Artificial Intelligence (AI) is the frontrunner in shaping the future of nearly all sectors, mobile application security is no exception. Mobile applications are the primary target for hackers due to the sensitive data they store and handle.

While traditional security solutions are often evaded or bypassed by modern cyber threats, AI-powered security solutions emerge as a game-changer and potential drivers in the future of mobile application security.

In this blog, we’ll explore the need for AI in mobile application security, challenges, and how AI is shaping the future of mobile application security.

Need for AI in Mobile Application Security

The mobile application landscape is vast with millions of apps available across multiple platforms. As app usage grows, the vulnerabilities that threat actors exploit also increase. Traditional signature-based antivirus software is no longer capable of stopping threats that target mobile apps.

Currently, BFSI and government sectors(19.5% and 20%) are the highest users of AI-powered cybersecurity solutions to protect mobile applications. This stat highlights the increased adoption of AI in mobile application security. 

Here are two reasons why AI has become an integral part of mobile application security:

  1. The sophistication of attacks: Mobile apps face a wide range of threats from malware, trojans, denial-of-service attacks(DDoS), etc. These sophisticated attacks can’t be prevented by traditional security measures, making developers rely on AI-powered mobile application security solutions to effectively counter modern threats.
  2. Quicker Response: Modern threats should be quickly removed from the IT infrastructure to minimize the damage. On average security teams have 93 minutes to respond. However, traditional mobile application security solutions can’t identify infiltrations quickly enough compared to AI-powered security solutions.

How AI is Shaping the Future of Mobile Application Security

1. Automated Vulnerability Scanning

Vulnerability scanning is crucial for mobile application security to prevent cybercriminals exploit vulnerabilities. Vulnerability scanning requires identifying vulnerabilities in the app source code. Tradinatial vulnerability scanning tools can be time-consuming and may miss vulnerabilities.AI can automate the vulnerability scanning process and it can be done at a much faster rate.

AI-powered automated vulnerability scanning tools can detect a wide range of vulnerabilities in mobile applications, including

  • Improper API
  • Code Injection flaws
  • Insecure data storage practices
  • Weak encryption mechanisms

Related Reading: On-Premise vs. Cloud-Based Vulnerability Scanning: Which is Better?

2. Behavioural Analysis

Mobile applications from the fintech sector, e-commerce, and social media are prime targets for threat actors. AI can detect fraudulent activities in these mobile applications by analyzing user behavior patterns and flag suspicious activities such as password changes from unusual geographic locations, several login attempts, etc. This can be helpful in detecting identity theft, account takeovers, or payment fraud.

3. Privacy Protection and Data masking

Mobile applications often need to collect sensitive data from users, such as PII, financial, and location data. With growing concerns over data privacy and breaches, it is essential to safeguard these data from breaches.

AI can assist in ensuring user privacy through data masking techniques. Data masking involves rephrasing sensitive data in such a way it remains usable for testing and development purposes but doesn’t reveal the identity of the user. AI can automate this masking process with various algorithms to replace sensitive data with anonymous data without disrupting operations.

4. AI-Powered Testing

AI can be implemented in the testing phase of mobile application development for automating the generation of test cases and identifying potential security gaps from source code. Machine learning algorithms can generate test cases after analyzing the mobile app’s code to simulate every possible scenario. This ensures the security of the mobile application and reduces the risk of vulnerabilities going unnoticed by developers.

5. Enhancing Authentication

Authentication plays a vital role in mobile application security, particularly if it handles sensitive information like personal details, financial data, etc. Traditional password-based security measures are vulnerable to brute-force attacks and credential stuffing. AI-powered authentication can enhance the authentication process in the future by voice recognition or facial recognition combined with behavioural analysis to prevent brute force attacks.

Related Reading: The Impact of AI on Modern Cybersecurity Solutions

Challenges in AI-powered Mobile Application Security 

Despite many advantages, the integration of AI in mobile application security comes with its own set of challenges.Organizations and developers must navigate these challenges to increase the effectiveness of AI in protecting mobile applications.

1. Data Privacy Concerns

AI systems need large amounts of data to train and improve the algorithm’s detection and response capabilities. This data includes sensitive user information, which can raise concerns about privacy. If not configured or handled properly, AI-powered mobile application security solutions could expose user data or violate regulations(e.g. GDPR).

2. False Positive

One of the biggest challenges with AI systems is their unpredictable nature. For example, if an AI security measure blocks legitimate users or flags a normal action as suspicious, the user gets frustrated and might not understand why. This is common in all social media platforms from Reddit to Instagram.

3. Integration

Many organization still employs legacy and old security infrastructure that are not compatible enough for many AI-powered mobile application security tool. Integration of AI-powered tools into existing IT infrastructure can be a costly and complex process, especially for large businesses and enterprises.

Conclusion

AI as a futurist concept in mobile application security is over it is here and playing a vital role in shaping the future of mobile application security. From quick response to AI-powered vulnerability scanning, AI offers security measures for businesses or organizations to safeguard mobile applications.

Related Reading: AI vs. Hackers: Who’s Winning the Battle?