312-85 Exam Dumps - Certified Threat Intelligence Analyst (CTIA)

The correct sequence for scheduling a threat intelligence program involves starting with the foundational steps of defining the project scope and objectives, followed by detailed planning and scheduling of tasks. The sequence starts with reviewing the project charter (1) to understand the project's scope, objectives, and constraints. Next, building a Work Breakdown Structure (WBS) (9) helps in organizing the team's work into manageable sections. Identifying all deliverables (2) clarifies the project's outcomes. Defining all activities (8) involves listing the tasks required to produce the deliverables. Identifying the sequence of activities (3) and estimating resources (7) and task dependencies (4) sets the groundwork for scheduling. Estimating the duration of each activity (6) is critical before developing the final schedule (5), which combines all these elements into a comprehensive plan. This approach ensures a structured and methodical progression from project initiation to execution.References:

• "A Guide to the Project Management Body of Knowledge (PMBOK Guide)," Project Management Institute
• "Cyber Intelligence-Driven Risk," by Intel471

Daniel's activities align with those typically associated with organized hackers. Organized hackers or cybercriminals work in groups with the primary goal of financial gain through illegal activities such as stealing and selling data. These groups often target large amounts of data, including personal and financial information, which they can monetize by selling on the black market or dark web. Unlike industrial spies who focuson corporate espionage or state-sponsored hackers who are backed by nation-states for political or military objectives, organized hackers are motivated by profit. Insider threats, on the other hand, come from within the organization and might not always be motivated by financial gain. The actions described in the scenario—targeting personal and financial information for sale—best fit the modus operandi of organized cybercriminal groups.References:

• ENISA (European Union Agency for Cybersecurity) Threat Landscape Report
• Verizon Data Breach Investigations Report

Incorporating a data management requirement in the threat knowledge repository is essential to provide the ability to modify or delete past or irrelevant threat data. Effective data management practices ensure that the repository remains accurate, relevant, and up-to-date by allowing for the adjustment and curation of stored information. This includes removing outdated intelligence, correcting inaccuracies, and updating information as new insights become available. A well-managed repository supports the ongoing relevance and utility of the threat intelligence, aiding in informed decision-making and threat mitigation strategies.References:

• "Building and Maintaining a Threat Intelligence Library," by Recorded Future
• "Best Practices for Creating a Threat Intelligence Policy, and How to Use It," by SANS Institute

For Alice to perform qualitative data analysis, techniques such as brainstorming, interviewing, SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis, and the Delphi technique are suitable. Unlike quantitative analysis, which involves numerical calculations and statistical modeling, qualitative analysis focuses on understanding patterns, themes, and narratives within the data. These techniques enable the analyst to explore the data's deeper meanings and insights, which are essential for strategic decision-making and developing a nuanced understanding of cybersecurity threats and vulnerabilities.References:

• "Qualitative Research Methods in Cybersecurity," SANS Institute Reading Room
• "The Delphi Method for Cybersecurity Risk Assessment," by Cybersecurity and Infrastructure Security Agency (CISA)

The network administrator collected log files generated by a traffic monitoring system, which falls under the category of low-level data. This type of data might not appear useful at first glance but can reveal significant insights about network activity and potential threats upon thorough analysis. Low-level data includes raw logs, packet captures, and other granular details that, when analyzed properly, can help detect anomalous behaviors or indicators of compromise within the network. This type of information is essential for detection and response efforts, allowing security teams to identify and mitigate threats in real-time.References:

• "Network Forensics: Tracking Hackers through Cyberspace," by Sherri Davidoff and Jonathan Ham, Prentice Hall
• "Real-Time Detection of Anomalous Activity in Dynamic, Heterogeneous Information Systems," IEEE Transactions on Information Forensics and Security