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The CompTIA CS0-002 certification exam covers a wide range of cybersecurity topics, including threat and vulnerability management, security operations and monitoring, incident response, and compliance and assessment. These topics are essential for cybersecurity professionals, as they are the core components of effective cybersecurity management. The exam is designed to test the candidate's ability to apply this knowledge to real-world scenarios, which makes it a very practical certification.
The CompTIA Cybersecurity Analyst (CySA+) Certification is a vendor-neutral certification offered by the Computing Technology Industry Association (CompTIA). The exam, designated as CS0-002, is designed to validate the skills and knowledge of professionals who work in the field of cybersecurity analysis. This certification is intended for individuals who have at least four years of experience in the field of cybersecurity and wish to advance their career by demonstrating their expertise in cybersecurity analysis.
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CompTIA Cybersecurity Analyst (CySA+) Certification Exam Sample Questions (Q164-Q169):NEW QUESTION # 164
A user's computer has been running slowly when the user tries to access web pages. A security analyst runs the command netstat -aon from the command line and receives the following output:
Which of the following lines indicates the computer may be compromised?
Answer: F
NEW QUESTION # 165
A security analyst was transferred to an organization's threat-hunting team to track specific activity throughout the enterprise environment The analyst must observe and assess the number ot times this activity occurs and aggregate the results. Which of the following is the BEST threat-hunting method for the analyst to use?
Answer: A
NEW QUESTION # 166
A SIEM alert occurs with the following output:
Which of the following BEST describes this alert?
Answer: D
NEW QUESTION # 167
Which of the following describes the mam difference between supervised and unsupervised machine-learning algorithms that are used in cybersecurity applications?
Answer: D
Explanation:
Supervised and unsupervised machine-learning algorithms are two types of machine-learning methods that are used in cybersecurity applications. Machine learning is a branch of artificial intelligence that enables systems to learn from data and improve their performance without explicit programming.
Supervised machine-learning algorithms are trained on labeled data, which means that each data point has a known outcome or class. Supervised algorithms learn to map input data to output data by finding patterns or rules from the training data. Supervised algorithms require security analyst feedback to provide labels for the data and evaluate the accuracy of the algorithm's predictions. Examples of supervised machine-learning algorithms are classification and regression.
Unsupervised machine-learning algorithms are trained on unlabeled data, which means that each data point has no known outcome or class. Unsupervised algorithms learn to discover hidden structures or patterns from the data without any guidance or feedback. Unsupervised algorithms do not require security analyst feedback, as they do not rely on predefined labels or outcomes. Examples of unsupervised machine-learning algorithms are clustering and anomaly detection.
NEW QUESTION # 168
An organization was alerted to a possible compromise after its proprietary data was found for sale on the Internet. An analyst is reviewing the logs from the next-generation UTM in an attempt to find evidence of this breach. Given the following output:
Which of the following should be the focus of the investigation?
Answer: B
NEW QUESTION # 169
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