In today’s world, people are inclining towards blockchain technology at a rapid rate. It is no surprise that blockchain technology has made a place in the hearts of the people. The primary reason behind the success of blockchain technology is its capability to build trust, by collecting data and carefully preserving the same. In fact, it is the blockchain technology that works as the pillar of different digital money platforms such as Bitcoin and is successfully helping people is going through a hassle-free transaction procedure. However, did you know that machine learning and blockchain have a certain degree of interlinking? In this article, we will collectively take a look at the nuanced way in which this happens. Without Much Ado, let us begin right away!
The security issue that has prevailed in the market
In complete harmony with the other kinds of technology available in the market, blockchain technology also has a number of downsides that people generally relate to the issue of security, utility, and functionality. It will be rather pertinent to point out that blockchain technology, in recent times, is constantly working towards getting better. Like one will be aware of the fact that Bitcoin is quite famously known for running into some fraudulent activity or the other very often. However, with the help of better implementation with blockchain technology, it is focusing on becoming a safer space for its investors.
However, we cannot possibly look past the problems that prevailed in this area. In this blog, we will together identify some of the problems, and then go and talk about how machine learning techniques are being adapted hugely as a means to solve the problem areas.
3 Problem areas and the implementation of machine learning techniques
- Taking Care of Cryptojacking: One of the most important implementations of the machine learning technique in the realm of the cryptocurrency and blockchain market is this. It is rather important to keep in mind that the different governmental forces and other institutional agencies are all mostly equipped with adequate resources to handle generating problems. Primarily, this makes them the usual targets. Different scholars have made efforts in tying together the technique. Together, this can help in identifying the malfunctioning programs that one can hold responsible for disrupting the normal flow, and hijacking. The system that handles this aspect has been known as SiCaGCN. SiCaGCN Largely looks at identifying the commonality between programs and having a proper grasp over the control flow graph.
- The Area of Trading: It is crucial to remember that in the market today one of the most involved things is the traditional trading bots. These bots generally are filled to the brim with the presence of algorithms that are explicitly of the machine learning domain. Thus, it is no matter of surprise that cryptocurrency and blockchain technology are dependent upon machine learning techniques in order for themselves to improve. It is mostly with the help of the branch of machine learning entitled Reinforcement Learning that this aspect is usually taken care of. This also has attached to it the ceremony of rewards with respect to the communicative aspect.
- Optimizing Mining Strategies: Another most important area that we need to talk about when we’re talking about machine learning is Optimising Mining Strategies. This is largely dependent upon Reinforcement Learning like the previous if you mentioned, and here the miners are generally given block rewards that come with subsequent essential transactions. As per studies, the quintessential RL techniques contribute largely to the field of systematic mining with its model-free algorithm. For further information, you can have a look at https://q-profit-system.com/!
If you take sufficient interest in the realm of cryptocurrency, blockchain, and machine learning, We hope that this blog will help you form a clear understanding regarding the same. We further hope that this will serve as one of the didactic articles that will enthuse you into wanting to know more about this area and implementing the same within the body of your work.