1. Browser fingerprinting: overview and open challengesMarko Hölbl, Vladimir I. Zadorozhny, Tatjana Welzer-Družovec, Marko Kompara, Lili Nemec Zlatolas, 2024, independent scientific component part or a chapter in a monograph Abstract: The central concept of browser fingerprinting is the collection of devicespecific information for identification or security purposes. This chapter provides an overview of the research conducted in the field of browser fingerprinting and presents an entry point for newcomers. Relevant literature is examined to understand the current research in the field of browser fingerprinting. Both research in the field of crafting browser fingerprints and protection against it is included. Finally, current research challenges and future research directions are presented and discussed.
Keywords: browser fingerprinting, profiling, user privacy, web tracking
Published in DKUM: 20.01.2026; Views: 0; Downloads: 1
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2. Zagotavljanje varnosti pri oblačni integraciji komunikacijskega sistema : magistrsko deloKristjan Šuligoj, 2025, master's thesis Abstract: Zaključno delo obravnava varnostne vidike migracije komunikacijskega sistema v oblak. Raziskava temelji na pregledu obstoječe literature, s poudarkom na prepoznavanju varnostnih groženj, ki se pojavijo ob selitvi v oblačno okolje, ter na identifikaciji ukrepov za njihovo zmanjšanje. Ker je varnost v literaturi obravnavana z zelo raznolikih vidikov, je bil na podlagi pregleda izbranih znanstvenih člankov oblikovan nabor najpogosteje omenjenih groženj, ki smo jih združili v smiselne kategorije za bolj sistematično analizo.
Pridobljeno znanje je bilo uporabljeno pri razvoju rešitve, ki je po novem umeščena v oblak in omogoča enotno upravljanje elementov komunikacijskega sistema. Prav tako je bila izvedena primerjava obstoječe in nove arhitekture, pri čemer se je pokazalo, kako varnostni ukrepi vplivajo na zasnovo sistema. Ugotovljeno je bilo tudi, da na varnost ne vplivajo zgolj mehanizmi, ki so vgrajeni v rešitev, temveč tudi lastnosti oblačne infrastrukture izbranega ponudnika in drugih storitev v okolju. Analiza tako potrjuje, da je migracija v oblak izvedljiva in je lahko varna, če so tveganja pravočasno prepoznana in obvladana z ustreznimi mehanizmi.
Keywords: kibernetska varnost, oblak, komunikacijski sistem, migracija v oblak, integracija
Published in DKUM: 16.12.2025; Views: 0; Downloads: 10
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3. A secure way of communication for smart grid networksPooja Tyagi, Saru Kumari, Mohammed J. F. Alenazi, Marko Hölbl, 2025, original scientific article Abstract: In 2021, Khan et al. suggested a scheme based on smart grid networks. They deployed the random oracle model to justify the security of their scheme formally. They also verified the security of the scheme using the AVISPA software tool. We studied this scheme and found some security issues. The scheme suffers from a confidentiality breach attack. In Khan et al.’s scheme, an adversary can track both the user and the server, and it does not provide user and server anonymity. An adversary can also impersonate a server. To overcome all these security issues, we propose a protocol for smart grid networks. In our proposed scheme, we maintain all the qualities of Khan et al.’s scheme and try to remove all its weaknesses.
Keywords: key agreement, smart grid, smart grid networks, user authentication
Published in DKUM: 01.12.2025; Views: 0; Downloads: 0
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4. Razvoj sistema za beleženje statistike ogledov nepremičninskih oglasov : diplomsko deloMarcel Matko Sotošek, 2025, undergraduate thesis Abstract: Diplomsko delo obravnava razvoj zalednega sistema za beleženje in analizo ogledov nepremičninskih oglasov na spletnih portalih. V prvem delu je predstavljen teoretični okvir, ki vključuje ozadje problema, cilje naloge ter pregled ključnih tehnoloških in konceptualnih temeljev za razvoj sistema.
Praktični del zajema celoten proces načrtovanja in implementacije sistema. Posebna pozornost je namenjena analizi zahtev, načrtovanju arhitekture in podatkovnih struktur ter razvoju ključnih funkcionalnosti, kot so integracija z nepremičninskimi portali, obdelava nalog ter pridobivanje in analiza statističnih podatkov.
Sistem je bil testiran v realnem okolju, pri čemer so bile ocenjene njegove zmogljivosti, natančnost in odzivnost, kar je omogočilo tudi identifikacijo možnosti za nadaljnje optimizacije in izboljšave.
Keywords: REST, Express.js, Redis, BullMQ, mikrostoritev
Published in DKUM: 15.10.2025; Views: 0; Downloads: 6
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5. Vzpostavitev šifrirnih ključev v post-kvantni kriptografijiMarko Kompara, Marko Hölbl, 2025, original scientific article Abstract: Razvoj kvantnega računalnika napreduje tako hitro, da čeprav kriptografsko signifikanten kvantni računalnik še ne obstaja in ga po najbolj optimističnih napovedih lahko pričakujemo komaj čez kakšno desetletje, je že potrebna zamenjava določenihranljivih kriptografskih gradnikov, ki se danes uporabljajo za varovanje podatkov. Ta prispevek je namenjen pregledu mehanizmov za inkapsulacijo ključa (KEM), ki so kvantno varni algoritmi za dogovor o šifrirnih ključih. V prispevku se bomo dotaknili nevarnosti kvantnih računalnikov za tradicionalno kriptografijo, predstavili splošno delovanje algoritmov KEM ter specifične rešitve, za katere bomo predstavili njihove varnostne lastnosti ter izvedli analizo učinkovitosti oz. hitrosti njihovega delovanja. Na koncu bomo predstavili še nekaj primerov uporabe algoritmov KEM oz. hibridnih rešitev, ki združujejo tradicionalno in post-kvantno kriptografijo v pogosto uporabljenih protokolih.
Keywords: mehanizem za inkapsulacijo ključa, post-kvantna kriptografija, analiza
Published in DKUM: 29.09.2025; Views: 0; Downloads: 12
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6. A comprehensive survey on integration of machine learning with secure blockchain-based applicationsChahna Meka, Keerthi Reddy Palakollu, Maria Azees, Arun Sekar Rajasekaran, Ashok Kumar Das, Marko Hölbl, 2025, original scientific article Abstract: Machine learning (ML) is a critical technology that provides pervasive intelligence for the Internet of Things (IoT), enabling smart decision and automation. Meanwhile, Blockchain has emerged as a reliable, secure, decentralized and distributed network with applications in a variety of sectors like healthcare, insurance, finance, banking, and business. The integration of blockchain and ML may further enhance security, optimize data processing and ensure intelligent automation. The linkage of blockchain technology with ML aims to safeguard the privacy of ML models by executing blockchain transparency functions. However, maintaining the integrity of ML models and optimizing blockchain process are challenging. The integration in this work aims to solve challenges like security vulnerability, scalability and computational efficiency. Integration enables automation through smart contracts, enabling secure decision making while preserving data integrity and supporting auditing tasks. Moreover, the security benefits of blockchain networks result from anomaly detection technologies enabled by ML that detects fraudulent activities while defending blockchain networks from security threats. This work presents an organized approach to examine contemporary blockchain-ML research developments, analysis of applications based on the integration of blockchain and ML, technical aspects of Integration and its case studies. Finally, integration with respect to industry focus, followed by open challenges and research problems in ML-based blockchain technology, future directions and emerging trends are discussed in this survey.
Keywords: machine learning, blockchain, artificial intelligence, security, privacy, regression
Published in DKUM: 05.09.2025; Views: 0; Downloads: 3
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7. Avtomatizirano skeniranje brezžičnih iot omrežij in identificiranje iot naprav : diplomsko deloAnže Plazl, 2025, undergraduate thesis Abstract: Skeniranje brezžičnih omrežij, se je razvilo iz začetnega entuziastičnega kartiranja brezžičnih omrežij v kompleksno dejavnost z različnimi nameni in metodami. Z razmahom interneta stvari je ta pristop dobil nov pomen, saj se pojavlja potreba po odkrivanju in kartiranju vedno večjega števila brezžičnih naprav. V diplomskem delu smo razvili namensko mobilno rešitev za zajem in analizo ZigBee naprav, ki so pogosto prisotne v IoT infrastrukturi. Sistem temelji na prilagojeni strojni opremi, ki združuje prenosljivost, energetsko učinkovitost in zmožnost zaznavanja ZigBee signala na terenu. Delovanje sistema smo preizkusili v realnem okolju, kjer smo preverili njegovo zanesljivost pri zaznavanju ZigBee naprav ter kakovost zajetih podatkov. V delu tako predstavljamo prispevek k razvoju orodij za varnostno analizo IoT okolij ter ponuja osnovo za nadaljnji razvoj rešitev za terensko zaznavanje brezžičnih naprav.
Keywords: ZigBee omrežje, brezžična omrežja, IoT naprave, zaznavanje naprav, kartiranje omrežij
Published in DKUM: 13.08.2025; Views: 0; Downloads: 28
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8. Uporaba metod strojnega učenja za zaznavanje kompleksnejših kibernetskih groženjMaja Rotovnik, 2025, master's thesis Abstract: Zaradi porasta in kompleksnosti kibernetskih groženj postajajo tradicionalni pristopi k zaznavanju napadov manj učinkoviti. Algoritmi strojnega učenja z zmožnostjo hitre obdelave velike količine podatkov ponujajo napredne rešitve za zaznavanje in preprečevanje vedno bolj prikritih in kompleksnih groženj. Namen magistrskega dela je bil ugotoviti, katere metode strojnega učenja so najučinkovitejše pri zaznavi napadov izvidništva in naprednih trajnih groženj – kompleksnejših vrst kibernetskih napadov. Raziskali smo, kako ustrezna predpriprava podatkov vpliva na učinkovitost napovedi in koliko je ansambelski pristop pri tem učinkovitejši. S sistematičnim pregledom literature smo ugotovili, da so pri zaznavi kompleksnih groženj najučinkovitejši algoritmi XGBoost, LightGBM, odločitvena drevesa, naključni gozd in naivni Bayesov klasifikator. Omenjene algoritme smo vključili v eksperiment, v katerem smo metode s pomočjo metrik (točnost, natančnost, priklic in F1 vrednost) ovrednotili. Ugotovili smo, da je pri klasifikaciji napadov najučinkovitejši algoritem naključni gozd. Iste algoritme smo vključili tudi v ansambel, pri čemer smo ugotovili, da je pri zaznavi naprednih trajnih groženj in izvidništva ansambelski pristop učinkovitejši, saj dosega višje rezultate vseh štirih metrik. Z ustreznimi tehnikami predpriprave podatkov pa smo dokazali, da ta pomembno vpliva na končno učinkovitost modelov oz. ansambla.
Keywords: kibernetska varnost, napredne trajne grožnje, izvidništvo, strojno učenje
Published in DKUM: 08.07.2025; Views: 0; Downloads: 59
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9. Data protection heterogeneity in the European UnionMarko Hölbl, Boštjan Kežmah, Marko Kompara, 2021, original scientific article Abstract: In light of digitalisation, we are witnessing an increased volume of collected data and
data generation and exchange acceleration. Therefore, the European Union (EU) has introduced the
General Data Protection Regulation (GDPR) as a new framework for data protection on the European
level. However, GDPR allows the member states to change some parts of the regulation, and the
member states can always build on top of the GDPR. An example is the collection of biometric data
with electronic signatures. This paper aims to compare the legislation on data protection topics in the
various EU member states. The findings show that the member states included in the study generally
do not have many additional/specific laws (only in 29.4% of the cases). However, almost all have
other/additional legislation to the GDPR on at least one topic. The most additional legislation is on
the topics of video surveillance, biometry, genetic data and health data. We also introduce a dynamic
map that allows for quick navigating between different information categories and comparisons of
the EU member states at a glance.
Keywords: data protection, personal data, data privacy, GDPR legislation, heterogeneity, legislation on data protection, European Union
Published in DKUM: 16.06.2025; Views: 0; Downloads: 13
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10. Models of privacy and disclosure on social networking sites: a systematic literature reviewLili Nemec Zlatolas, Luka Hrgarek, Tatjana Welzer-Družovec, Marko Hölbl, 2022, original scientific article Abstract: Social networking sites (SNSs) are used widely, raising new issues in terms of privacy and
disclosure. Although users are often concerned about their privacy, they often publish information
on social networking sites willingly. Due to the growing number of users of social networking sites,
substantial research has been conducted in recent years. In this paper, we conducted a systematic
review of papers that included structural equations models (SEM), or other statistical models with
privacy and disclosure constructs. A total of 98 such papers were found and included in the analysis.
In this paper, we evaluated the presentation of results of the models containing privacy and disclosure
constructs. We carried out an analysis of which background theories are used in such studies and
have also found that the studies have not been carried out worldwide. Extending the research to
other countries could help with better user awareness of the privacy and self-disclosure of users
on SNSs.
Keywords: structural equations modeling, social networking sites, privacy, disclosure
Published in DKUM: 28.03.2025; Views: 0; Downloads: 6
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