Types Of Cyber Crimes Performed Through E Mail

1705 Words Mar 3rd, 2015 7 Pages

The topic of discussion that was proposed by Rachid Hadjidj, Mourad Debbabi*, Hakim Lounis, Farkhund Iqbal, Adam Szporer, Djamel Benredjem was a new technique in uncovering e-mail forensic data for use in a court of law. Different types of cyber crimes performed through e-mail include “spamming, phising, drug trafficking, cyber bullying, racial vilification, child pornography, sexual harassment, etc.” Suspected e-mail accounts are examined by forensic analysis and data is captured in order to prove crimes in court. The amount of e-mail cyber crimes that manifest is proof that there is a need for a software tool that can be an all encompassing e-mail analyzer in order to capture the needed forensic data. The writers propose
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Analytics should include keyword searches, authorship attribution, and computing statistics. The writers of the article have combined social network analysis with these analytics to create a tool that can track who might be accomplices to malicious e-mailing. Their framework is titled Integrated E-mail Forensic Analysis Framework (IEFAF). With traditional authorship attribution, the writing style of a person is examined by using an entire collection of e-mails without regards to whom they are written. Further more stylometric features are assumed consistent and not controlled by the writer. The writers of the article have proposed that there could be variation in writing style of e-mails dependent upon certain context, recipient, and even time of day. Their proposed approach for authorship attribution is based on statistical analysis results, text mining results (classification/clustering), stylometric features analysis and social networking techniques. E-mail statistical analysis could be a brief summary of e-mails per sender, per recipient, per sender domain, per recipient domain, per class and per cluster. In the writers’ proposed approach, they even include frequency during different parts of the day, average e-mail size and attachment size. They used the following example to depict the reason for needing these statistics: suppose a user sends 20-30 e-mails to co-workers in the

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