A framework to detect cybercrime in the virtual environment

Thangiah, Murugan; Basri, Shuib

doi:10.1109/iccisci.2012.6297307

Cited by 7 publications

(6 citation statements)

References 5 publications

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“…According to the researchers, the results of their studies performed very well in detecting cyberbullying in both languages. In this way, their model can therefore detect multiple languages in the cyberbullying space [40], [41].…”

Section: A Cyberbullying Text Detectionmentioning

confidence: 99%

Cyberbullying in Text Content Detection: An Analytical Review

Azumah¹,

Elsayed²,

ElSayed³

et al. 2023

Preprint

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Technological advancements have resulted in an exponential increase in the use of online social networks (OSNs) worldwide. While online social networks provide a great communication medium, they also increase the user's exposure to life-threatening situations such as suicide, eating disorder, cybercrime, compulsive behavior, anxiety, and depression. To tackle the issue of cyberbullying, most existing literature focuses on developing approaches to identifying factors and understanding the textual factors associated with cyberbullying. While most of these approaches have brought great success in cyberbullying research, data availability needed to develop model detection remains a challenge in the research space. This paper conducts a comprehensive literature review to provide an understanding of cyberbullying detection.

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Section: A Cyberbullying Text Detectionmentioning

confidence: 99%

Cyberbullying in Text Content Detection: An Analytical Review

Azumah¹,

Elsayed²,

ElSayed³

et al. 2023

Preprint

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“…Based on [25], cyber crime could be categorized in two ways: content based and technology based crimes. The former is managed by any specific terrorist organization related to the article of threating , national security, child pornography, sexual harassment, etc.…”

Section: Cybercrime Analysismentioning

confidence: 99%

A review of cyberbullying detection: An overview

Nadali

Murad

Sharef

et al. 2013

2013 13th International Conference on Intellient Systems Design and Applications

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With the growth of Web 2.0, online communication and social networks are emerging. This alternation helps users to share their information and collaborate with each other easily. In addition, these internet services help establish new connections between persons or reinforce existing ones. However, they can also lead to misbehaviors or cyber criminal acts for example, cyberbullying. At the same time, it can make children and adolescents to use the technologies for the intention of harming another person. Due to the negative effect of cyberbullying, some techniques and methods are proposed to overcome this problem.This paper illustrates a survey covering some methods and challenges in cyberbullying. Next, we offer suggestions for continued research in this area.

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“…The second group consists of the people who may not expert users of computer but utilize computers and the Internet to harass other users, such as to bully someone using social media, to threaten national security using Internet services, and to send threatening e-mails. Given these characteristics, cybercrime is classified into two broad categories, namely, (i) technology-based cybercrimes and (ii) content-based cyber [57], as shown in Fig. 1.…”

Section: Cybercrime and Its Taxonomymentioning

confidence: 99%

“…This type of cybercrime is performed by technical experts and involves hacking, injection of malicious codes, and incidents of espionage [57]. Cyberattack, a type of technology-based cybercrime, is any sort of offensive act utilized by people or entire associations that targets information systems, critical infrastructure, computer networks, and/or personal computers via different methods for pernicious acts normally starting from an unknown source that either takes, changes, or decimates a predefined focus by hacking into a susceptible system [58].…”

Section: Technology-based Cybercrimementioning

confidence: 99%

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Detection of Suspicious Terrorist Emails Using Text Classification: A Review

Mujtaba

Shuib

Raj

et al. 2018

MJCS

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This paper provides a comprehensive review and analysis of the detection of suspicious terrorist electronic mails (emails) using various phases and methods of text classification. We explored, analyzed, and compared different datasets, features, feature extraction techniques, feature representation techniques, feature selection schemes, text classification techniques, and performance measurement metrics used in the detection of suspicious terrorist e-mails. 30 articles were retrieved from 6 well-known academic databases after rigorous selection. From the study, we found that researchers often generate their own e-mails dataset since there is no public dataset is available in the research area of detecting suspicious terrorist e-mails. In most of the studies, researchers used content and context-based features to detect terrorist e-mails. Our findings also show that the most commonly used feature extraction techniques are the bag of words and n-gram, the most typically applied feature representation schemes are binary representation and term frequency, the most usually adopted feature selection method is information gain,, the most common and most accurate text classification algorithms are naïve bayes, decision trees, and support vector machines, and the widely employed performance measurement metrics are accuracy, precision, and recall. Open research challenges and research issues that involve significant research efforts are also summarized in this review for future researchers in the area of suspicious terrorist e-mail detection using text classification techniques where the critical analysis presented in this paper also provides valuable insights to guide these researchers. Finally, the indicated issues and challenges presented in this paper can be used as future research directions in this area.

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A framework to detect cybercrime in the virtual environment

Cited by 7 publications

References 5 publications

Cyberbullying in Text Content Detection: An Analytical Review

Cyberbullying in Text Content Detection: An Analytical Review

A review of cyberbullying detection: An overview

Detection of Suspicious Terrorist Emails Using Text Classification: A Review

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