The FREE Cybersecurity Glossary by Thor Pedersen!

Diffie-Hellman (DH or D-H): A cryptographic protocol enabling secure key exchange over a public channel, allowing two parties to establish a shared secret key without directly sharing private information. It is foundational for secure communications, underpinning many encryption and secure communication technologies.

DSaaS (Data Science as a Service): A cloud-based service that offers data science capabilities, including analytics, machine learning, and big data processing, without the need for organizations to maintain their own data science infrastructure. DSaaS enables access to advanced tools, algorithms, and expertise, facilitating data-driven decision-making and insights.

Damage Evaluation: A process used to assess the extent and impact of harm caused by an event, such as a cyber-attack, natural disaster, or accident. In a cybersecurity context, this involves analyzing the consequences of a breach or attack, determining which assets were compromised, and estimating the associated costs and operational impacts. It includes identifying data loss, service disruptions, financial implications, and reputational damage. A thorough damage evaluation is crucial for developing an effective recovery plan and mitigating future risks.

Dashboard: In a broad operational sense, a dashboard is a visual display that aggregates and simplifies key information and metrics about the system's operation. In a security context, dashboards are often employed to provide a consolidated view of the organization's security posture, presenting important metrics such as ongoing threats, vulnerabilities, incidents, and overall system health.

Data Aggregation: The process of collecting and summarizing information from multiple sources to achieve a consolidated view. Often used in data analytics, business intelligence, and reporting, it allows for more informed decision-making by presenting a comprehensive picture of collected data for analysis. Aggregation can involve compiling detailed data into summary form, computing sums, averages, counts, or other metrics that provide insight into trends, patterns, or performance across datasets.

Data Analysis: The process of inspecting, cleansing, transforming, and modeling data with the objective of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under various names in different business, science, and social science domains. It typically involves removing noise or inconsistencies from data to highlight meaningful trends and patterns, which can then be used to make informed predictions, decisions, and hypotheses in various areas such as market research, business intelligence, and operational efficiency.