As of this writing, the algorithm employed for difficulty adjustment in the CryptoNote reference code is known by the Monero Research Lab to be flawed. We describe and illustrate the nature of the flaw and recommend a solution. By dishonestly reporting timestamps, attackers can gain disproportionate control over network difficulty. We verify this route of attack by auditing the CryptoNote reference difficulty adjustment code, which, we reimplement in the Python programming language. We use a stochastic model of blockchain growth to test the CryptoNote reference difficulty formula against the more traditional Bitcoin difficulty formula. This allows us to test our difficulty formula against various hash rate scenarios. This research bulletin has not undergone peer review, and reflects only the results of internal investigation.
The Internet has become the broadest area in which to exchange information and communicate.Some use this function in a positive way, whilst others do so negatively. With the growth of the Internet, social networks have also grown. Social networks are used in different fields and for different proposes. They are used in higher education to enhance training and collaborative learning and exchange knowledge in an interaction environment.
This paper aims at finding the 10 best universities by measuring the use of social networks in education.Universities are selected for this experiment from the Academic Influence Ranking website for the domain of computer science overall (type A) (for more information about the selected universities please visit this link: http://pubstat.org/).
Visualization is a descriptive way to ensure the audience attention and to make people better understand the content of a given topic. Nowadays, in the world of science and technology, visualization has become a necessity. However, it is a huge challenge to visualize varying amounts of data in a static or dynamic form. In this paper we describe the role, value and importance of visualization in maths and science. In particular, we are going to explain in details the benefits and shortages of visualization in three main domains: Mathematics, Programming and Big Data. Moreover, we will show the future challenges of visualization and our perspective how to better approach and face with the recent problems through technical solutions.