AI for Mobile App Security: How AI Can Prevent Cyber Threats

In 2022, the global market for artificial intelligence (AI) in cybersecurity was $17.4 billion high, which is projected to leapfrog to reach $102.78 billion by 2032, a CAGR of 19.43% between 2023 and 2032. However, as cyber threats get stronger, so does the importance of using AI to combat those threats, especially in mobile applications which are highly vulnerable to those cyber threats.

However, with today’s AI tech, AI is not just one added layer of security, but can really ‘be the game changer’ for mobile app protection. Real-time AI senses everything and picks up on the unusual, adapts security on the fly, and reacts in an instant to counter an attack should one occur. For these reasons, it is a vital tool for a wide range of industries from retail and finance to government, all heavily exposed to the rapidly growing risk of cyber intrusions.

Mobile apps are seldom as secure as other platforms and are a prime target for cyber threats. Because of these vulnerabilities, they are especially vulnerable to attacks they fall victim to such as phishing, data breaches, and malware intrusion​. Growing numbers of mobile apps mean that increasing numbers of attackers are developing ever more sophisticated attacks, threatening not just users, but also the businesses they employ.

That’s where AI comes in, by having the ability to adapt to changing threat landscapes. The BFSI, retail, and government sectors are the highest adopters (19.5%, 19.3%, and 20%, respectively) of AI-driven cybersecurity solutions, using AI to secure sensitive information and protect from attacks targeting mobile platforms.​

Real-time threat detection is one of the greatest gifts AI has given to mobile app security. The primary goal is to train the AI so that it can learn normal user behavior, and then recognize the anomaly that could potentially be a sign of danger. Because AI can analyze enormous quantities of data at the speed of light, it is able to identify anomalies that the regular system probably wouldn’t have picked up​.

Furthermore, AI collects threat intelligence to detect and respond to new threats with greater speed as well as handle potential vulnerabilities. This capability is of high value to the enterprise segment (24%) and retail sector (19.3%), as enterprises and retailers constantly need to protect sensitive customer data​. Powered by AI, real-time threat detection allows organizations to neutralize risks before they escalate.

With AI, mobile apps can have smarter, more secure authentication methods. Traditional password-based systems are becoming very vulnerable but the AI-assisted solutions like biometric authentication (facial recognition, fingerprint scanning), and behavioral biometrics provide an additional layer of user-customized security.

AI doesn’t stop at biometrics, it also enhances multi‑factor authentication (MFA), adjusting access requirements according to risk levels. For example, if it seems, AI can prompt for additional verification for a suspicious login attempt. Given the high login activity beginning in these industries as well, like manufacturing (6.5%) and automotive (3.9%), this adaptive approach helps secure data.

AI can tell you what’s happening next. Predictive analysis entails estimating and preventing future attacks by matching historical cyber incidents’ patterns making it a forward-thinking tool to protect against eventual cyber risks to mobile applications​.

Additionally, this preventive approach is powered by AI-driven behavioral analysis which continuously watches for signs of malicious behavior. It can protect the system from similar threats when AI can detect the pattern of those threats that appeared in previous attacks. This capability is most valuable to high-risk sectors such as government and defense which is one of the most common sectors to adopt AI for cybersecurity​.

By defending against malware, unauthorized access, or any attack vectors where these are implemented either directly or stored on a mobile device, AI solidifies endpoint security for mobile devices. By way of continuous monitoring and analytics, AI is capable of identifying anomalous behavior on mobile endpoints and identifying possible security threats quickly.

Automated incident response is an important feature of AI in endpoint protection. Once a threat is detected, AI can take action automatically — isolating the affected area for example, or alerting security teams — to stop it spreading. For example, this rapid response is especially valuable for healthcare (3.4%) and BFSI (19.5%), the industries where mobile devices are often used to handle sensitive data​.

The way mobile apps have reacted to cyber threats is being reshaped by AI. AI-enabled solutions such as real-time detection, adaptive authentication, predictive analysis, and robust endpoint protection, are making mobile applications safer and less vulnerable to attacks.

The role of AI in mobile app protection will only develop as industries turn to adopt AI in cybersecurity. As the cybersecurity AI market is expected to touch $102.78 billion by 2032, it is evident that AI will be an essential element of the cyber threat warfare, across diverse sectors. In today’s digital age, accepting AI-driven security for mobile apps is not just a trend, but necessary.

For businesses already planning their mobile app security with the help of AI-driven tools, Techtic Solutions provides the expertise and innovative approach to remain ahead of the curve. With Techtic, you can onboard AI-propelled security that suits your requirements, making sure you have a solid defense against any mobile application security threat.