2018 International Conference on Advances in Big Data, Computing and Data Communication Systems (icABCD) 2018
DOI: 10.1109/icabcd.2018.8465413
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Mitigating Online Sexual Grooming Cybercrime on Social Media Using Machine Learning: A Desktop Survey

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Cited by 20 publications
(9 citation statements)
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“…According to the definition of child sexual grooming, it is "a communication process by which a perpetrator uses affinity seeking strategies, while concurrently engaging in sexual desensitization and gathering information about targeted victims with the aim to develop relationships that result in need fulfillment, such as physical sexual solicitation." Therefore, the labels "pedophile" or "sexual predator" are frequently used to refer to such individuals [18].…”
Section: Groomingmentioning
confidence: 99%
“…According to the definition of child sexual grooming, it is "a communication process by which a perpetrator uses affinity seeking strategies, while concurrently engaging in sexual desensitization and gathering information about targeted victims with the aim to develop relationships that result in need fulfillment, such as physical sexual solicitation." Therefore, the labels "pedophile" or "sexual predator" are frequently used to refer to such individuals [18].…”
Section: Groomingmentioning
confidence: 99%
“…Por fim, recentemente foi realizada uma revisão de literatura em Ngejane et al [2018]. Nessa revisão, foram considerados todos os trabalhos com melhores resultados, considerando as métricas acurácia e F 1 .…”
Section: Trabalhos Relacionadosunclassified
“…Machine-learning approaches are being used by researchers to detect power outages caused by cyber-attacks [8] and to prevent the Internet of Things vulnerabilities [9]. Other applications include detecting spam and network attacks [10], detecting phishing attempts against banks [11], and increasing sexual crimes on social media [12] Stock prediction [13], risk mapping [14], and www.ijacsa.thesai.org cyber profiling [15] are some of the sectors where these technologies have been used. Implementation areas include predicting crime trends and patterns [16], criminal identity detection [17], and crime prevention [18].…”
Section: Introductionmentioning
confidence: 99%