According to Infosecurity Magazine, machine learning is being used to heighten security and handle the large volumes of data that come with online gaming. This approach helps security experts to deploy a tool which would learn on its own, see patterns of behavior consistent with cheating, and monitor real time data to prevent instances of cheating.
Manual monitoring does not work due to the large amount of data in the form of game play which happens at any given time. Experts maintain that since criminals are operating digitally, law enforcement should be in the same plane as well.
Online gaming is a big business. Massively multiplayer online role playing games or MMORPG are very popular among gamers, and there are even global tournaments. It is so popular that there are professional players who can be found in different countries around the world. With this popularity, there are also people who have dedicated themselves to cheating on video game play, Naked Security reports.
In the early years, video game security centered on making sure that the games are not copied for free, or sold by third parties without paying for it. Nowadays, with most games being distributed for free, the problem lies in some players who steal identities, or who cheat the game and win or level up using methods other than playing the game fairly.
Security teams have a hard time trying to ‘police’ games online because there are a lot of players playing at the same time. Tracing each of these players entails going through voluminous data. Although there are patterns of behavior which may indicate cheating, the sheer volume of data makes it very hard to pinpoint which ones are the bogus players.
Security programs using machine learning to identify patterns of suspicious behavior
Security companies use artificial intelligence and machine learning tools to sift through the huge amount of data to compare behavior which looks dubious. Programs can be created to search and identify these patterns of behavior and trace them back to their owners.
There are three ways that machine learning is being used for online game security: leverage, detective and watchdog. You can put everything that you know about online game security into a program, and let that program work for you. Machine learning can also be used to verify and trace back the cheater. The same program can be used to watch over the action in real time and check to see if anyone is cheating.
The focus on digital security has reached critical mass. Security is being tightened as more and more gadgets and appliances are able to connect digitally, making it easier for hackers and identity thieves to attack unsuspecting victims. The numerous applications for machine learning are becoming increasingly evident, with online game security hopefully being just the first bold step towards a larger goal of overall online security.