Cybersecurity is a growing concern not only for small businesses but for larger businesses as well. Common cybersecurity attempts are done to hack into servers to steal user data, company data, plant ransomware, and more. A report published by Forbes says, the number of data breaches in 2021 was more than 2020. And, the more concerning part is that, with technological evolution and increasing accessibility, these cyberattacks are becoming more and more systematic in functioning.
Furthermore, in this blog, we are discussing some AI-supported cybersecurity tips that can not only protect an organization but evolve with time to enhance the quality of firewalls used for protection against cyber attacks. So, stay with us until the end of this blog to have some insightful information.As you can see in the above graph by Statista, in 2019, most companies became victims of Phishing attacks with a share of 38%. Phishing attacks are generally hidden in the form of emails, text messages, and more and sent to the employee of a company with a link. The receiver clicks on the link and fills in details just to give the attacker access to their usernames and passwords. However, many organizations are trying to train staff to avoid such situations from occurring.
Use of AI to improve cybersecurity
AI is capable of helping in improving cybersecurity. Its components like Machine Learning and Deep Learning are used to assign cybersecurity tasks based on their requirements.
Automated learning of new cyberthreats
With the help of big data collected through resources such as historical data and events going on in the market, AI can update itself to identify new cyber threats. With the help of the internet, it can automatically learn functionalities and features of new cyber threats coming into existence to identify them as a potential harm. In case such attacks are detected by the AI-supported server as well, it can take precautionary measures as it is equipped with.
Keeping hardware in check
Hardware failure can also result in data loss and can be identified as a cyber threat. Especially when an organization handles a big amount of data regularly, hardware failures can cause a huge data compromise. To avoid this, AI can keep an eye on hardware performances to identify or predict any possible hardware failures. On top of that, 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 on backup servers to ensure the data is retrievable at any point in time. Under this process, AI can monitor data center components like cooling fans, RAM health, Hard Disk performance, temperatures, and more.
Vulnerability management techniques
Many hack attempts are done through authorized user credentials as well. Either by hacking or through fake user accounts, such attacks were only identified once the attack was done. However, with User and Event Behavioral Analytics (UEBA), it is possible to use AI and ML algorithms to detect anomalies. These analytics are capable of detecting and tracking suspicious user behavior to either put temporary or permanent blocks on their activities. Services such as e-mail filters are usually using techniques similar to these to spam emails that have a higher probability of causing cyber attacks.
Additional verification method
To make changes in any data, user login details are required. However, if these credentials are compromised and an unauthorized access attempt is made, AI can detect and prevent it through extra steps of verifications. For instance, AI can ask the user to verify through CAPTCHA, two-factor authentication, and more. Usually, financial services such as credit card companies use this AI to put an automatic block on cards to keep them safer if malicious activity is detected.
For instance, you usually make transactions in the USA, but suddenly, if your transaction location shows Australia and you have not informed the bank about your overseas travel, the bank’s AI might consider it a suspicious activity and block the card. Until the owner of the card does not confirm by calling to the bank and verifying all details, cards remain blocked. Other factors like the type of purchases, frequency of transactions, and more are used as well.
Combining blockchain and AI for extra security
Along with blockchain, AI can help in improving 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 need for a third party. To approve operations, smart contracts use documentation as references and make decisions accordingly.
For cybersecurity, with AI, smart contracts can detect malicious attempts of transactions, international transactions, and more. To avoid fraud payments and to reduce the probability of errors, AI-supported smart contracts are the best option against cyber threats on a blockchain network.
Blockchain is also a good pick reason that any entry made on this server can not be deleted or edited. To execute or modify operations, a new entry will have to be made. With each entry, a timestamp along with the other details like users’ IP address, device, and more are given to ensure tracking the user is easy.
Cybersecurity is a growing concern and even though AI is an effective support to cyber security, it also arises new and more evolved attacks. Cyberattackers are using AI as well to hide them, mask them, and infiltrate databases. However, a maximum of these attacks are picked by AIs to improve themselves to predict if the situation arises in organizations that have still not faced new attacks. As AI is also capable of predicting what can be used as the gateway to data breaches, it is also a reason why AI should always be used by organizations.
In the end, hopefully, the blog was useful. We will see you with a new blog soon. Until then, See you!