A Perusal of Transaction Details from Silk Road 2.0 and its Cogency using the Riemann Elucidation of Integrals

Authors

  • Manan Roy Choudhury Undergraduate, Computer Science and Engineering, Government College of Engineering and Textile Technology, Serampore, Calcutta, India

Abstract

The 21st century witnessed a huge boom in technology, improvement in living standards, or ‘just’ terms, people felt the thrills of modernization. But, as we know, all great deeds come at a pleasant cost. Alongside the numerous positive aspects of modernization, we got to experience several negative aspects of it. One such is the growth of the internet black market. In the past decade, the collaboration of several international intelligence agencies unveiled the sheer extent of these operations. Normally operated on the unregulated Darknet, these markets grew unbeknownst to the masses surfing the World Wide Web. In this paper, we will be studying the transaction details of one particular Darknet marketplace, namely SilkRoad 2, and will analyze its minute details with statistical essence. Now, unlike the Surface Web, the information from the darknet neither has the verified tags clinging to them nor has been stored in secure vaults. So, there’s a huge chance of the transaction details being sandwiched with fallacies. To cope with this dilemma, one needs some strong pillar of evidence supporting it. So, do we. In this literature, we have proposed a new hypothesis, namely Riemann elucidation of Integrals, and have validated the transaction details, using some pre-existing principles and have compared its outcome to that of the outcome through our Hypothesis which has served as a witness to justify the effectiveness of our proposition.

Keywords:

Crypto-markets, Silk Road 2.0, Cryptocurrencies, Zipf’s Law, Dark Web, Riemann Integration

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Published

2022-12-31

How to Cite

Manan Roy Choudhury. (2022). A Perusal of Transaction Details from Silk Road 2.0 and its Cogency using the Riemann Elucidation of Integrals. Applied Mathematics and Computational Intelligence (AMCI), 11(2), 423–436. Retrieved from https://ejournal.unimap.edu.my/index.php/amci/article/view/111