Cybersecurity is a growing concern not only for small businesses, but also for larger companies. Common cybersecurity attempts are made to hack into servers to steal user data, company data, install ransomware and more. A report published by Forbes says the number of data breaches in 2021 exceeded 2020. And most worryingly, with technological evolution and increasing accessibility, these cyber-attacks are becoming more and more systematic.

Furthermore, in this blog we discuss some AI-supported cybersecurity tips that can not only protect an organization, but evolve over time to improve the quality of firewalls used to protect against cyber-attacks. So stick with us until the end of this blog to have some insightful information. As you can see in the chart above by statistic, in 2019 most companies fell victim to phishing attacks with a share of 38%. Phishing attacks are generally hidden in the form of emails, text messages and more and sent to a company employee with a link. The recipient clicks on the link and fills in details to give the attacker access to their usernames and passwords. However, many organizations try to train personnel to avoid such situations.

Using AI to improve cybersecurity

AI can help improve cybersecurity. The components like Machine Learning and Deep Learning are used to assign cybersecurity tasks according to their requirements.

Automated learning of new cyber threats

Using big data collected from sources such as historical data and market events, AI can update itself to identify new cyber threats. With the help of the Internet, it can automatically learn the functionalities and characteristics of new cyber threats to identify them as potential harm. If such attacks are also detected by the AI-assisted server, it can take precautions as equipped.

Keeping hardware under control

Hardware failure can also lead to data loss and can be identified as a cyber threat. Especially when an organization regularly processes a large amount of data, hardware failures can lead to enormous data loss. To avoid this, AI can monitor hardware performance to identify or predict possible hardware failures. In addition, AI can also generate alerts to warn administrators before it is too late. AI is also used for backup processes to ensure that all data is automatically scanned and uploaded to backup servers to ensure that the data can be retrieved at any time. During this process, AI can monitor data center components such as cooling fans, RAM health, hard drive performance, temperatures, and more.

Vulnerability Management Techniques

Many hacking attempts are also made through authorized user credentials. Either through hacking or via fake user accounts, such attacks were not identified until after the attack was carried out. However, with User and Event Behavioral Analytics (UEBA), it is possible to use AI and ML algorithms to detect anomalies. These analytics are able to detect and track suspicious user behavior in order to temporarily or permanently block their activities. Services such as email filters usually use techniques similar to spam emails, which are more likely to cause cyber-attacks.

Additional verification method

To make changes to data, user credentials are required. However, if these credentials are compromised and an unauthorized access attempt is made, AI can detect and prevent this through additional verification steps. For example, AI can prompt the user to authenticate via CAPTCHA, two-factor authentication, and more. Typically, financial services such as credit card companies use this AI to automatically block cards to keep them more secure if malicious activity is detected.

For example, you usually transact in the US, but suddenly, if your transaction location shows Australia and you haven’t notified the bank about your overseas travel, the bank’s AI may consider this a suspicious activity and block the card. Until the card owner does not confirm by calling the bank and verifying all the details, cards will remain blocked. Other factors such as type of purchases, frequency of transactions and more are also used.

Blockchain and AI combine for extra security

Together with blockchain, AI can help improve cybersecurity by taking steps such as smart contracts. Smart contracts are terms and conditions defined as algorithms and uploaded on blockchain servers. These smart contracts are used in financial institutions to approve claims, transactions, international exchanges and more without the involvement of a third party. To approve operations, smart contracts use documentation as a reference and make decisions accordingly.

For cybersecurity, AI smart contracts can detect malicious transaction attempts, international transactions, and more. To prevent fraud payments and reduce the chance of errors, AI-enabled smart contracts are the best option against cyber threats on a blockchain network.

Blockchain is also a good reason to ensure that entries on this server cannot be deleted or edited. To perform or change edits, a new entry must be created. Each entry is given a timestamp along with the other details like the user’s IP address, device and more to make sure user tracking is easy.

Conclusion

Cybersecurity is a growing concern and while AI is an effective support for cybersecurity, new and more sophisticated attacks are also emerging. Cyber ​​attackers also use AI to hide, mask and infiltrate databases. However, a maximum of these attacks is singled out by AIs to self-improve to predict whether the situation will arise in organizations that have still not faced new attacks. Since AI can also predict what could be used as a gateway to data breaches, this is also one reason why AI should always be used by organizations.

Hopefully the blog was helpful in the end. We’ll see you soon with a new blog. Until then, See you soon!

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