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| Section | Objectives |
|---|---|
| Network Optimization and Management | - Monitoring and Troubleshooting
|
| AI in Network Security | - Threat Detection
|
| AI and Networking Fundamentals | - Core Networking Concepts
|
| Network Technologies | - Software-Defined Networking (SDN)
|
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NEW QUESTION # 28
(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?)
Answer: C
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 # 29
(How are devices within a VNET able to communicate with devices on other networks?)
Answer: A
Explanation:
Devices within a Virtual Network (VNET) communicate with devices on other networks through routing mechanisms that determine the best path for traffic. AI+ Network foundational networking documents explain thatrouting protocolsor static routing configurations enable Layer 3 connectivity between separate IP networks.
Routing protocols such as OSPF, BGP, or static routes allow routers and virtual gateways to exchange network reachability information. This ensures that packets can traverse different network segments, cloud regions, or on-premise environments. Without routing, devices would be limited to local subnet communication only.
NAT may be used for address translation but does not itself enable network-to-network communication.
Defining IP subnets establishes network boundaries but does not provide connectivity. Layer 2 switching operates within the same broadcast domain and cannot forward traffic across different networks.
AI+ Network training materials consistently reinforce that routing is the core mechanism enabling inter- network communication in both physical and virtualized environments.
NEW QUESTION # 30
(What is a key advantage of using Ansible for network automation?)
Answer: D
Explanation:
Ansible's key advantage in network automation is itsagentless architecture, which allows devices to be managed without installing additional software on them. AI+ Network automation documentation emphasizes that Ansible uses standard protocols such as SSH and APIs to communicate with network devices, making deployment simple and scalable.
This design significantly reduces operational overhead and security risks associated with maintaining agents across hundreds or thousands of devices. Ansible playbooks, written in YAML, define desired configurations in a clear, human-readable format, improving collaboration and reducing configuration errors.
Unlike Chef, which relies on Ruby-based cookbooks, Ansible does not require specialized programming knowledge. It also supports a wide range of vendors and platforms beyond Linux. AI+ Network materials consistently position Ansible as an efficient, low-complexity automation tool ideal for both enterprise and multi-vendor network environments.
NEW QUESTION # 31
(How can SDN controllers enhance VNET management?)
Answer: C
Explanation:
Software-Defined Networking (SDN) controllers enhance Virtual Network (VNET) management primarily through automated task provisioning. AI+ Network documentation explains that SDN introduces a centralized control plane that separates network intelligence from the data plane, enabling programmatic control of network behavior.
With SDN controllers, administrators can automatically provision network services such as routing, access control, segmentation, and bandwidth allocation across virtual networks. This automation reduces manual configuration errors and ensures consistency across large-scale environments. SDN controllers also enable rapid deployment of new services, dynamic policy enforcement, and real-time network optimization.
Options such as decentralized control and simplified local configuration contradict SDN's centralized, policy- driven design. Limited visibility is the opposite of SDN's advantage, as SDN provides enhanced, global visibility into network state. AI+ Network materials emphasize SDN controllers as key enablers of scalable, agile, and automated VNET management.
NEW QUESTION # 32
(How can ChatGPT assist network administrators in understanding complex networking concepts?)
Answer: C
Explanation:
ChatGPT assists network administrators by providing detailed explanations and examples through natural language interaction. AI+ Network documentation describes conversational AI as a powerful knowledge- support tool that helps engineers understand complex networking concepts, protocols, configurations, and troubleshooting workflows.
Through interactive dialogue, ChatGPT can break down advanced topics such as routing protocols, automation frameworks, AI-driven optimization, and security models into clear, understandable explanations.
It can also provide contextual examples, configuration snippets, and step-by-step guidance tailored to the user' s level of expertise.
ChatGPT does not directly simulate networks, manage traffic, or monitor live environments. Instead, its value lies inknowledge acceleration, decision support, and learning enhancement, making it an effective assistant for both novice and experienced network professionals. AI+ Network materials emphasize AI assistants as key enablers of faster learning and operational efficiency.
NEW QUESTION # 33
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