Cybersecurity Data Breach

The growing impact of Artificial Intelligence and Machine Learning on cyber security

The world is quick at accepting Machine Learning and Artificial Intelligence. These cyber incentives are influencing various spheres in our day to day lives and how major economies in the world operate. AI and ML are also adopted during privacy protection policies and for communication purposes. It’s wise to say that the future is AI an ML. Cyber security analysts and experts are identifying both technologies as huge help in combating cyber-crime of various forms. Once employed, ML and AI can be used in the detection of possible cyber threats and strikes. While traditionalist are not planning to adopt ML and AI for the fear of losing their physical relevance, the impact of both technologies if applied successfully is bound to improve human life.
What role will machines play in achieving cyber security?
Before we delve further, let’s first define ML and AI.
Artificial Intelligence
This is technology applied in robotics. Computer bots function through specific application created to enable them engage various task. In this case, the robot or machine has to be programmed using a developed software that can receive command prompts either manually or through voice prompts. AI is successfully applied to accomplish repetitive tasks in manufacturing and organizational levels.
Machine Learning
Machine learning is a branch of AI and also a form of technology whereby computers and mobile devices can be programmed to function through adaptive learning and experience.
Notice that both technologies have an interaction with the cyber world and with their advanced nature they are suitable for combating cyber-crime. Here are some ways in which machines shall achieve cyber security:
• Biometric logins which are part of AI have are successfully used to achieve secure login access through palm prints, scanning finger prints, audio recognition as well as retinas.
• Login passwords can be used together with AI to achieve user privacy on computers and mobile devices
• Since AI and ML depend mostly on adaptive learning which programs the machines to remember previous prompts and attempts, these technologies can easily notice strange operations thus identifying possible cyber threats and attacks.
• Information storage and transfer is safe. Secure logins ensure that only identified users can access the sored files, manipulate them or even transfer them at will
• At industrial level, production will increase. Bots and machines will run the show. This system ensures that there is less human interaction in the event of privacy policies and information storage or transfer.

Some possible drawbacks to using ML and AI to achieve cyber security
AI and ML have lots to offer in the mainstream world as we have observed nonetheless these technologies are still under scrutiny. Analysts have identified various drawbacks which may delay in their full adoption and implementation. Some drawbacks to using AI and ML for cyber security are:
• Both technologies can also be accessed by hackers, who can create AI proof malware.
• To set up ML and AI you need a huge amount of infrastructure and resources. AI users have to employ advanced computing techniques, use more memory and data for it to function successfully.