Digital privacy is a hot topic these days. But unfortunately, not for good reasons. Ordinary netizens don’t know who can attack their digital privacy and use it for their benefit. From our mobile devices to desktops, every device connected to the internet leaves digital footprints that hackers can trace. 

Users’ data is collected by the websites they browse for information, the apps they use, the social media platforms they visit, and the eCommerce stores where they purchase different products. Sadly, users don’t know how they are using their data. 

The real question is, what happens when that data falls into the wrong hands? From financial losses to depression and stress, the misuse of our data can have devastating effects on us. That’s why everyone must protect their digital privacy.

If you are already worried about your data and how to protect it, don’t worry at all. When hackers and data thieves use different technologies, especially AI (Artificial Intelligence), netizens can also utilize them. AI can help people protect their digital privacy in many ways. And this article will briefly discuss the best AI-driven strategies to protect digital privacy.

Let’s learn what AI has in its bucket!

Read More:- How Does Artificial Intelligence Work with Big Data?

Best AI-Driven Strategies to Protect Digital Privacy

AI can help netizens, consumers, and companies in many ways. However, the strategies or technologies mentioned below are the best regarding data protection or digital privacy.

AI Driven Strategies to Protect Digital Privacy
  • Behavioral Analytics
    • Behavioral analytics is among the best AI solutions that can be used to ensure your digital privacy. Behaviour analytics tools and techniques use data sciences to analyze and interpret data. For example, they analyze behaviour patterns to detect suspicious activities and potential threats. Besides data sciences, behavioural analysis is also powered by artificial intelligence, bringing more accuracy in threat detection.
    • The process of behaviour analytics starts with data collection from various online sources. After the data collection, now comes data processing. In this step, the collected data is then processed and prepared for analysis. Moreover, this step also checks whether the data is usable or not. 
    • After the data processing, machine learning models come into play. They analyze the available data and identify potential threats.
    • This strategy helps netizens in many different ways. First, it detects insider threats. Insider threats are attacks on the data from inside the company by employees with access to a large amount of data. They can attack the company’s data for financial gain or take revenge on employers. 
    • Whatever the case is, they may harm an organization’s digital privacy. However, this strategy can prevent these kinds of attacks as it can inform the security teams about the unusual behaviour of employees.
    • Apart from inside threats, it can also detect APTs (Advanced Persistent Threats). It’s a specific and prolonged cyber-attack on data. These attacks are performed by experienced and skillful hackers who want to steal an organization’s data. APTs are usually tricky to find using conventional methods as they are not designed to analyze and detect these threats. 
    • However, behavioural analytics algorithms can quickly judge any unusual activity by hackers and alert the teams about this kind of threat.
  • Federated Learning
    • Federated learning is a new and advanced method of training a model without sharing raw data with others. In this method, different organizations and individuals can work collaboratively to create a stronger digital privacy model. 
    • Organizations can protect their personal data from various threats by utilizing federated learning strategies. Moreover, almost all sectors can use this digital privacy model, including health, education, IT, defense, etc. 
    • Federated learning provides a wide range of benefits to users. For example, it protects users’ privacy and reduces the risks of data breaches by not exposing the raw data and its sources. In addition, this strategy ensures that data privacy is maintained and not used for any unauthentic purpose.
    • Moreover, this strategy allows different organizations to share their expertise without making their data vulnerable. That’s how multiple organizations can collaboratively create data security methods to protect their valuable data from external and internal threats.
    • And lastly, federated learning offers more efficiency than many other AI-driven data protection strategies as it doesn’t allow organizations to transfer large datasets.
  • Multi-factor Authentication
    • Almost every internet user is aware of multi-factor authentication (MFA) as they use it to secure their accounts on different social media platforms or banking apps. In this data security technique, users must provide multiple identification forms before accessing the data. These identifications include a pin, password, security token, biometric, etc.
    • Although MFA didn’t have any link with AI in its initial stages, with time, AI became its need. As a result, AI has improved the effectiveness of MFA models. For example, AI algorithms can quickly detect unusual user behaviour and identify it as a security threat. That prevents unauthorized access even when the users have the passwords.
    • MFA is very helpful for all those who don’t want to protect their digital privacy. Whether they are individuals or organizations, they can protect their privacy using this method. Many users use this technique to protect their social media accounts as it doesn’t allow anyone to access those networks without authentication.
    • Moreover, AI helps users to prevent fraud by making it difficult for hackers and content stealers to reach and exploit secured data. And lastly, MFA improves security without compromising convenience, as users don’t need to set and remember complicated passwords.
  • Reverse Image Search Engines
    • AI-powered reverse image search engines are also very effective in protecting digital privacy. The reverse photo lookup method can help users locate who is using their data without their consent. It is one of the best ways to find visual content stealers. 
    • Reverse photo search engines take a few seconds to track the content stealers. However, these engines were less efficient and quick than they are now. And the credit goes to AI.
    • Before the integration of AI, image search engines could not perfectly analyze pictures and bring results accordingly. However, most picture search engines now use computer vision, deep learning, neural networks, and machine learning algorithms for precision. Together all these sub-domains of AI are making the image search process quicker and more efficient. As a result, users now get more accurate results according to their queries.
    • In image reverse search, computer vision helps identify various objects, places, and elements in the pictures. Therefore, they can accurately differentiate between two similar things. For example, they can easily differentiate between the full moon and the sun, which are similar in different ways. 
    • Moreover, they can also recognize the difference between different animals and birds. So, when users upload the visual inputs, they quickly judge them and fetch data according to those images.
    • Like other AI-driven data protection strategies, reverse photo lookup also helps users in many ways. For example, it helps them learn who uploads their pictorial data on other platforms without their consent. 
    • This method is helpful for both organizations and individuals. Organizations, especially eCommerce stores, can find out who is uploading their product images and selling them with their names. It also helps them learn where those pictures are uploaded. So they can prevent scams on their names. 
    • On the other hand, individuals, especially artists, can find out who is misusing their pictures and taking credit for their creations.
  • Virtual Private Networks
    • VPNs create a secure and encrypted link between a device and the internet. The VPNs protect users’ digital privacy by keeping their IPs anonymous from hackers. They hide users’ IP addresses and provide them with a new IP to browse the internet. That’s how they keep many intruders away from the users. And no one can trace a user’s online actions.
    • For internet users, virtual private networks are the best solution for protecting their privacy. Although VPNs are already very secure and help users protect their identity, AI implementation is making them more efficient. 
    • Machine learning technology is allowing VPNs to deal with different kinds of threats and protect users’ personal data from being exposed. A recent study revealed that AI and machine learning algorithms could make VPN networks 90% more accurate than they are. Although hackers and content stealers are also using AI to steal users’ data, VPNs coupled with AI can easily combat them. Moreover, AI is helping to make VPNs more secure than ever.
    • Advanced VPNs powered by AI provide many benefits to users. For instance, they can protect their browsing history and not allow anyone to discover their search patterns. Moreover, they also offer a secure internet connection which they need the most to protect their digital privacy. 
    • Apart from that, VPNs also help users bypass geographical restrictions and access the data denied by governments. And last but not least, they hide users’ IP addresses from hackers and provide them with a temporary IP to browse the network. That’s how they keep their users away from hackers.


In the last analysis, with the rise of cyber threats and data breaches, protecting digital privacy is more crucial than ever. As a result, users could suffer from depression, which could be devastating. Many cases have been reported worldwide where data breaches have ruined individuals’ lives. Apart from that, data breaches can also lead to financial losses.

Hackers pose a grave threat to cybersecurity.When hackers use AI and advanced technologies to attack users’ data, users also need to exploit AI services to prevent them and protect their digital privacy. This article has discussed the best and most effective AI-driven strategies to protect digital privacy. So, whether you are an ordinary internet user or an organization, utilize them and protect your data from hackers.