Modern digital transformations have been fueled by APIs, revolutionizing how many businesses and organizations are now run.
However, the recent wave of innovation and digital transformation is also to blame for opening up new entry points for hackers to exploit.
API communication makes up 83% of internet traffic. As a result, as APIs are used more frequently, there are also an increasing number of API data breaches.
The issue persists because outdated API security is insufficient to stop sophisticated cyberattacks today.
An innovative approach to enabling API security that uses AI-driven API security measures has begun to emerge as API security has emerged as the focal point for guaranteeing customer data privacy and security.
To safeguard unsecured APIs, artificial intelligence (AI) can assist in enabling strong security measures.
In order to develop the capacity to fend off attacks, AI is trained using a sizable amount of data artifacts from both structured and unstructured resources.
Additionally, AI strengthens its knowledge and comprehension of cybercrime with the aid of machine learning and deep learning, which significantly strengthens an API’s security posture.
What Is API Security, And Why Is It Crucial?
API security has quickly emerged as one of the top concerns for GDPR, PSD2, CDR, PCI, and HIPAA compliance as API integration moves into the spotlight at many organizations.
The growing number of data breaches brought on by unreliable APIs serves as further evidence of this.
According to IBM, at least one breach affected 50% of all security decision-makers worldwide in 2018.
There were an alarming number of data breaches in 2021 alone, with some of the most significant ones being:
- Data breach: The social media site’s unreliable APIs led to a privacy leak of user messages and other sensitive data. The platform was quickly taken down after that.
- Microsoft Exchange Server attacks: The Chinese government-sponsored hacking group targeted several Microsoft Exchange Server deployments, specifically its web component and APIs.
- LinkedIn scraping: The attacks took place twice, once in April 2021 and once in June 2021. As a result, a sizable amount of LinkedIn profile data was sold on a dark web market. Microsoft claims that such data mining is made possible by API leaks.
The prevalence of these attacks has made API security a crucial component of any business strategy in the digital age.
A strong security strategy must be in place because APIs are used to transmit and store such a large amount of sensitive data.
Any organization that implements API security is guaranteed defense against a variety of threat actors and their nefarious attacks.
However, given the current threat environment, incorporating AI-based security measures is the only way to ensure high-grade API security.
Traditional API Security Issues
The traditional model for API security heavily relies on authentication, authorization rate-limiting, and throttling. Although these tools are useful, they still do not offer the security APIs required to thwart threat attacks.
Although modern internet users rely on the use of robust security tools like VPN to enable data protection and online security, API attacks continue to rise steadily.
The fact that API gateways front multiple web services and frequently have a high volume of active sessions on the APIs they manage must be understood.
So, even if someone works to analyze all of those sessions through policies and processes, it will still be difficult for an API gateway to manually review each request without computer assistance.
In addition, every API functions via its access patterns. Consequently, a pattern of legitimate API access could frequently point to malicious activity for another API.
To determine the appropriate response in this situation, the API gateway may need to analyze each API access pattern separately.
Insider threats are a crucial element that frequently undermines the effectiveness of current API security measures.
It is challenging to stop these insider threats using policy-based authentication and authorization because they involve users who have legitimate credentials and access to systems.
The most effective way to reduce insider threats while utilizing the conventional API security method is to add more rules and policies within an API gateway.
This approach would, however, put more strain on API gateways, which would cause processing delays. Users who experience the delays may become irate.
Improvements In API Security With The Arrival Of AI
Modern security methods see AI as the ultimate solution as the traditional API security method continues to fall short in ensuring robust API security.
Since AI can recognize and respond to dynamic attacks and specific vulnerabilities that each API faces on its own, it has significantly altered API security.
Through ongoing inspection and detection, AI models can help businesses find suspicious API activities and threats.
Without a doubt, the risks and anomalies that API faced could have been detected by the prior security measures.
But because these procedures took months, it was frequently already too late when discoveries were made.
Contrarily, incorporating AI-based security models on user access patterns can assist in real-time threat detection.
The fact that AI models frequently operate outside of API gateways and establish their communication and decisions externally is the most important aspect of integrating AI security.
The addition of AI security has no effect on API gateway runtime performance because these models don’t call for the expansion of the resources of the API gateways.
The following are a few of the main advantages of using AI-powered API security:
- Real-time protection against cyberattacks
- Identification of malicious actors and patterns
- Improved security for API data
- Increased safety for businesses in the digital age
Due to the advent of AI, businesses can now better safeguard their API data and keep their systems secure because API security is more crucial than ever in the age of cyberattacks.
Organizations can ensure their business is secure in the digital age by putting API security measures in place.
For instance firetail has built an API security platform that provides application layer visibility, real-time, inline inspection and blocking of malicious API calls.
Finally, strong API security is required given the current threat environment.
Integrating AI appears to be the best solution in enabling robust API security as the conventional security techniques cannot keep up with the contemporary, actively thriving digital landscape.
With the advent of AI, businesses can now better safeguard their API data and safeguard their systems.
Organizations can manage their affairs without the hassles and interference of various API threats and vulnerabilities thanks to a number of advantages provided by an AI-based API security approach.
