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[General] 2026 Positive AT-510 Feedback | High-quality AT-510 Interactive Questions: AI+ N

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【General】 2026 Positive AT-510 Feedback | High-quality AT-510 Interactive Questions: AI+ N

Posted at yesterday 08:22      View：5 | Replies：1        Print      Only Author   [Copy Link] 1#
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AI CERTs AI+ NetworkExamination Sample Questions (Q20-Q25):NEW QUESTION # 20
(Which system is best for detecting unauthorized logins and adapting to new threats?)
  • A. Reactive AI
  • B. Static firewalls
  • C. Machine learning-driven intrusion detection
  • D. Load balancers
Answer: C
Explanation:
Machine learning-driven intrusion detection systems (IDS) are best suited for detecting unauthorized logins and adapting to emerging threats. AI+ Network security documentation highlights ML-driven IDS as systems that continuously learn from historical and real-time data to identify abnormal behavior.
Unlike static firewalls, which rely on predefined rules, ML-based IDS can detect novel attack patterns, brute- force attempts, and compromised credentials. They adapt over time, improving detection accuracy and reducing false positives.
Load balancers are unrelated to security monitoring, and reactive AI responds after incidents rather than proactively detecting them. AI+ Network materials consistently identify machine learning-driven IDS as a core component of modern, adaptive cybersecurity architectures.

NEW QUESTION # 21
(How do AI frameworks simplify model development for networking solutions?)
  • A. By focusing only on manual coding for each specific model.
  • B. By limiting model designs to a single use case.
  • C. By providing pre-built algorithms to abstract low-level details.
  • D. By requiring advanced expertise in deep learning for all implementations.
Answer: C
Explanation:
AI frameworks simplify model development for networking solutions by providing pre-built algorithms and abstractions that hide low-level implementation complexity. According to AI+ Network documentation, frameworks such as TensorFlow, PyTorch, and specialized networking AI libraries enable engineers to focus on problem-solving rather than mathematical and architectural details.
These frameworks include optimized libraries for data processing, training, validation, and deployment, significantly reducing development time. In networking use cases-such as traffic prediction, anomaly detection, and performance optimization-pre-built models can be adapted quickly without designing algorithms from scratch.
Contrary to requiring advanced deep learning expertise, AI frameworks lower the entry barrier for network engineers by offering modular components and reusable templates. They also support scalability and integration with automation platforms, aligning with AI+ Network goals of agility and efficiency.
Limiting models to a single use case or relying solely on manual coding contradicts the purpose of frameworks. AI+ Network materials clearly position AI frameworks as accelerators for innovation in intelligent networking solutions.

NEW QUESTION # 22
(Which tool is most effective for real-time monitoring of compliance with a clean desk policy?)
  • A. NetBox for compliance visualization.
  • B. Zabbix for real-time desk inspections.
  • C. Zabbix for real-time data analysis.
  • D. NetBox for periodic compliance checks.
Answer: C
Explanation:
Zabbix is the most effective tool for real-time monitoring when continuous data analysis is required. AI+ Network operational monitoring documentation explains that Zabbix is designed for real-time monitoring, alerting, and analytics across IT systems.
While Zabbix does not perform physical inspections, it can integrate with sensors, access logs, cameras, or environmental monitoring systems that support clean desk policy enforcement. Its real-time data processing and alerting capabilities allow immediate detection of policy violations.
NetBox is primarily used for network documentation and infrastructure modeling, making it more suitable for visualization and periodic audits rather than real-time enforcement. AI+ Network materials emphasize Zabbix' s strength in live monitoring and automated alerting workflows.

NEW QUESTION # 23
(A large-scale enterprise faces frequent DNS spoofing attacks and requires a system that can classify DNS domains dynamically, detect potential threats, and integrate seamlessly into its network environment without manual intervention.
Which tool is best suited?)
  • A. AIEngine, providing programmable packet inspection and DNS domain classification.
  • B. PentestGPT, which identifies vulnerabilities during penetration testing.
  • C. Open-AppSec, which focuses on securing web applications and APIs.
  • D. DeepSlice, which focuses on load management in 5G networks.
Answer: A
Explanation:
AIEngine is the most suitable tool for defending against DNS spoofing attacks through dynamic DNS domain classification and programmable packet inspection. AI+ Network security documentation explains that AIEngine operates directly within the network fabric, enabling real-time inspection of DNS traffic and automated response to suspicious domains.
By leveraging AI-driven classification, AIEngine can detect malicious or spoofed DNS queries without relying solely on static signatures. Its seamless integration into the network allows automatic mitigation actions such as blocking, rerouting, or alerting, all without manual intervention.
DeepSlice addresses 5G slicing optimization, PentestGPT focuses on vulnerability discovery rather than live defense, and Open-AppSec is limited to application-layer security. AI+ Network frameworks clearly position AIEngine as an adaptive, inline security and traffic management solution.

NEW QUESTION # 24
(Scenario: A multinational corporation faces an issue where employees working remotely often connect to corporate resources using unsecured devices. Despite enforcing strong password policies, they still encounter breaches due to compromised endpoints. The security team needs a strategy to ensure only compliant devices can access sensitive resources while minimizing user disruption.
Question: What approach should the corporation adopt to resolve this issue?)
  • A. Restrict remote access entirely to prevent breaches from unsecured devices.
  • B. Deploy network segmentation to isolate critical resources from remote access.
  • C. Implement Zero Trust Architecture to verify user and device compliance.
  • D. Enforce stricter password policies to enhance user authentication security.
Answer: C
Explanation:
Implementing a Zero Trust Architecture (ZTA) is the most effective approach for securing access from remote and potentially unsecured devices. AI+ Network security documentation explains that Zero Trust operates on the principle of "never trust, always verify," requiring continuous validation of both user identity and device posture before granting access.
Unlike traditional perimeter-based security, Zero Trust evaluates device compliance factors such as operating system health, patch status, and endpoint security controls. Access is granted dynamically and contextually, minimizing disruption while significantly reducing risk. Even authenticated users are restricted to least- privilege access.
Stricter passwords alone do not address compromised endpoints, and completely restricting remote access harms productivity. Network segmentation helps limit damage but does not verify endpoint integrity. AI+ Network frameworks clearly identify Zero Trust as the preferred model for modern, distributed workforces.

NEW QUESTION # 25
......
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Posted at yesterday 08:39        Only Author  2#
The article was incredibly insightful and profound. Wish me all the success I can get for the New study questions 312-38 free exam!
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