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Detection of criminal entities involved in money laundering using data mining / Mohamed Metwally Elbanna ; Supervised Hatem Elkadi , Mohamed Khafagy

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Mohamed Metwally Elbanna , 2020Description: 65 Leaves : charts ; 30cmOther title:
  • اكتشاف الكيانات الاجرامية المتورطة فى غسل الاموال باستخدام التنقيب عن البيانات [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Computers and Artificial Intelligence - Department of Information Systems Summary: Criminals do money laundry to hide theillegitimate sources of money. Money laundry has many stages that moneyflow has to go through to finally look legitimate, rule-based systems are implemented across differentbanks to detect structuring which is one technique of thelayering stage which sophisticated criminals can evade by unsatisfyingthe check rules.In this work, graph database and graph data mining are tobe used to overcome this limitation, the proposed techniquedoes this by using Clustering along with PageRank for detecting money launderers, our results have proven correct detection
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.04.M.Sc.2020.Mo.D (Browse shelf(Opens below)) Not for loan 01010110082599000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.04.M.Sc.2020.Mo.D (Browse shelf(Opens below)) 82599.CD Not for loan 01020110082599000

Thesis (M.Sc.) - Cairo University - Faculty of Computers and Artificial Intelligence - Department of Information Systems

Criminals do money laundry to hide theillegitimate sources of money. Money laundry has many stages that moneyflow has to go through to finally look legitimate, rule-based systems are implemented across differentbanks to detect structuring which is one technique of thelayering stage which sophisticated criminals can evade by unsatisfyingthe check rules.In this work, graph database and graph data mining are tobe used to overcome this limitation, the proposed techniquedoes this by using Clustering along with PageRank for detecting money launderers, our results have proven correct detection

Issued also as CD

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