wolak, 2001). This task report outlines our progress in developing a framework to address this issue. Through the implementation of this framework, accounts associated with predatory behaviour are identified, and reports are promptly submitted to the administrator for further action.

Child Predator Detection System On Social Media

2021

PROFESSIONAL PSYCHOLOGISTS NEED TO UNDERSTAND THE DANGERS OF ONLINE SEXUAL HARASSMENT AND HOW TO PROTECT YOUNG PEOPLE FROM SEX PREDATORS USING THE INTERNET. ALTHOUGH THE NET HAS SEVERAL POSITIVE ASPECTS, ONE IN ALL THE FOREMOST PERNICIOUS ASPECTS IS ITS POTENTIAL USE FOR ON-LINE SEXUAL POSTULATION. THE INTERNET SHOWS A MEDIUM THAT ALLOWS SEX PREDATORS TO ENTER NUMEROUS CHILDREN IN A RELATIVELY ANONYMOUS ENVIRONMENT. THE MAIN OBJECTIVE OF OUR PROJECT IS TO DETECT CHILD PREDATOR BASE ON COMMENTS AND POST OF SOCIAL MEDIA ACCOUNT AND SEND PREDATOR RECORD TO CYBER CELL ADMIN.A RECENT NATIONAL SURVEY INDICATED THAT ABOUT ONE IN FIVE YOUTH ARE SOLICITED FOR SEX OVER THE INTERNET ANNUALLY (FINKELHOR, MITCHELL, & WOLAK, 2000; MITCHELL, FINKELHOR, & WOLAK, 2001). THIS PROJECT REPORT PRESENTS OUR CURRENT DEVELOPMENT TO ENABLE THE CREATION OF THE SYSTEM. AS A RESULT, WITH THE DEVELOPED SYSTEM, CHILD PREDATOR ACCOUNTS DETECTION ANY REPORT TO ADMIN FOR FURTHER ACTION. Index Terms – SVM, ML, Train...

A Learning-Based Approach for the Identification of Sexual Predators in Chat Logs

2012

The existence of sexual predators that enter into chat rooms or forums and try to convince children to provide some sexual favour is a socially worrying issue. Manually monitoring these interactions is a way to attack this problem. However, this manual approach simply cannot keep pace because of the high number of conversations and the huge number of chatrooms or forums where these conversations daily take place. We need tools that automatically process massive amounts of conversations and alert about possible offenses. The sexual predator identification challenge within PAN 2012 is a valuable way to promote research in this area. Our team faced this task as a Machine Learning problem and we designed several innovative sets of features that guide the construction of classifiers for identifying sexual predation. Our methods are driven by psycholinguistic, chat-based, and tf/idf features and yield to very effective classifiers.

Child Predator Detection in Online Chat Conversation using Support Vector Machine

2021

Increase in Internet use and facilitating access to social media platform has help the predatory to establish online relationships with children which has boost to increase in online solicitation. We are proposing system that enables us to detect a predator in online chats using Text classification method. In this paper, the use of machine learning algorithm named as support vector machine has been used to determine cyber predators. The main objective of our system is to detect child predator base on chat, comments and post of social media account and send predator record to cyber cell admin & the use of PAN12 dataset is done for text classification Purpose. This paper presents our current development to enable the creation of the child predator system using SVM text classification.

Sexual predator detection in chats with chained classifiers

This paper describes a novel approach for sexual predator detection in chat conversations based on sequences of classifiers. The proposed approach divides documents into three parts, which, we hypothesize, correspond to the different stages that a predator employs when approaching a child. Local classifiers are trained for each part of the documents and their outputs are combined by a chain strategy: predictions of a local classifier are used as extra inputs for the next local classifier. Additionally, we propose a ring-based strategy, in which the chaining process is iterated several times, with the goal of further improving the performance of our method. We report experimental results on the corpus used in the first international competition on sexual predator identification (PAN'12). Experimental results show that the proposed method outperforms a standard (global) classification technique for the different settings we consider; besides the proposed method compares favorably with most methods evaluated in the PAN'12 competition.

Overview of the international sexual predator identification competition at PAN-2012

2012

Abstract This contribution presents the evaluation methodology for the identification of potential “sexual predators” in online conversations as part of PAN 2012. We provide details of the realized collection and analyse the submissions of the participants, who had to solve two problems: identify the predators among all the users in the different conversations and identify the part (the lines) of the predator conversations which are the most distinctive of the predator bad behaviour.

Combating the Internet Child Predator

Combating the Internet Child Predator will examine the practice of child predation using the technology and use of the internet, identifying offenders, what steps parents can monitor home internet usage to prevent and stop a child"s exposure to possible internet predation, what resources and organizations are available to address internet child predation, how law enforcement investigates reports of internet child predation, the successful prosecution of internet child predation cases, and recidivism of internet child predators.

Detecting Child Grooming Behaviour Patterns on Social Media

Online paedophile activity in social media has become a major concern in society as Internet access is easily available to a broader younger population. One common form of online child exploitation is child grooming, where adults and minors exchange sexual text and media via social media platforms. Such behaviour involves a number of stages performed by a predator (adult) with the final goal of approaching a victim (minor) in person. This paper presents a study of such online grooming stages from a machine learning perspective. We propose to characterise such stages by a series of features covering sentiment polarity, content, and psycho-linguistic and discourse patterns. Our experiments with online chatroom conversations show good results in automatically classifying chatlines into various grooming stages. Such a deeper understanding and tracking of predatory behaviour is vital for building robust systems for detecting grooming conversations and potential predators on social media.

Automated Identification of Child Abuse in Chat Rooms by Using Data Mining

Data Mining Trends and Applications in Criminal Science and Investigations, 2000

Providing a safe environment for juveniles and children in online social networks is considered as one of the major factors of improving public safety. Due to the prevalence of the online conversations, mitigating the undesirable effects of child abuse in cyber space has become inevitable. Using automatic ways to combat this kind of crime is challenging and demands efficient and scalable data mining techniques. The problem can be casted as a combination of textual preprocessing in data/text mining and pattern classification in machine learning. This chapter covers different data mining methods including preprocessing, feature extraction and the popular ways of feature enrichment through extracting sentiments and emotional features. A brief tutorial on classification algorithms in the domain of automated predator identification is also presented through the chapter. Finally, the discussion is summarized and the challenges and open issues in this application domain are discussed.

Profiling of online pedophiles

Pravo - teorija i praksa

Paraphilias represent a group of disorders characterized by a pathological sexual tendency or anomaly, with the impulses including intense sexual fantasies and urges that keep returning in regard to the unusual objects, activities, circumstances, and/or certain category such as the children. Pedophilia belongs to this group of disorders and it is alternatively labeled as a pedophile disorder, which includes specific incriminated actions, which in addition to prison sentences, generally result in a social stigmatization of not only perpetrators but victims too. It is a sexual affinity disorder mostly found in adults who have expressed sexual fantasies and a tendency to enter the sexual relations with children of the same or the opposite sex. Nowadays, a "digital space" has become a unique environment where these specific crimes take place, and the border between the virtual and real world is practically indistinguishable. In this digital environment, pedophiles and other se...