Understanding the sides of Artificial Intelligence (AI) and Machine Learning (ML) in the World of Cyber Security
The quick adoption of technology and the rising wave of the digital era have led businesses to grow steadily, which is quite apparent! But we are also aware of the fact that technology is also becoming a threat to companies and businesses. With the rapid increase in hacking and cybercrime cases, businesses need to redefine their strategy to reduce cyber risks and learn to deal with them.
But are humans sufficient enough to handle the rising cyber-attacks? Well, the answer is a big NO! Since each company differs in function and size, it is becoming difficult for human potential to analyze and improve the cyber security posture.
That is where Artificial Intelligence (AI) & Machine Learning (ML) come in!
With Artificial Intelligence and Machine Learning, the technology and the software can detect complex problems, remove malicious links & malware, prevent pushing attacks, and conservative organizations of the risks ahead. These potent tools are helpful because they can learn the threats over time and identify the types of attacks.
Artificial Intelligence & Machine Learning work together without or less human assistance; thereby preferred heavily in the expeditiously emerging world of cyber security.
Artificial IntelligenceIntelligence exhibits the IntelligenceIntelligence of humans in a more advanced way. Artificial Intelligence can organize, reason, and structure the data as humans do. Machine Learning manages large data sets and runs through them without being programmed. It is a general conception that AI is a superset of Machine Learning.
The Rising Importance Of AI and Machine Learning
Cyber Security professionals often influence AI and Machine Learning with low fault tolerance and increased resource optimization to address the trouble.
• Enhancing Human Analysis
These technologies help solve the problems of expensive expertise and cyber security products through resource optimization. It increases the staff productivity by organizing, reasoning and structuring the critical and challenging data. It reduces the false positivity rate and increases the exactness of providing efficient cyber security solutions. The widening cyber-attacks have become a severe issue for companies, and the need to solve the problem faster and effectively is significant. AI and Machine Learning guarantee the truthfulness and speedy solution of the problem.
• Incident Response
If an unfortunate situation arrives where a cybercriminal attacks the organization, ML generates an automatic response to minimize the amount of damage. Its defensive mechanism can stop the attacks.
AI and Machine Learning can quickly respond to a situation which usually takes time when humans do it. It speeds up the process of early recognition of the problem and conducts forensics to defend the attacked system efficiently.
• Fraud Detection
Early fraud detection can improve internal security and secure the operations of an organization from any external cyber attack. Machine Language reads the dataset patterns, and Artificial Intelligence applies the analytical model. Both these technologies work together and detect any false transaction.
If Machine Learning is used correctly, these technologies help identify the fraud activities and respond to the unknown fraud method and techniques over time. Meanwhile, Artificial Intelligence creates models that reject the transaction if it is suspected of fraud. With the help of the codes, Artificial Intelligence flags the transactions and directs the investigator to speed up the investment.
• Bot Protection
Bots are a large section of online traffic. The bots can be of two types; good bots and bad bots. The bad bots can be a potential threat to the company systems. Bots can perform various tasks such as website monitoring, disturbing denial of service attacks, and engine indexing.
Using AI and ML in cyber security equipment can help determine known and unknown bots. AI can analyze the bot’s behaviour and apply the defence techniques based on the type of bot.
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