Template 2: electric boogaloo

.gitignore

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+razpored*
+
+# Don't commit the final PDF files
+*.pdf
+
+# The seminarske/ folder should be left empty
+seminarske/*
+!seminarske/.gitkeep
+
+# Core latex/pdflatex auxiliary files:
+*.aux
+*.lof
+*.log
+*.lot
+*.fls
+*.out
+*.toc
+*.fmt
+*.fot
+*.cb
+*.cb2
+.*.lb

README.md

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+# UL FRI DF journal template
+
+## How to use
+
+Everything that you need to edit is in the `edit_this` folder. You shouldn't have to touch anything else. The top of each file contains instructions for what to do.
+
+## Compiling
+
+The easiest way to compile this is using `tectonic`. Simply run `tectonic main.tex` in the root of the repository and you'll get a `main.pdf` file out.
+
+## Using LLMs
+
+I happened to be experimenting with LLMs a lot the week that I had to do this, so natually I wanted to see how useful they might be to automate some of this work.
+
+The first thing you'll probably want to do is textify all the pdfs so the LLM can read them.
+
+```sh
+find seminarske/*.pdf -exec pdftotext -raw {} \;
+```
+
+You'll also want to make a "razpored.txt" file with the works ordered by categories. If you got a pptx file, this will do:
+
+```sh
+libreoffice --headless --invisible --convert-to pdf razpored.pptx
+pdftotext razpored.pdf
+```
+
+Then you can have some fun with your robot intern. These prompts were tested in late 2025, in the Zed IDE, using the Claude Sommet 4 model. YMMV
+
+PDF includes:
+
+> The "seminarske" folder contains pdf journal submissions with their corresponding .txt version. The first few lines of each file contain the title. Write and execute a shell one-liner to extract the titles corresponding to the file names into your context.
+Read the "razpored.txt" file to map titles to categories.
+> Write the following latex command for each of the works, keeping their order from razpored.txt intact:
+> \includework
+> {Title of category}
+> {seminarske/name_of_the_file.pdf}
+> {Full title of the work}
+
+Summaries:
+
+> You now need to look through each of the files and extract the abstract and keywords. It should be in the first hundred lines.
+> For each work, output in the following form:
+>  \subsection{Full title of the work}
+>  Full, unchanged abstract goes here
+> \textbf{Keywords:} copy, the, keywords, here
+> For abstracts in non-english, use the same term they used for keywords (e.g. Ključne besede)
+> Process and output them in markdown blocks one at a time so you don't fill up your context window and make mistakes.

edit_this/10-variables.tex

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+% This is the beginning of the school year (e.g. for 2025/26 it should be 2025)
+\newcommand{\currentyear}{2025}
+% This should include at least Andy and YOU - the person compiling this
+\newcommand{\editors}{Andrej Brodnik, Miha Frangež}

edit_this/30-introduction.tex

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+\newcommand{\introauthor}{Miha Frangež}
+%
+% The first few paragraphs don't really change between years
+%
+Digital forensics is a pivotal branch of forensic science dedicated to the recovery and investigation of materials found in
+digital devices. Originally synonymous with computer forensics, the field of digital forensics has expanded significantly
+to encompass the examination of all digital data storage devices. Its roots can be traced back to the personal computer
+revolution of the late 1970s and early 1980s, evolving through the 1990s without formal organization until the emergence
+of national guidelines in the 21st century.
+\par
+Digital forensic investigations serve diverse purposes, primarily to substantiate or challenge hypotheses in both criminal
+and civil court proceedings. In criminal cases, these investigations support allegations of offenses such as murder, theft,
+and personal assault. In civil cases, they safeguard individuals’ rights and property, often addressing disputes ranging
+from family matters to contractual conflicts among economic entities. The field also extends into electronic discovery,
+crucial in modern litigation.
+\par
+This conference gathers the seminar papers of master’s students at the Faculty of Computer Science and Information,
+University of Ljubljana \currentyear/\nextyear. It explores a variety of topics including mobile forensics, logs, password forensics
+and cyphering, browser forensics and forensic investigation. Each paper contributes to the ongoing development and
+application of digital forensic techniques, enhancing our ability to navigate the complexities of today’s digital landscape.
+In mobile forensics, three seminar papers provide valuable insights. The first paper addresses data recovery from
+damaged devices, highlighting challenges in accessing data without owner-provided access. The second paper evaluates
+smartphone backup integrity, focusing on iPhone and Android systems. The third paper examines MOBILedit Forensic
+Express for retrieving digital evidence, emphasizing complexities in accessing messaging app data amid evolving security
+measures.
+%
+% Here, add a one-paragraph summary for each of the categories/topics
+%
+
+% TODO: do this

edit_this/50-summaries.tex

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+%
+% For each work, add a \subsection with its title, followed by the abstract and keywords, copied from the work
+%
+
+
+\subsection{WARNE: Orodje za zbiranje dokazov o zalezovalski programski opremi}
+Intimnopartnersko nasilje pogosto vključuje uporabo zalezovalskih aplikacij, katere storilci namestijo na žrtvino mobilno napravo in s tem posegajo v njeno zasebnost. V članku opišemo delovanje programske opreme WARNE. To je forenzično orodje za prepoznavo takšnih aplikacij in zbiranje dokazov o identiteti zalezovalca. Orodje je uspešno odkrilo pomanjkljivosti pri 20 od 30 testiranih zalezovalskih aplikacijah in s tem pokazalo velik potencial za pomoč žrtvam in preiskovalcem.
+
+\textbf{Ključne besede:} zalezovalske aplikacije, digitalna forenzika, varnost mobilnih naprav, intimnopartnersko nasilje, IPN
+
+\subsection{How to detect cryptocurrency miners? By traffic forensics!}
+The paper by Veselý and Žádník presents a hybrid approach for detecting cryptocurrency mining traffic in large-scale network environments. Using flow-level features extracted from data collected in a national academic network, a labeled dataset was constructed through a semi-automated annotation process involving both passive analysis and active probing, enhanced by leveraging the sMaSheD catalog of known mining pool addresses. Two classifiers were developed and evaluated: a manually tuned rule-based classifier and a supervised machine learning model. The manual classifier serves as an interpretable baseline, relying on heuristic feature thresholds, while the machine learning model demonstrates superior accuracy and generalization. Evaluation results show a significant reduction in false positives and false negatives with the ML-based detector. A two-step detection schema, combining statistical classification with behavioral confirmation via active probes, further enhances precision and reliability. The findings confirm that mining traffic exhibits distinct, detectable characteristics, and that combining machine learning with domain knowledge, along with up-to-date mining pool information, provides an effective solution for real-world deployment.
+
+\textbf{Keywords:} Traffic forensics, Cryptocurrency, Cryptojacking, Mining pool
+
+\subsection{Was the clock correct? Timestamps and time anchors across operating systems}
+Accurate event reconstruction in digital forensics depends on the integrity of system-generated timestamps, yet operating-system clocks are often misaligned with real time because of drift, battery failure or deliberate tampering. The authors formalise this problem by introducing time anchors: artefacts that embed both a local timestamp supplied by the device and an external timestamp issued by an independent source. By comparing the two we can quantify clock skew at the moment an artefact is created and label events as anchoring (verifiable) or non-anchoring. The authors also define time anomalies — inconsistent skews or impossible temporal sequences — that signal manipulation or hardware faults. Two controlled Windows 10 experiments validate the approach. First, Google-search artefacts (browser history, cache entries and server logs) were collected with the system clock set correctly and then shifted three hours behind real time. The skew measured in each anchoring artefact precisely matched the imposed offset and exposed the unreliability of non-anchoring events. A second experiment repeated the procedure for local file creation, demonstrating how non-anchoring events can be corrected once neighbouring anchors establish the true skew. Our addition is a review of methods of timestamp manipulations on Linux system, in which we review how to spot a faked timestamp using the touch command, extended file attributes, and journal history.
+
+\textbf{Keywords:} timestamp, time shift, time anchor, OS forensics
+
+\subsection{Enhancing speaker identification in criminal investigations through clusterization and rank-based scoring}
+Speaker identification is a crucial task in criminal investigations, but analyzing large volumes of noisy audio and comparing them with extensive databases often leads to a high rate of false positives when using standard methods. This paper presents an approach to improve the identification of forensic speakers by combining state-of-the-art speaker embeddings with clustering and a rank-based scoring mechanism. The method extracts embeddings using an ECAPA-TDNN model, groups audio segments using HDBSCAN, and applies a rank-adjusted scoring system. Experiments demonstrate that this approach significantly reduces the number of potential candidates requiring manual review compared to baseline methods, making the investigation process more efficient and manageable in real-world forensic scenarios.
+
+\textbf{Keywords:} Digital forensic, Speker identification, Clusterization, Audio analysis, Scoring
+
+\subsection{Oblačna forenzična analiza Amazon iRobot Roomba sesalca}
+Članek predstavlja možnost uporabe avtonomnih naprav, kot je Amazonov-ova iRobot Roomba, za preiskovanje zločinov. Kot mnogo drugo IoT naprav tudi Roomba zbira in hrani kup podatkov o uporabi, lokaciji, sobah in pohištvu v stanovanju, časovne žige, metapodatke in drugo. Ti podatki bi lahko bili zelo koristni pri raziskavi zločinov, saj nam bi lahko podali dragocene informacije o poteku dogodkov. Avtorji so najprej analizirali vse API dostopne točke, preko katerimh Roomba komunicira s strežnikom, nato pa jih uporabili za razvoj nove odprtokodne aplikacije PyRoomba, ki izboljša uradno Roombino aplikacijo, tako da doda več podrobnosti in izriše bolj natančne 2D zemljevide prostorov, v katerih je sesalec aktiven. Aplikacija je bila nato testirana v več različnih prostorih z različno velikostjo in številom objektov, nato pa je bila še simulirana scena umora, kjer so na tla položili truplo in več nožev, ter testirali, ali jih bo Roomba zaznala. Preizkusi so se izkazali za uspešne, saj je sesalec identificiral dodatne ovire, ki se povezane z umorom.
+
+\textbf{Ključne besede:} Digitalna forenzika, Forenzika interneta stvari, Oblačna forenzika, Amazon iRobot Roomba
+
+\subsection{Hit and run: Forensic vehicle event reconstruction through driver-based cloud data from Progressive's snapshot application}
+This paper provides a summary and critical analysis of a pioneering study by Onik et al. (2024) on the forensic analysis of the Snapshot application from Progressive Insurance. Driving Insurance Applications (DIAs) gather extensive data on driver behavior, yet their cloud-based data repositories remain a largely untapped resource for forensic investigations. The original study developed PyShot—an open-source Python tool—to extract granular data from the Progressive cloud, much of which is inaccessible via the standard user interface. It investigated the accuracy of Snapshot's location and speed data, its resilience against GPS spoofing, and its ability to provide detailed event information for reconstructing a simulated hit-and-run scenario. This seminar paper evaluates the methodology and findings of that work, contextualizes it within the broader field of vehicle and cloud forensics, and discusses its implications. The findings confirm that telematics cloud data offers a robust and reliable new avenue for investigating traffic incidents and crimes, even when faced with user tampering.
+
+\textbf{Keywords:} Driving insurance application (DIA), Vehicle forensics, Digital forensics, Snapshot, Driving patterns, Cloud forensics
+
+\subsection{Grand Theft API: A Forensic Analysis Of Vehicle Cloud Data}
+Modern cars collect and send meaningful amount of data to manufacturer cloud systems. This situation creates new possibilities for modern digital forensic investigations. In this paper, we look at how investigators can get vehicle cloud data directly through manufacturer APIs, using login details taken from suspects' mobile devices. We explain the basics of vehicle forensics, look at current methods for getting vehicle cloud data, and show how API-based methods work in practice. After analyzing 23 different vehicle apps and manually testing with Mercedes-Benz and BMW cars, we found that a significant amount of vehicle data can be accessed through these APIs. This includes current car status, location, and personal info. Our research shows that using APIs to get vehicle cloud data gives valuable information for forensic investigations. This approach could change how evidence is collected from modern vehicles. It represents a step forward in digital vehicle forensics and allows access to both real-time and historical vehicle data while following proper forensic principles.
+
+\textbf{Keywords:} Vehicle Forensics, API-based Acquisition, Digital Forensics, Telemetry Data, Cloud Forensics
+
+\subsection{Applying digital stratigraphy to the problem of recycled storage media}
+This report provides an overview of a study by Schneider et al. (2024) that applied digital stratigraphy to recycled storage media in a forensic context. The main goal of that research was to determine whether this technique can distinguish older residual data from new data on a reused device, especially when such fragments are found in unallocated space without metadata. The methodology relies on the concept of digital stratigraphy – adapted from geology – to analyze how file fragments are layered on disk over time. Schneider et al. implemented an automated file system simulation framework that systematically creates, modifies, and deletes files using real file system drivers, generating realistic layers of data for analysis. Experiments showed that examining these data layers and observing file system behavior can reveal stratigraphic markers indicating a fragment's likely origin. These markers help investigators infer whether a recovered file fragment originated from the device's previous usage or the current user's activities. While the digital stratigraphy approach cannot definitively attribute every fragment, it significantly improves data provenance assessment on recycled storage media when conventional file metadata is absent.
+
+\textbf{Keywords:} Digital stratigraphy, File System Upper Bound (FSUB), Data layering, Recycled Storage Media, Forensic analysis
+
+\subsection{Forenzični vidiki zloženih datotečnih sistemov}
+Članek obravnava izzive forenzične analize zloženih datotečnih sistemov, ki so postali bolj kompleksni zaradi večslojnih arhitektur in naprednih funkcij, kot je npr. šifriranje. Tradicionalne forenzične tehnike niso primerne za te sisteme, saj zahtevajo analizo tako zgornjih kot spodnjih slojev datotek. Predlagan je nov model, ki vključuje fazo za prepoznavanje indikatorjev in analizo časovnih žigov. Za preverjanje učinkovitosti modela so avtorji izvedli študijo primerov na sistemih MooseFS, GlusterFS in eCryptfs, pri čemer so prepoznali ključne forenzične izzive teh sistemov, kot sta fragmentacija in prisotnost skritih podatkov. Model omogoča izboljšanje forenzične preiskave z obnovo izbrisanih datotek in celovitejšo analizo datotečnih sistemov.
+
+\textbf{Ključne besede:} Zloženi datotečni sistemi, Forenzična analiza, Digitalna forenzika
+
+\subsection{Forenzična analiza naprave Steam Deck: Predstavitev in razširitev članka Well Played, Suspect!}
+V članku analiziramo področje digitalne forenzike na igralnih konzolah in igrah. Osredotočamo se predvsem na članek Well Played, Suspect!, ki je bil osnova za našo raziskavo. V prvem delu predstavimo postopek diferencialne forenzike in opišemo napravo Steam Deck ter operacijski sistem SteamOS, ki sta glavno področje naše raziskave. V drugem delu naredimo pregled področja, kjer opišemo sorodne članke ter njihove ugotovitve, poleg tega še podrobneje predstavimo članek, ki je osnova za naše delo. Nato opišemo praktični del našega članka, kjer pridobimo slike fizične in virtualne naprave in na njih preverimo delovanje dodatka oziroma razširitve za orodje Autopsy, ki so jo napisali avtorji predhodnega članka. Razširitev tudi popravimo. Na koncu predstavimo rezultate in primerjamo delovanje razširitve na obeh napravah.
+
+\textbf{Ključne besede:} Digitalna forenzika, Diferencialna forenzika, SteamOS, Steam Deck, Nintendo 3DS, PlayStation 4, Autopsy
+
+\subsection{Beyond the 3DS: A Cross-Platform Study Inspired by Nintendo 3DS Residual Data Analysis}
+This paper presents an extended study inspired by a 2024 forensic case-study of secondhand Nintendo 3DS devices. The original work analyzed residual personal and technical data retrievable from these consoles and highlighted their potential forensic value. Building upon that research, we provide a broader contextual analysis by reviewing related studies on other gaming platforms such as the Xbox and PlayStation, offering a comparative perspective on cross-platform forensic readiness and privacy implications. We further investigate the limitations of existing forensic tools and propose enhancements to extract additional artifact types, such as deleted files and detailed game logs. Finally, we simulate a hypothetical forensic investigation involving a game console, analyzing how the extracted evidence might be handled in court with regard to legal admissibility, chain of custody, and ethical boundaries. Our findings highlight the role of game consoles in modern digital forensics and the need for standardized approaches to data recovery and privacy management across different hardware platforms.
+
+\textbf{Keywords:} Digital Forensics, Game Consoles, Nintendo 3DS, Xbox, PlayStation, Cross-Platform Analysis, Data Recovery, Residual Data, NAND Forensics, Ethical Forensics, Tool Development
+
+\subsection{Analyzing Deterministic and Heuristic Approaches to JPEG Fragmentation Detection}
+JPEG files are commonly used because of their efficient compression. However, they are prone to fragmentation, which complicates data recovery in forensic. This paper reviews a newly proposed deterministic algorithm designed to detect fragmentation points in JPEG files by analyzing inconsistencies in the bitstream. Unlike traditional methods, this one uses Huffman code lookup errors and quantization array overflows to identify fragmentation. The algorithm was tested on a custom dataset of real-world images. The research contributes an open-source tool (algorithm) and a real-world dataset to support digital forensics.
+
+\textbf{Keywords:} JPEG fragmentation, Digital forensics, Data recovery, Fragmentation point detection, Huffman code analysis, Quantization table overflow, Bitstream inconsistency, File carving
+
+\subsection{Natančnost geolokacijskih metapodatkov slik pametnih telefonov}
+Geolokacijski podatki, še posebej tisti v EXIF metapodatkih fotografij pametnih telefonov, predstavljajo pomemben dokaz v digitalni forenziki. Ključnega pomena za njihovo uporabo v pravnih postopkih je zanesljivost in natančnost teh podatkov. Ta članek obravnava natančnost geotagiranja fotografij, posnetih s pametnimi telefoni, z izvedbo empirične študije, ki temelji na metodologiji Ryserja in sod. (2024). Preučujemo vpliv različnih dejavnikov na natančnost lokacijskih podatkov, vključno z uporabljenimi viri lokacije (GNSS, Wi-Fi, mobilno omrežje), okoljem (urbano proti podeželskemu) in generacijo mobilnega omrežja (2G, 3G, 4G). Cilj raziskave je oceniti, v kolikšni meri ti dejavniki vplivajo na napake pri določitvi lokacije ter osvetliti zanesljivost lokacijskih metapodatkov fotografij kot forenzičnega dokaza.
+
+\textbf{Ključne besede:} geolokacija, forenzika mobilnih naprav, zanesljivost metapodatkov, natančnost lociranja naprave, analiza napak pri pozicioniranju, statistična analiza
+
+\subsection{Mobile Device Forensics: A Targeted Overview}
+We summarize a findings from several papers, with the main focus being article Nyon unchained: Forensic analysis of bosch's ebike board computere, where a Bosch Nyon device is used to obtain user information. Besides the hardware components, the methodology used and the analysis is described. Additionally we look into papers linked to the main one. One of them explores the possibilities of using cars and their infotainment systems as sources of digital evidence, where a general approach is also outlined. Furthermore, we give attention to forensics of Internet of Things (IoT) devices, mainly the Amazon Echo Dot version 2. Lastly, we look into acquiring data from backups of smartphones.
+
+\textbf{Keywords:} Digital forensics, e-bike, car, smartphone, Internet of Things

edit_this/70-pdf-includes.tex

@@ -0,0 +1,79 @@
+% For each work, use the following command to include it:
+%   \includework
+%   {Title of category}
+%   {seminarske/name_of_the_file.pdf}
+%   {Full title of the work}
+
+% Razno / Miscellaneous
+\includework
+{Razno / Miscellaneous}
+{seminarske/DigFor-25_paper_2.pdf}
+{WARNE: Orodje za zbiranje dokazov o zalezovalski programski opremi}
+
+\includework
+{Razno / Miscellaneous}
+{seminarske/DigFor-25_paper_8.pdf}
+{How to detect cryptocurrency miners? By traffic forensics!}
+
+\includework
+{Razno / Miscellaneous}
+{seminarske/DigFor-25_paper_10.pdf}
+{Was the clock correct? Timestamps and time anchors across operating systems}
+
+\includework
+{Razno / Miscellaneous}
+{seminarske/DigFor-25_paper_14.pdf}
+{Enhancing speaker identification in criminal investigations through clusterization and rank-based scoring}
+
+% IoT in avtomobili / IoT and cars
+\includework
+{IoT in avtomobili / IoT and cars}
+{seminarske/DigFor-25_paper_6.pdf}
+{Oblačna forenzična analiza Amazon iRobot Roomba sesalca}
+
+\includework
+{IoT in avtomobili / IoT and cars}
+{seminarske/DigFor-25_paper_4.pdf}
+{Hit and run: Forensic vehicle event reconstruction through driver-based cloud data from Progressive's snapshot application}
+
+\includework
+{IoT in avtomobili / IoT and cars}
+{seminarske/DigFor-25_paper_11.pdf}
+{Grand Theft API: A Forensic Analysis Of Vehicle Cloud Data}
+
+% Datoteke in sistemi / Files and systems
+\includework
+{Datoteke in sistemi / Files and systems}
+{seminarske/DigFor-25_paper_1.pdf}
+{Applying digital stratigraphy to the problem of recycled storage media}
+
+\includework
+{Datoteke in sistemi / Files and systems}
+{seminarske/DigFor-25_paper_7.pdf}
+{Forenzični vidiki zloženih datotečnih sistemov}
+
+\includework
+{Datoteke in sistemi / Files and systems}
+{seminarske/DigFor-25_paper_12.pdf}
+{Forenzična analiza naprave Steam Deck: Predstavitev in razširitev članka Well Played, Suspect!}
+
+\includework
+{Datoteke in sistemi / Files and systems}
+{seminarske/DigFor-25_paper_13.pdf}
+{Beyond the 3DS: A Cross-Platform Study Inspired by Nintendo 3DS Residual Data Analysis}
+
+% Mobilna forenzika / Mobile forensics
+\includework
+{Mobilna forenzika / Mobile forensics}
+{seminarske/DigFor-25_paper_5.pdf}
+{Analyzing Deterministic and Heuristic Approaches to JPEG Fragmentation Detection}
+
+\includework
+{Mobilna forenzika / Mobile forensics}
+{seminarske/DigFor-25_paper_3.pdf}
+{Natančnost geolokacijskih metapodatkov slik pametnih telefonov}
+
+\includework
+{Mobilna forenzika / Mobile forensics}
+{seminarske/DigFor-25_paper_9.pdf}
+{Mobile Device Forensics: A Targeted Overview}

main.tex

@@ -4,22 +4,54 @@
 \usepackage{pdfpages}
 \usepackage{tabu}
 \usepackage[top=2cm, bottom=2cm, outer=1.5cm, inner=1.5cm]{geometry}
+% Make TOC clickable
+\usepackage{hyperref}
+\hypersetup{
+    colorlinks,
+    citecolor=black,
+    filecolor=black,
+    linkcolor=black,
+    urlcolor=black
+}
+\usepackage{etoolbox} % for \ifstrequal
+
+%----------------------------------------------------------------------------------------
+% NOTE TO EDITORS:
+%   Anything that you need to edit is marked with "EDIT THIS"
+%   grep/CTRL+F is your friend
+%----------------------------------------------------------------------------------------
+
+%----------------------------------------------------------------------------------------
+%   VARIABLES
+%----------------------------------------------------------------------------------------
+\include{edit_this/10-variables}
+
+\newcommand{\nextyear}{\the\numexpr\currentyear+1\relax}
 
 \definecolor{fri_red}{RGB}{225, 48, 41}
+
 \renewcommand{\contentsname}{Kazalo / Contents}
 
 
 \begin{document}
+
+%----------------------------------------------------------------------------------------
+%   TITLE PAGE
+%----------------------------------------------------------------------------------------
+
 \begin{titlepage}
 
 \newcommand{\HRule}{\rule{\linewidth}{0.5mm}} % Defines a new command for the horizontal lines, change thickness here
 
 \center % Center everything on the page
- 
+
 %----------------------------------------------------------------------------------------
 %   HEADING SECTIONS
 %----------------------------------------------------------------------------------------
-\vspace*{70pt}
+\vspace*{30pt}
+
+% \includegraphics[width=0.3\textwidth]{ul_fri_logo.pdf}\\[1cm]
+
 \textsc{\LARGE Univerza v Ljubljani}\\[0.4cm] %
 \textcolor{fri_red}{\textsc{\LARGE Fakulteta za računalništvo in informatiko}}\\[1cm]
 \textsc{\LARGE University of Ljubljana}\\[0.4cm] %
@@ -34,21 +66,20 @@
 
 
 { \Huge \bfseries Seminarske naloge,}\\[0.4cm] % Title of your document
-{ \Huge \bfseries (leto)/(leto+1)}\\[0.4cm] % Title of your document
+{ \Huge \bfseries \currentyear/\nextyear}\\[0.4cm] % Title of your document
 
- 
 
 %----------------------------------------------------------------------------------------
 %   DATE SECTION
 %----------------------------------------------------------------------------------------
 \vspace*{300pt}
-{\large Ljubljana, (leto)}\\[2cm] % Date, change the \today to a set date if you want to be precise
+{\large Ljubljana, \currentyear}\\[2cm]
+
 
- 
 %----------------------------------------------------------------------------------------
 
 \vfill % Fill the rest of the page with whitespace
-\AddToShipoutPictureBG*{\includegraphics[width=\paperwidth,height=\paperheight]{ozadjeA4.png}}
+% \AddToShipoutPictureBG*{\includegraphics[width=\paperwidth,height=\paperheight]{ozadjeA4.png}}
 \end{titlepage}
 
 %----------------------------------------------------------------------------------------
@@ -59,55 +90,69 @@
 \noindent\rule{\textwidth}{0.4pt}
 \\[0.5cm]
 {\large Zbornik}\\[0.5cm]
-{\large Digitalna forenzika, Seminarske naloge (leto)/(leto+1)}\\[0.5cm]
-{\large Editors: Andrej Brodnik, (tvoje ime), študenti}\\[0.5cm]
-{\large Template author: David Klemenc}\\[0.5cm]
-{\large Ljubljana : Univerza v Ljubljani, Fakulteta za računalništvo in informatiko (leto).}\\[0.5cm]
+{\large Digitalna forenzika, Seminarske naloge \currentyear/\nextyear}\\[0.5cm]
+{\large Editors: \editors, študenti}\\[0.5cm]
+{\large Template authors: David Klemenc, Miha Frangež}\\[0.5cm]
+{\large Ljubljana : Univerza v Ljubljani, Fakulteta za računalništvo in informatiko \currentyear.}\\[0.5cm]
 {\textcopyright These proceedings are for internal purposes and under copyright of University of Ljubljana, Faculty of Computer and Information Science. Any redistribution of the contents in any form is prohibited.
 All rights reserved.}\\[0.5cm]
 \noindent\rule{\textwidth}{0.4pt}
 
 \clearpage
 \pagenumbering{arabic}
+
+%
+%   TABLE OF CONTENTS
+%
+
 \tableofcontents
 
 \newpage
 
+%----------------------------------------------------------------------------------------
+%   THE ACTUAL CONTENT
+%%----------------------------------------------------------------------------------------
+
 \section{Uvod / Introduction}
 
-Prvi odstavek uvoda.
-\par
-Drugi odstavek uvoda.
-\par
-...
-
+\input{edit_this/30-introduction}
 
 \vspace*{\fill}
 \begin{tabu} to \textwidth{ X[l] X[r] }
- Ljubljana, (leto) & (tvoje ime)
+ Ljubljana, \currentyear & \introauthor
 \end{tabu}
 
 \newpage
 
 \section{Povzetki / Summaries}
 
-\subsection{Naslov povzetka}
-Vsebina povzetka (abstract)
-
-\subsection{Naslov povzetka 2}
-Vsebina povzetka 2 (abstract)
-...
+\input{edit_this/50-summaries}
 
 
-\includepdf[pages=-, addtotoc={
-    1,section,1,Metodologija / Methodology,forenzika_metodologija,
-    1,subsection,1, Programming\, investigation and documentation in digital investigation   ,forenzika_metodologija_1}]{./seminarske/DigFor_2018_paper_3.pdf}
-\includepdf[pages=-, addtotoc={
-    1,subsection,1, SCARF: Skaliranje digitalnega forenzičnega procesiranja z uporabo vsebniških tehnologij v oblaku ,forenzika_metodologija_2}]{./seminarske/DigFor_2018_paper_8.pdf}
-    
+\newcommand{\lastsection}{} % stores last section name
 
-\includepdf[pages=-, addtotoc={
-    1,section,1,Razno / Misc,forenzika_razno,
-    1,subsection,1, DROP (DRone Open source Parser): Forenzična analiza modela DJI Phantom III ,forenzika_razno_1}]{./seminarske/DigFor_2018_paper_17.pdf}
+\newcommand{\includework}[3]{%
+  \ifstrequal{#1}{\lastsection}{%
+    % same as last → only add subsection
+    \includepdf[
+      pages=-,
+      pagecommand={\thispagestyle{plain}},
+      addtotoc={1,subsection,1,{#3},{#3}}
+    ]{#2}%
+  }{%
+    % different → add both section and subsection
+    \renewcommand{\lastsection}{#1}%
+    \includepdf[
+      pages=-,
+      pagecommand={\thispagestyle{plain}},
+      addtotoc={
+        1,section,1,{#1},{#1},
+        1,subsection,1,{#3},{#3}
+      }
+    ]{#2}%
+  }%
+}
 
-\end{document}
+\input{edit_this/70-pdf-includes}
+
+\end{document}