Andrey Nikiforov
National Research Nuclear University MEPhI
8 Papers
10 Citations
Andrey Nikiforov is an academic researcher from National Research Nuclear University MEPhI. The author has contributed to research in topics: Money laundering & Computer science. The author has an hindex of 2, co-authored 7 publications.
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Papers
Applying Big Data Technologies to Detect Cases of Money Laundering and Counter Financing of Terrorism
Kirill Plaksiy,Andrey Nikiforov,Natalia Miloslavskaya +2 more
- 01 Aug 2018
TL;DR: The paper suggests a technique that allows to automate schemes that generates new criminal cases for money laundering and counter financing of terrorism (ML/CFT), which are based on ML/C FT typologies but do not appear as their exact copies.
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Standardization Issues for the Internet of Things
Natalia Miloslavskaya,Andrey Nikiforov,Kirill Plaksiy,Alexander Tolstoy +3 more
- 16 Apr 2019
TL;DR: This research is focused on how the IS issues are addressed in these standards and an assumption on the significance and prospects of the progress in this field is made on the basis of the analysis performed.
9
Исследование графовых субд, пригодных для работы с большими данными при обнаружении дел по отмыванию доходов, полученных преступным путем, и финансированию терроризма
TL;DR: In this article, the authors proposed a method to improve the quality of the information provided by the users by using the information gathered from the users' own data, such as: рассматривa данным.
Big Data Analytics for Financial Crime Typologies
Kirill Plaksiy,Andrey Nikiforov,Natalia Miloslavskaya +2 more
- 26 Aug 2019
TL;DR: A technique to automate the generation of new criminal cases for money laundering from crime and financing terrorism (ML/FT), which are based on ML/FT typologies are proposed on the basis of creating various versions of case typologies and further filtering them by the derived criteria.
2
Standardization of Ensuring Information Security for Big Data Technologies
Natalia Miloslavskaya,Andrey Nikiforov,Vladimir Budzko +2 more
- 01 Aug 2018
TL;DR: Existing standards in the field of Big Data are discussed, where reviewed with a gross emphasis on the adequate ensuring of its IS, and some prognostications in the studied area are attempted.
2