AI-Driven Managed 
Security Services Explained: 
How to Choose the 
Perfect MSSP Partner

It is reported that by 2027, global cyber-crimes are expected to cost the world more than $23 trillion. Hence, no surprise the cybersecurity providers and enterprises at large are looking for better ways to protect the networks and systems on which organizations operate and store data. Enter artificial intelligence.

Going beyond traditional monitoring and predictive analysis, AI has made a larger impact in cybersecurity. Employing advanced machine learning algorithms, AI can now reconstruct attack scenarios, avoid human errors in interpreting data, facilitate 24x7 monitoring, even identify intricate threat patterns that may have remained invisible to human analysts. Powered by generative AI and agentic frameworks, AI adapts to, learns from, and evolves for future threats while automating remedial actions.  

Organizations find themselves not just purchasing security services; but investing in intelligent, adaptive defense ecosystems that anticipates, detects, and neutralizes cyber threats. Managed Security Services combine advanced AI tools with human expertise to offer robust and proactive cybersecurity defenses. MSSPs have been seen as strategic partners by enterprises seeking a holistic, intelligent defense ecosystem.

Let us understand better. This blog will explore how AI-driven managed security services are turning the face of security strategies worldwide, the exceptional advantages it offers and why it is an absolute necessity to choose the RIGHT managed security service provider. 

What is the Current State of AI in SecOps?

Security operations (SecOps) have evolved from reactive to proactive. For a long period, the Security Operations Center (SOC) meant a huge room with big screens constantly flashing alerts. To these screens hooked, were security teams – continuously monitoring and analyzing alerts. The SOCs were originally established for government and defense organizations focusing mainly on network alerts. Then came intrusion detection systems (IDS), firewalls, anti-virus, etc. SecOps got sophisticated to keep up with the growing threats. For instance, security information and event management (SIEM) were added sometime in 2005 to detect threats and respond to them better (incident detection and response).

Jumping to the current year, technologies like automation and artificial intelligence are getting fully integrated into security operations, helping businesses cut through the noise, process data better, and resolve threats efficiently – with an expectation to deliver not just security, but also meet compliance, reporting, and training needs. However, with the legacy core still needing upgrade or lack of consolidation in data flows across environments present significant silos in proper AI implementation. 

For instance, let's take a recent study to understand better.  Analysts get thousands of alerts each day, on average:

• Number of alerts received daily: 4484
• Hours spent in the manual alert triage: 3
• Percentage of alerts handled/attended daily: 33%
• Number of false positives: 83%
• Time spent on alerts that aren’t a threat: 32% 

Or, what happened with a giant US-based retailer. In 2013, the retailer faced one of the largest data breaches where the credit and debit card information of about 41 million customers was stolen. This data breach cost them $18.5 million in lawsuit settlement. The penny for thoughts moment here was that alerts were raised by their monitoring software, but security experts missed to act on them. They likely thought of the alert as a false positive or a low-priority alert, like hundreds of others they receive daily.

AI in security isn't just for innovators anymore—it's also in the hands of hackers, phishers, cybercriminals, and state-sponsored groups. If the adversaries are using it, shouldn’t you?

Managed Security Services for Advanced Risk Management

What are Managed Security services (MSS)?

MSS are a suite of security services provided by a third-party provider - designed to protect businesses from cyber threats such as malware, ransomware, and phishing attacks. Managed security services (MSS) cover a range of security services, including and not limited to network security, endpoint security, vulnerability management, threat detection and response, firewall management, and cloud security. 

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Security teams are drowning in data, struggling to keep up with the daily security events, facing challenges like alert fatigue, delayed threat detection, manual investigation bottlenecks, and a constant cat and mouse game to catch up with sophisticated criminals. This is where AI-powered MSS comes in.

Role of AI In Managed Security Services

Security operations teams continue to upgrade their existing security adaptive control layers with AI-embedded capabilities. These adaptive controls include cloud-based email security, intrusion prevention, and layer 7 web application firewalls.  

Managed security solution providers, have significantly invested in AI and machine learning (ML) in their various solutions, including security automation, deep visibility to help with the response to cybersecurity threats, and using behavior analytics to detect never seen potential threats. AI solutions have the potential to completely transform the way we look at cybersecurity. By combining ML with advanced algorithms, AI can automate and optimize security practices. Here are some of the ways AI can enhance Managed Security services:

• AI-driven Threat Detection and Prevention: AI algorithms analyze vast amounts of data and identify patterns that analysts might miss. This enables the system to detect and prevent threats in real time before it can escalate into a major event.
• Real-time Monitoring and Response: AI monitors network and system activity in real time and responds to threats within seconds - this minimizes the impact of any attack by a large extent.
• Endpoint Security: AI-powered, ML enables real time analysis helps identify anomalies in large data volumes of endpoint data, which could highlight signs of potential threats or beginning of a cyberattack.
• Predictive Analytics: AI systems contribute significantly to breach risk prediction by providing accurate and detailed IT asset inventories. It covers all devices, users, and applications with varying access levels to critical systems. By combining the inventory data with threat exposure assessments, global threat databases, historical attack patterns, AI can predict the areas most susceptible to cyber-attacks.
• AI-assisted Cyber Threat Intelligence: Cyber Threat Intelligence (CTI) collects information about cyber security attacks and events. The goal of CTI is to be informed about new or ongoing threats with the intention of proactively preparing teams for the possibility of an attack.
• Code Scanning: SAST has used a “sources and sinks” approach to code scanning, to track the flow of data, looking for common pitfalls. AI/ML solutions learn and understand the context or intent around possible findings in the code base, reducing false positives and false negatives.
• Automated Discovery of Vulnerabilities: DAST and other related application testing tools have begun to implement AI/ML directly into their platforms, or even as plugins, enabling improved automated scanning. Not only does this free up staff who would need that ramp up time, it also frees up time and money needed to do full scale penetration testing which still requires manual efforts.
• Authentication and Access Control: GenAI improves identity and access management by implementing advanced, context-aware authentication mechanisms. It can analyze user behavior, location, device characteristics, and historical access patterns to make decisions about granting or restricting access.
• Advanced Behavioral Analytics and Anomaly Detection: AI identifies any unusual behavior and anomalies that may indicate any potential threat. Now, this can include identifying policy violations, unusual login times, sudden spike in data transfers, abnormal communication patterns, and unauthorized access attempts.
• Automation Of Routine Security Tasks: Automating daily events like log analysis and incident response can reduce the workload of analysts and free them up to focus on more strategic and complex security challenges.

Managing it all in-house is no joke, especially if there are no dedicated security teams. This brings us to the next big step – Choosing the right Managed Security Services Provider or MSSP.

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Selecting a Forward-Thinking MSSP: Why Is It So Crucial?

When choosing an MSSP, it is a basic checkpoint to evaluate their approach to the adoption of AI technologies in security.  

An MSSP with a clear vision to integrate AI-powered security solutions into its services offers advanced capabilities to address the new and coming cybersecurity challenges. This vision should include road maps for AI implementation, along with investments in advanced threat detection capabilities, automated response capabilities, and predictive analytics tools.  

IDC's recent security services survey found that 46% of U.K. organizations consider generative AI capability to be a very important or extremely important criteria when choosing a security services provider.  

Organizations must also assess the MSSPs ability to offer custom AI-powered solutions that meet specific needs. MSSPs that offer flexible service options, scalable AI platforms, and personalized threat intelligence feeds tailored to the industry and specific business requirements provide better support in improving the overall cybersecurity posture.

An MSSP that offers AI-powered cybersecurity chatbots as part of their managed services is another plus for organizations to access advanced threat intelligence and incident response capabilities without big internal teams. These chatbots can be tailored to meet specific security needs and can provide real-time support to boost SOC efficiency.  

Partnering with forward-thinking MSSPs that prioritize AI integration should be on top of the list when putting a robust security strategy in place. MSSPs like Cloud4C come to mind.

Cloud4C: World’s Leading Automation-driven Managed Security Services Provider (MSSP)

"First rule of any technology in a business is that automation applied to an efficient operation will magnify the efficiency.” - Bill Gates.

As an MSSP, Cloud4C acts as an extended Cybersecurity Incident and Response Team (CSIRT) to your security management ecosystem, delivering the entire monitoring and threat management work with ease, while assisting the organization in the adoption of breakthrough cybersecurity frameworks, methodologies, and intelligent solutions. 

Cloud4C's Managed Extended Detection and Response (MXDR) solutions offer a comprehensive suite of AI-powered cyber defense platforms. This full-stack solution integrates various key technologies - Security Information and Event Management (SIEM), Security Orchestration, Automation, and Response (SOAR), Endpoint Detection and Response (EDR), and Advanced Threat Protection (ATP). Leveraging these tools, we ensure real-time monitoring, threat detection, and automated incident response across multi-cloud and hybrid environments. Our dedicated Security Operations Center (SOC) teams further improve the value of our MXDR offerings by providing expert insights and tailored security strategies.

Integrating AI in our security solutions, we offer advanced threat intelligence powered by industry-leading platforms such as Microsoft, OSINT, STI&TAXI, MISP, etc, allowing us to provide solutions like advanced threat hunting, deep cybersecurity analytics, predictive alerting, and preventive maintenance through our proprietary AI-driven automation solutions. We also offer our proprietary Self-Healing Operations Platform (SHOP™) solutions - an innovative approach that not only automates threat detection and response but also incorporates preventive maintenance features.

It doesn’t end, but the future of security solutions surely starts with AI. Contact us to know more today! 

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