Hello everyone. I'm excited to present enhancing enterprise security with ai, a strategic framework for automation and threat management. As cybersecurity threats continue to evolve in sophistication and frequency, organizations are turning towards artificial intelligence as a game changing LA to their security operations. This framework explores how AI is transforming enterprise security automation and threat management. In this presentation, we'll examine the essential components of AI driven cybersecurity architecture, how it enhances network security. Automates reporting and enables proactive security, pro poster management. Ultimately creating more resilient systems that can adopt to continuously changing threat landscape. AI is changing how we protect our networks and systems from cyber threats. It helps us detect potential issues faster, respond more efficiently, and adopt our security systems to new and evolving threats. This is important because cyber attacks are becoming more sophisticated and frequent. AI brings us the ability to not only defend against known threats, but also to predict and stop unknowns before they can cause harm. Imagine you are a security guard at a bank. Traditional methods would only help you spot obvious threats like a person trying to break in. But AI would help you spot subtle signs like a person trying to gather information about security systems even before they act. The growing AI security adoption landscape, the adoption of AI powered cybersecurity solutions has witnessed exponential growth over past five years. Organizations across industries are recognizing the value of integrating AI to their security infrastructures. Therefore, trend is driven by compelling results. The key benefits of implementing AI is reduced breach life cycle. AI powered solutions significantly shorten the time from threat identification to contaminant cost savings. Organizations utilize AI in their security operations, realize cost savings up to 60% compared to traditional security methods. Let's take an example. Think about a company dealing with hundreds of security alerts daily. Without ai, the security team has to manually check each one leading to delays and missed threats. But with AI, the system automatically filters. And prioritize alerts, making it much easier for the team to focus on critical issues, straight away. Core components of AI driven security framework. A robust AI driven security framework is built upon multiple interconnected components. At its foundation is a comprehensive data collection and analysis that fits intelligent systems. Intelligence power machines, learning models that accelerate identifying anomalies that signature based approaches often miss. The middle layers enable automated incident response through orchestration. Technologies that accelerate remediation at the top. Predictive capabilities provide pro defense by anticipating potential attack factor before they materialize a security poster that stays ahead of emerging threats. We, we would also like to integrate a zero zero trust architecture. Let's take an example. It's like setting up an automated home security system where sensors detect motion cameras, monitors suspicious activity, and alarms go off before a burglar even tries to break in. AI enhanced anomaly detection, pattern recognition. AI algorithms detect septal patterns and correlates in network behavior that human analysis might miss. Behavioral baselines. Machine learning establishes normal operation baselines, flagging deviations with greater accuracy and fewer false positives. Real time analysis. Continuous monitoring provides instant threat assessment and actionable intelligence for security teams. Adaptive learning. AI systems evolve by incorporating new data, improving detection capabilities as threat landscape changes. Let's take an example. If an employee who usually logs in from one location suddenly logs in from a foreign country, AI spots this anomaly and flags it as suspicious. Even though it might not be a direct attack yet, let's take one more example. An employee who logs in normally from eight to five has an unusual login somewhere around 3:00 AM or maybe, 2:00 AM. So AI flags those suspicious activities and based on that. It can take some action like blocking that account or analyzing the severity and criticality of the application. Based on that, it can take actions. Automated incident response capabilities, alert evaluation, AI evaluates incoming alerts based on severity, context, and potential impact. Organizing critical threats. Contextual analysis enriches alerts with relevant intelligence and environmental context for more informed decision making. Orchestrated response automates the executions of predefined playbooks and response procedures across security systems. Verification and reporting verifies the effectiveness of remediation and provides detailed documentation for compliance and future improvements. By using all this, AI can prioritize what critical threats, and based on that it can take an action. Let's take an example. Imagine you get an alert that an employee clicked on a suspicious email instead of manually investigating ai, quickly analyzes the risk and either wants the employee or isolate the issue to prevent the further harm vulnerability management revolution. Intelligent continuous assessment. AI moves beyond traditional scanning using machine learning to evaluate vulnerabilities based on exploitability attacker behavior and asset criticality. Risk-based prioritization, AI prioritizes remediation efforts based on actual risk to the organization. Rather than relying solely on CVSS scores, faster remediation AI can recommend or even implement fixes. Significantly reducing the time from discovery to resolution. AI is fundamentally transforming vulnerability management by moving beyond simple scanning to intelligent continuous assessment. Machine learning algorithms evaluate vulnerabilities. This revolutionary approach prioritizes remediation effects based on actual risk rather than. Generic ratings ensuring security teams focus on what matters most. Let's take an example. Let's say your system has vulnerability that is only exploitable. If an attacker is already inside your network. AI can consider this and tell you to focus on fixing other vulnerabilities that are more likely to be exploited from outside automated compliance monitoring. Continuous assessment, real-time monitoring of systems, configurations against regulate regulatory frameworks like nist, P-C-I-D-S-S, hipaa, and a SO 27,001 Documentation Generation. Automatic creation of compliance reports and audit trails, reducing manual documentation efforts for creation maintenance. Drift detection, immediate identification of configuration changes that may impact compliance status and enabling rapid remediation by using automated compliance monitoring, it is very easy to maintain our certifications because AI will take care of all the monitoring that are necessary and all the documentation that is necessary for maintaining the certification. Let's take an example. AI works like an automatic compliance audit that never misses anything. It continuously checks if your systems are following regulations, so you don't have to scramble to prepare when an audit is due. Threat intelligence, integration, collection and aggregation, gathering threat data from diverse sources, including commercial feeds, open source intelligence. Dark web monitoring and industry I-S-A-C-S. Analysis and enrichment. AI processes raw intelligence to identify patterns, relevance, and create actionable insights specific to environment. Operational integration, automated distribution of intelligence to security controls for proactive defense across security stacks. Advanced natural language processing can analyze unstructured threat data from security blogs, forms, and social media. While machine learning algorithms identify correlation between seemingly unrelated incidents, the result is significantly more robust. Defense poster that anticipates and counters emerging threats. Let's take feedback and refinement, continuous evaluation and adjustment of intelligence parameters to improve future analysis. Let's take an example. If a hacker shakes new shares, a new exploit tool on a forum, AI can detect it, learn from it, and update security systems to protect against that specific tool before it's used in an attack. Just in time security remediation. Just in time security remediation represents a paradigm shift from a static defense to dynamic protection measures that adopt in real time. The approach leverages AI to continuously evaluate risk and automatically implement appropriate security controls precisely when needed. Dynamic protection shifts from static defense to adoptive real-time security measures that continuously evaluate and respond to risks. AI driven security AI automatically implements context aware security controls precisely when needed, reducing unnecessary exposure. Reducing attacks surface by moving away from traditional always on-premise. Organizations can significantly lower their attacks surfaces while maintaining operations efficiency cloud environments. This approach is especially beneficial in cloud environments where perimeter based securities in insufficient. Let's take an example. It's like adjusting the security level in your home. When you are home, you don't need high security locks everywhere. But when you are away, AI sets up strong protections automatically. Just in time. Security remediation has three main components temporary access controls, adoptive security boundaries on demand isolation. By using these things, it'll only implement when the security is needed, and other times it can relax so that systems can perform more effectively. Performance optimization through AI integrations. By using AI integration we have, we can reduce the false positives by 85%. You can respond to incidents by increasing your speed by 67%, and you can improve the resource utilization by 73%. AI driven security solutions significantly reduce false positives, helping. Elevate alert fat that often burden security teams faster response. Automated orchestration capabilities have cut incident response time by over two thirds, enabling quicker mitigation of threats. Intelligence, resource allocation, AI optimizes resource users allowing security teams to achieve more with existing staff. Improved security and cost savings. These efficiency gains result in stronger security poster and direct cost savings for organizations. Let's take an example. Think of security team constantly overwhelmed with alerts. AI filters out unnecessary ones and help the team focus only on what really matters, reducing burnout and improving their effectiveness. Building your AI cybersecurity roadmap. Implementing an AI driven cybersecurity framework requires a strategic phased approach tailored to your organization's specific needs. Begin with the comprehensive assessment of your current security poster and clearly define objectives of AI integration, strategic phase approach. Begin with the comprehensive assessment of. Your current security poster and define clear objectives of AI integration pilot projects start with focused AI initiatives, high value areas like phishing detection and endpoint production to demonstrate early value and build confidence. Integration not replacement. Emphasize integrating AI with existing security tools and practices rather than replacing them entirely Continuous improvement. Regularly assess the effectiveness of AI solutions and refine the approach as technologies mature. Let's take an example. It's like building a new bridge. First, you need to assess the land, plan, the design, and then start with small test sections. Once you've got it right, you build more and refine the process. In conclusion, AI plays a critical role in improving cybersecurity By making systems smarter and more responsive, it helps detect threats faster, respond more efficiently, reduce human errors, and improve compliance. AI makes security operations more efficient and reduces costs while keeping organizations safe. Just think of an AI as a superpowered assistant that works 24 by seven, constantly improving and ensuring your systems stay ahead of potential threats. That's all. Thank you.