5 Cybersecurity Use Cases Leveraging AI that Signal a Paradigm Shift

Security administration tasks such as creating security policies or governing user access have mainly been manual for a long time, requiring extreme precision and oversight. At times, one wrong policy is enough to compromise a system.

The Cisco AI Assistant for Security allows firewall administrators to perform the same tasks with a natural language interface. Rather than typing 10 different shell commands for checking policies, they can simply ask the assistant, “What policies are controlling access to the production server?” for a quick answer.

As the assistant is context-aware, it can generate new policy rules based on natural language prompts and intents. It can also detect duplicates and misconfigurations across hundreds of rules to maintain an optimal policy hygiene.

If the administrators need to undertake a complex configuration, it can create a step-by-step tutorial to make the process easy to follow. The dauntingly complex firewall can now be managed with simple queries. This saves time while freeing up bandwidth for top-order security priorities.

AI essentially works by understanding patterns and making correlations. This capability is quite beneficial in a cyberattack scenario as AI-led systems can identify even the tiniest of signals that could lead to an attack.

Cisco XDR uses AI-driven detection to check for suspicious patterns across email accounts, network domains, web activities and more. It can analyze and piece together the datapoints to flag any patterns that look like a cyberattack.

This capability can help cybersecurity teams overcome alert fatigue and automate the manual watchguard process. As a result, fewer attacks slip through the cracks, harmful attacks can be caught early and many can be stopped much before any harm is caused.

To boost network security, the flow of information on a network is usually encrypted so that unauthorized systems can’t eavesdrop on it. But sometimes, this can make it harder to discern compromised endpoints or malicious commands being sent over an encrypted network.

Cisco’s Encrypted Visibility Engine (EVE) uses machine learning and a traffic fingerprinting process to read through encrypted traffic. It helps firewall systems inspect encrypted traffic without decrypting it.

EVE assigns a unique fingerprint to the encrypted traffic it encounters and then identifies whether it is safe or malicious by comparing it to a fingerprint database. It can block the traffic that resembles the fingerprints of malware and let only safe traffic pass through.

This way, EVE can prevent malware from infecting the network or stealing data. The innovative technique empowers cybersecurity teams to stay vigilant and protect against threats that are hard to spot. This can also enable vulnerability scanning and applying security patches.

A security workflow is like a well-organized playbook for handling security incidents within an organization. As more apps, servers and web assets join the digital front, these playbooks can get pretty complex to manage.

AI-driven automation can improve the manageability and monitoring of such workflows by checking if any rules or policies deviate from the acceptable configuration. In many instances, AI can fix problems independently, minimizing loopholes in the system.

Cisco AI Assistant will soon have capabilities to analyze firewall rules in the Cisco Secure Firewall Management Center to drive greater efficiencies in firewall configuration. It can read existing rules, understand the goals and assist administrators to close discrepancies faster.

Recovering from a ransomware attack can be quite time-consuming, as it encrypts data on virtual disks, endpoints and storage drives. The best defence is to prevent ransomware before it can infect systems.

With AI-driven detection, ransomware can be caught much earlier than through manual monitoring. It can check for telltale signs of common vulnerability or exposure (CVE) as they enter a system and automatically trigger a backup before any damage is caused.

This pre-emptive approach and quick action can be very effective. There might be some false positives that the AI may see as real attacks, but it can still reduce the number of successful attacks significantly.

Cisco XDR is trained with machine learning models by Talos that make this early detection possible for triggering a backup before it’s too late.

Cisco Security Cloud is a unified security offering built on zero-trust principles, delivered via cloud to simplify security management and improve security effectiveness. Cisco is progressively integrating AI capabilities across the Security Cloud to empower cybersecurity teams with the following advancements.

• AI assistance: Help users make informed decisions, augment existing capabilities and automate complex tasks to reduce human errors. Provide insights, recommendations and guidance based on the user’s context and goals.
• AI augmentation: Enhance your existing security capabilities with AI-powered features that run at machine speed. Detect and respond to threats faster, analyze and prioritize alerts and optimize security policies.
• AI automation: Cisco Security Cloud can learn from human-to-machine interactions and automate complex playbooks and workflows. Orchestrate actions across multiple security domains, remediate incidents and enforce compliance.

The potential benefits for organizations that use Cisco Security Cloud are:

• Improve security outcomes: By leveraging AI, Cisco Security Cloud can help organizations close the gap between cybersecurity intent and outcomes, minimize exposure to threats and protect their data and assets.
• Increase efficiency and productivity: By automating repetitive tasks, organizations can boost efficiency and productivity, save time and resources and focus on strategic objectives.
• Gain an edge over the competition: By adopting AI, Cisco Security Cloud can help organizations gain a competitive edge and thrive in the AI-dominated future. You’ll also benefit from Cisco’s Responsible AI Framework, which ensures privacy, security, trust and respect for human rights.

Responsible AI is the practice of designing and using artificial intelligence (AI) systems in a way that respects and protects human values, rights and interests. As AI becomes more powerful and pervasive, it also poses potential risks and challenges, such as bias, discrimination, privacy breaches, security threats and reliability issues.

Cisco has developed a Responsible AI Framework that includes five core aspects.

• Guidance and oversight: Ensure that there are clear rules and directions in place to guide responsible AI development and usage.
• Controls: Manage and mitigate risks associated with AI, such as bias, privacy and security.
• Incident management: A fire alarm system for AI that detects and responds swiftly to any unexpected issues.
• Industry leadership: Take the lead in promoting responsible AI practices across the tech world.
• External engagement: Collaborate with other players such as partners, vendors and customers to create a safer AI landscape for everyone.

The framework is designed to promote the ethics of building safer AI systems across industries. For cybersecurity teams, using responsible AI practices is fundamental as it prevents AI capabilities from being weaponized against end users.

Organizations introducing AI into their legacy systems should make responsible AI a part of their AI strategy to govern its implementation and avoid possible harmful outcomes.

CDW has achieved a gold certification with Cisco, the highest partner status available. CDW has also proven its knowledge and expertise across the Cisco security portfolio and passed a rigorous assessment of its capabilities, earning the Master Security Specialization.

Cisco and CDW can help customers defend their businesses with secure and reliable security solutions across networks, clouds, endpoints and applications. Our security engineers offer expertise in building tailored security solutions that can comprehensively meet your organizational needs.

A hallmark of our security services is that we drive resourceful security investments and meet security objectives within budgets, which positions us among Canada's leading professional security advisory companies.

These are still early days for AI in cybersecurity, but AI should see massive adoption for security. This blog highlights some elementary use cases for cybersecurity administration that will continue to mature and become central to cyberthreat detection and response.

Cisco's innovations in the field can offer a stronger defence against rising cyberattacks in Canada. And CDW's expertise in Cisco's solutions can provide you with seamless and predictable ways to introduce AI capabilities into your security workflows.