% generated by tables/make_tables.py from ./literature_synthesis/landmarks/security_privacy_landmarks.csv
\begin{table}[htbp]\centering\caption{Composition of the automatically selected landmark set of the security-and-privacy area, by category.}\label{tab:security_landmarks}
\begin{threeparttable}\small
\begin{tabular}{lrrrrrrrrr}
\toprule
\textbf{Category} & \textbf{Works} & \textbf{Post-period} & \textbf{Dated 2026} & \textbf{Articles} & \textbf{Conf.} & \textbf{Preprints} & \textbf{Grey} & \textbf{Abstract} & \textbf{No DOI} \\
\midrule
Cybersecurity & 25 & 16 & 9 & 13 & 1 & 1 & 10 & 20 & 5 \\
Applied cryptography & 25 & 15 & 8 & 11 & 2 & 0 & 12 & 18 & 1 \\
Blockchain systems & 25 & 6 & 2 & 14 & 1 & 5 & 5 & 19 & 0 \\
Privacy-preserving computation & 25 & 14 & 8 & 16 & 3 & 1 & 5 & 21 & 1 \\
Federated learning & 25 & 15 & 6 & 18 & 4 & 0 & 3 & 14 & 2 \\
\bottomrule
\end{tabular}
\begin{tablenotes}\footnotesize\item Landmarks are the works with the highest field-normalised 36-month citation score (NCS36; 2025--2026 works ranked by 12-month citations) within each primary category, with a floor of fifteen per category, plus the 200 most cited works of the corpus overall (\texttt{literature\_synthesis/select\_landmarks.py}). Grey = dissertations, reports, book chapters and books as typed by OpenAlex. Abstract = works whose abstract is available in the metadata; the synthesis of Part VII reads these abstracts only, never full texts. The set is flagged for principal-investigator review; Part VII documents the records that are duplicates, misdated or misclassified.\end{tablenotes}
\end{threeparttable}\end{table}