Machine Learning-Powered Cybersecurity: A Guardian of the Future

Aashish Yadav | May 18, 2022 | 219 views

Machine Learning-Powered Cybersecurity: A Guardian of the Future
Today, as more and more businesses are undergoing digital transformation, the risk of cybersecurity is also rising. Cyber risk has evolved as one of the significant threats for businesses over time. Businesses are struggling to safeguard themselves from a growing number of cyber threats. Because of cybercrime, businesses lost approximately $1,797,945 per minute in 2021, according to Tessian.

Machine learning (ML) and artificial intelligence (AI) tools offer huge potential to help businesses and other entities deal with a wide range of current cybersecurity challenges. AI and ML enable real-time learning and analysis of potential cyber threats. They also use algorithms to make behavioral models, which they then use to predict cyberattacks whenever new data becomes available. Let’s have a look at the reasons why ML-based cybersecurity has become more crucial than ever.


Why Has Machine Learning Become so Important in Cybersecurity?

There are several reasons why ML-based machine learning has grown to prominence. Cybersecurity systems can use AI and ML to analyze attack patterns and learn from them in order to prevent them and respond to their changing behavior. It can support cybersecurity professionals in becoming more proactive in terms of preventing risks and dealing with current attacks in real-time. In short, good data and machine learning can make cybersecurity easier, more proactive, cheaper, and much more effective.


How can Machine Learning help businesses improve their cybersecurity?

AI and machine learning are providing significant advantages to organizations that implement them in their cybersecurity programs. According to a report from the Capgemini Research Institute, 61% of businesses think AI will be needed to find critical threats, and 69% think AI will be needed to deal with cyberattacks. AI and ML can quickly analyze huge quantities of data, making it far faster than manually detecting threats.

  • AI and ML minimize cyber threat detection and response effort, making them cost-effective. The Capgemini report found a 12% average cost reduction.
  • Cyber analysts are alerted aboutattacks and categorize the kinds, which helps them determine the correct response.
  • As more data is analyzed and the technologies learn from past patterns, AI and machine learning improve cybersecurity over time.
  • AI and ML are used by many businesses to rank network threats and figure out which parts have been attacked the most.
  • Businesses use AI to identify malicious activity automatically.
  • AI and machine learning are also being used to detect suspicious user behavior.
  • Many businesses prevent financial fraud by predicting unusual consumer behavior utilizing machine learning.
  • AI and machine learning can also help businesses predict potential cyberattacks.


Companies Bolster their Cyber Security Systems through ML



Concluding Lines

If used correctly, machine learning can improve cybersecurity. Machine learning's dramatic and lasting influence is real. Integrating AI and ML to improve cybersecurity is crucial, but organizations should remember that these technologies are only as effective as the analysts who control and use them.

Spotlight

Intertrust Technologies Corporation

Intertrust Technologies invents, develops, and delivers technologies for trusted computing, digital privacy, and security among leading global corporations from mobile and CE manufacturers and service providers, to enterprise software platform companies. Intertrust and its subsidiaries are also developing new trusted computing services for vertical markets related to consumer privacy, Internet processing of DNA data,

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GuidePoint Security | September 28, 2022

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