212-82 Exam Dumps : Certified Cybersecurity Technician (CCT)

Capture is the Wireshark menu that Leilani has navigated in the above scenario. Wireshark is a network analysis tool that captures and displays network traffic in real-time or from saved files. Wireshark has various menus that contain different items and options for manipulating, displaying, and analyzing network data. Capture is the Wireshark menu that contains items to start, stop, restart, or save a live capture of network traffic. Capture also contains items to configure capture filters, interfaces, options, and preferences . Statistics is the Wireshark menu that contains items to display various statistics and graphs of network traffic, such as packet lengths, protocols, endpoints, conversations, etc. Main toolbar is the Wireshark toolbar that contains icons for quick access to common functions, such as opening or saving files, starting or stopping a capture, applying display filters, etc. Analyze is the Wireshark menu that contains items to manipulate, display and apply filters, enable or disable the dissection of protocols, and configure user-specified decodes.

To effectively trace unauthorized activities within TechTonic's Windows-based server farm, the best strategy is:

Centralized Logging:

Aggregation: Collect all system logs in a centralized logging server. This ensures that all log data is stored in one place, making it easier to manage and analyze.

Correlation: Correlate logs from different sources to identify patterns and anomalies that might indicate unauthorized activities.

Pattern-Detection Algorithms:

Automated Analysis: Use algorithms to automatically detect patterns that are indicative of security breaches. This can include machine learning models trained to recognize signs of intrusion.

Real-Time Alerts: Set up real-time alerts for suspicious activities identified by the pattern-detection algorithms, enabling swift responses to potential threats.

References:

Best practices for Windows logging and monitoring:Microsoft Docs

Centralized logging solutions and their benefits: Splunk Documentation

 A data-driven hunting method is a type of threat hunting method that employs existing data collected from various sources, such as DNS and proxy logs, to generate and test hypotheses about potential threats. This method relies on data analysis and machine learning techniques to identify patterns and anomalies that indicate malicious activity. A data-driven hunting method can help discover unknown or emerging threats that may evade traditional detection methods. An entity-driven hunting method is a type of threat hunting method that focuses on specific entities, such as users, devices, or domains, that are suspected or known to be involved in malicious activity. A TTP-driven hunting method is a type of threat hunting method that leverages threat intelligence and knowledge of adversary tactics, techniques, and procedures (TTPs) to formulate and test hypotheses about potential threats. A hybrid hunting method is a type of threat hunting method that combines different approaches, such as data-driven, entity-driven, and TTP-driven methods, to achieve more comprehensive and effective results.