One of the greatest threats into cubing the threats to cyber security is that the hackers are always on the move to create more improvised and coded virus. Therefore the need to identify, define and detect malware attacks at a faster and more efficient way has made the network administrators to decide on having machine learning and artificial intelligence to take over from human beings. Despite having influencing and interesting ideas on improving the threats that com about with this malicious software and virus using machine learning, it is best if we also consider some of the disadvantageous parts that are accompanied by machine learning taking over from human beings in the process of creating antivirus. In this article, both the positive and negative part of machine learning being used to create antivirus will be highlighted and explained in great depths.

The system will definitely be fully automated hence no human ads would generally be needed. The process 1being automated means that the machines can do a large portion of work that humans might find difficult and tiresome. The machines will therefore be accurate and reliable in fighting malware and computer virus infection within a very short time frame. The need for more personnel that were unava1ilableto deal with the computer virus freq1uent attacks triggered the use of automated machines to deal with the case.

The employees that carried data to their homes and those that worked from were mostly the ones that hackers attacked since they knew that companies concentrated in the employees that worked within the offices hence ending up forgetting those that didn’t work in the offices, and they could unknowingly transmit the virus to the company’s servers. This has made companies to want to have more visibility on the companies’ data hence used the machine learning techniques to create an automated antivirus protection for their confidential data.

The idea that machine learning will definitely do it and forget about it has triggered the need for using machine learning in building antivirus. The machines will do the detection and analyze the virus within a short time and find the very best way to stop the virus from spreading. This is quite the opposite when it comes to humans. Humans will need more time and frequent breaks to keep on doing this.

The machines will provide a cheaper and effective way of building antivirus. The machines will not require payment to build the antivirus and the quality of products that they will produce will be very high. The machines are therefore the best in building computer antivirus.

However machine learning in building computer antivirus may lead to unemployment of many people. This is because of their efficiency and quality in their services compared to humans. With increased unemployment, there will be increased threats to cyber security. Therefore the use of machine learning in building antivirus may affect the social being of humans in a great way.

Machine learning consulting in creating antivirus will also require frequent updates unlike human beings who can easily adapt and react appropriately to changes in the system. Since the hackers frequently change the codes in which they use to make malicious software and virus, the machines will also need to up to date in order to make them respond appropriately with the changes in the codes.

In conclusion, although machine learning being used in creating antivirus will have such a big improvement in the fight against virus, its implementation will have a great negative impact in human employees. Therefore all this factors should be taken into consideration.