P.S. JPNTestがGoogle Driveで共有している無料かつ新しい300-745ダンプ：https://drive.google.com/open?id=1x8fbyjEYKWis4qLK-BmF4E1QYVjMEVFU
当社の300-745トレーニング資料は国内外で有名です。主な理由は、コア競争力を持たない他の会社があるためです。市場には多くの複雑な類似製品があります。独自に必要です。他の製品との300-745テストの質問は、300-745学習教材を更新する最も中核的な専門家チームがあることです。製品のポイント。
| トピック | 出題範囲 |
|---|---|
| トピック 1 |
|
| トピック 2 |
|
| トピック 3 |
|
| トピック 4 |
|
JPNTestのCiscoの300-745試験トレーニング資料は全てのIT認定試験に通用します。JPNTestのCiscoの300-745試験トレーニング資料は豊富な経験を持っている専門家が長年の研究を通じて開発されたものです。その権威性は言うまでもありません。もしCiscoの300-745問題集は問題があれば、或いは試験に不合格になる場合は、全額返金することを保証いたします。
質問 # 69
A global energy company moved a monolithic application from the data center to public cloud. Over time, the company added many capabilities to the application, and it is now difficult for the application team to scale it.
The application owner decided to modernize the application by moving to a Kubernetes cluster. However, he wants to ensure that the new application architecture provides a container network interface that is scalable, offers options for cloud-native security, and helps with visibility and observability. Which solution must be used to accomplish the task?
正解：A
解説：
In the realm of modern application security and Kubernetes networking,Ciliumhas emerged as the industry- standardContainer Network Interface (CNI)that leverageseBPF (extended Berkeley Packet Filter) technology. For a global company modernizing a monolithic app into microservices, Cilium provides the required scalability and high-performance networking by operating directly within the Linux kernel.
Unlike traditionalSecurity Groups(Option A) which are often limited to IP-based rules at the cloud infrastructure level, orENIs(Option C) which are AWS-specific hardware interfaces, Cilium providesidentity- awaresecurity. It understands Kubernetes labels and metadata, allowing for granular Layer 7 policy enforcement. Furthermore, Cilium addresses the "visibility and observability" requirement through itsHubble component, which provides deep insights into network flows, application dependencies, and security events without the overhead of traditional sidecar proxies. AnIngress Gateway(Option D) manages external traffic entering the cluster but does not provide the comprehensive pod-to-pod networking, eBPF-based security, or internal observability that a CNI like Cilium offers. Designing with Cilium aligns with Cisco's focus on cloud- native security and the use of eBPF for distributed firewalling and telemetry in modern application environments.
========
質問 # 70
After deploying a new API, the security team must identify the components of the application that are exposed to the internet and whether there are application authentication risks. Which technology must be deployed to discover the applications services and monitor for authentication issues?
正解：D
解説：
Securing APIs requires visibility into the "runtime" behavior of the application.API trace analysis(often part of anAPI Securitysolution like Cisco Panoptica) is the technology used to automatically discover API endpoints and analyze the traffic flowing through them. This process identifies "shadow APIs" (undocumented endpoints) that are exposed to the internet and inspects the headers and payloads for authentication risks, such as missing tokens or broken object-level authorization (BOLA).
By monitoring actual traffic traces, the security team can confirm if the API is following the intended security design or if it is leaking sensitive data due to poor authentication implementation.Cloud Security Posture Management (CSPM)(Option A) focuses on the configuration of the cloud infrastructure (like an open S3 bucket) rather than the internal logic of an API's authentication.Secret scanning(Option C) is a "shift-left" technique used to find hardcoded passwords in source code during the build phase, not for monitoring live traffic.Cloud Workload Protection (CWPP)(Option D) focuses on protecting the underlying host or container from malware and exploits. Only API trace analysis provides the specific visibility into service discovery and application-layer authentication health required in the Cisco SDSI v1.0 objectives for modern DevSecOps environments.
質問 # 71
Which generative AI impact is addressed by a human-in-the-loop design policy?
正解：A
解説：
A human-in-the-loop design policy ensures that humans validate or oversee AI-generated outputs, reducing the risk of AI hallucinations (false or misleading information generated by AI).
This provides accountability and accuracy in generative AI use.
質問 # 72
What does watermarking AI generated content prevent?
正解：A
解説：
In the realm of Artificial Intelligence and DevSecOps,watermarkingis a critical security technique used to identify the origin of synthetic media. As generative AI models become increasingly sophisticated, they can create highly realistic images, videos, and audio clips-often referred to asdeep fakes. These deep fakes pose a significant risk to organizational security and public trust, as they can be used for sophisticated social engineering attacks, such as impersonating executives in "Business Email Compromise" (BEC) scenarios or spreading misinformation.
By embedding a cryptographic or perceptible watermark into AI-generated content, security systems and users can verify the authenticity and provenance of the media. This proactive measure helps prevent the successful deployment of deep fakes by making it easier for automated security tools to flag synthetic content that lacks a valid "signature" of origin. While watermarking does not inherently stop the creation ofharmful content(Option C) or reduceresource consumption(Option A), it provides a layer of accountability and verification. Similarly,scale changes(Option D) are technical image manipulations that watermarking does not prevent. Within the Cisco SDSI framework, watermarking is viewed as an essential component of the AI security lifecycle, ensuring that generative technologies are used responsibly and that synthetic content is distinguishable from genuine data.
========
質問 # 73
What is a use for AI in securing network infrastructure?
正解：C
解説：
In the architecture of modern security, Artificial Intelligence (AI) and Machine Learning (ML) are leveraged to move beyond reactive, signature-based defenses. One of the most significant uses of AI in securing network infrastructure is the detection ofzero-day attacks(often referred to in exam contexts as "day zero" attacks). A zero-day attack exploits a vulnerability that is unknown to the software vendor or the public, meaning no signature exists for traditional firewalls or antivirus software to block it.
AI identifies these threats throughbehavioral analysisandanomaly detection. By establishing a highly granular baseline of "normal" network traffic patterns-including flow direction, packet size, inter-packet arrival times, and protocol behavior-AI models can detect subtle deviations that indicate a malicious exploit.
For example,Cisco Secure Network Analytics(formerly Stealthwatch) andEncrypted Threat Analytics (ETA)use ML to identify the cryptographic "fingerprints" of malware even within encrypted traffic, without the need for decryption. This allows the security infrastructure to identify and mitigate threats at the moment they appear, rather than waiting for a vendor to release a signature. While load balancing (Option B), traffic shaping (Option C), and Quality of Service (Option D) are critical for network performance and availability, they are traditional traffic engineering functions that do not inherently provide the advanced threat detection capabilities offered by AI-driven security models. Within the Cisco SDSI objectives, AI is positioned as the primary technology for achieving proactive visibility and reducing the "Mean Time to Detect" (MTTD) for previously unseen vulnerabilities.
質問 # 74
......
他人の気付いていないときに、だんだんCiscoの300-745試験成功したいのですか？我が社はIT資格認証試験資料の販売者として、いつまでもできご客様に相応しく信頼できる300-745問題集を提供できます。あなたのすべての需要を満たすためには、一緒に努力します。躊躇われずに我々の模試験を利用してみてください。全力を尽くせば、300-745試験の合格も可能となります。
300-745資格講座: https://www.jpntest.com/shiken/300-745-mondaishu
BONUS！！！ JPNTest 300-745ダンプの一部を無料でダウンロード：https://drive.google.com/open?id=1x8fbyjEYKWis4qLK-BmF4E1QYVjMEVFU