How firms can improve private cloud security with AI integration

Over the years, several technological advancements have had a profound impact on industries, revolutionising global business landscapes. At the forefront of this transformation stands cloud computing, which is emerging as a business disruptor in the digital age. Gartner forecasts that more than 50% of global enterprises will use industry cloud platforms by 2028, expanding the global market size to $1,266.4 billion. Thanks to its ability to eliminate long standing roadblocks to business progress.  

From enabling well-established organizations to optimise their workloads to empowering startups born in the cloud, such as Uber and Airbnb, to seize opportunities swiftly, cloud computing has facilitated transformative changes, all at a pace that was once unimaginable!

While private cloud environments offer better protection as compared to public cloud environments, due to better organizational control and monitoring practices, some entry points persist. Attacks on private cloud infrastructure may stem from diverse causes, including inadequate security measures and misconfigured systems, attracting threat actors such as hackers and cybercriminals to exploit vulnerabilities, compromise data integrity, and steal confidential information.  

Even industry giants like Microsoft have fallen victim to cyber-attacks originating from cloud computing vulnerabilities. In a recent incident, the Russian state-sponsored threat actor known as Midnight Blizzard launched a password spray attack on Microsoft in late November 2023, which resulted in the compromise of critical customer data. Alarmingly, the server involved was not password protected, rendering it accessible to anyone on the internet.

In another shocking case, an India-based wearable company, Boat, faced a massive data breach where the critical data of over 7.5 million customers was exposed on the dark web.  

Leveraging AI technologies is paramount to bridging such security gaps and augmenting the existing security protocols. A few benefits of AI integration include:  

Continuous Monitoring: AI-driven systems ensure continuous monitoring by analysing extensive datasets, a key advantage in early threat detection. Oftentimes, human security teams may inadvertently overlook certain threat indicators; however, with AI algorithms, one can prevent this. Through real-time observation of user activities, network traffic, and system behavior, AI provides timely insights into potential security threats and compliance breaches, thereby ensuring a better security posture.

Anomaly Detection: By training ML models, a subset of AI, one can identify deviations from usual behavioral patterns. By developing a sharp knowledge base of suspicious behaviors over time, these models can promptly alert to suspicious activities, signaling potential security risks or non-compliance.

These AI-powered systems adapt and evolve with training, learning from past incidents to enhance accuracy.

Behavioral Analysis: In contrast to systems lacking robust security measures that may inadvertently accept unauthorized login attempts posing as legitimate users, AI models armed with advanced algorithms can discern and pinpoint suspicious behavior, offering in-depth insights into user patterns within the cloud environment. This proactive approach enables organisations to detect and mitigate potential threats right in time.

Adaptive Security Measures: Gartner outlines four stages of AI-driven adaptive security architecture: predict, prevent, respond, and detect. These stages, coupled with security policies and compliance measures, empower AI to proactively identify new attack vectors and tactics employed by cybercriminals. By adapting to newer security measures, AI ensures seamless defense against evolving threats at their source.

Automated Remediation: Automated remediation powered by AI facilitates detecting security incidents while also executing response and remediation actions automatically. When a security incident is detected, AI can analyze the threat severity and determine the right course of action based on predefined response protocols. This includes isolating compromised systems, blocking malicious IP addresses, and revoking compromised user credentials. This not only minimizes damage to private cloud infrastructure but also helps alleviate the burden on security teams.

The Future of AI in Cloud Computing

AI and cybersecurity are inextricably linked, as witnessed by the rapid adoption of both over the last few years. As cybercriminals continue to evolve with their tactics, AI’s extraordinary speed and outstanding threat detection capabilities empower modern security teams to stay ahead of the evolving security threats. The symbiotic relationship between AI and cloud computing accelerates businesses toward a sophisticated, interconnected future.  

The reliance on cloud infrastructure is rapidly growing across the world. It is thus imperative for modern businesses across sectors to embrace AI to enhance their cybersecurity posture. This measure not only addresses present-day challenges but also future-proofs organizations, ensuring resilience in the face of emerging cyber threats, thus laying a solid foundation for long-term security success.

Vaibhav Tare

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Vaibhav Tare is VP & Chief Information Security Officer (CISO) of Fulcrum Digital