Wojciech Mazurczyk

5.0k total citations
182 papers, 2.9k citations indexed

About

Wojciech Mazurczyk is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Wojciech Mazurczyk has authored 182 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 105 papers in Artificial Intelligence, 77 papers in Computer Networks and Communications and 77 papers in Computer Vision and Pattern Recognition. Recurrent topics in Wojciech Mazurczyk's work include Internet Traffic Analysis and Secure E-voting (93 papers), Advanced Steganography and Watermarking Techniques (71 papers) and Advanced Malware Detection Techniques (70 papers). Wojciech Mazurczyk is often cited by papers focused on Internet Traffic Analysis and Secure E-voting (93 papers), Advanced Steganography and Watermarking Techniques (71 papers) and Advanced Malware Detection Techniques (70 papers). Wojciech Mazurczyk collaborates with scholars based in Poland, Germany and Italy. Wojciech Mazurczyk's co-authors include Krzysztof Szczypiorski, Luca Caviglione, Krzysztof Cabaj, Steffen Wendzel, Salvador E. Venegas-Andraca, Bassem Abd-El-Atty, Ahmed A. Abd El‐Latif, Artur Janicki, Carol Fung and Zbigniew Kotulski and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Communications of the ACM.

In The Last Decade

Wojciech Mazurczyk

171 papers receiving 2.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Wojciech Mazurczyk Poland 29 1.5k 1.3k 1.2k 1.0k 657 182 2.9k
Battista Biggio Italy 27 2.5k 1.6× 476 0.4× 963 0.8× 1.5k 1.4× 671 1.0× 97 3.3k
Zhifeng Bao Australia 26 839 0.6× 336 0.3× 665 0.6× 1.0k 1.0× 412 0.6× 153 2.3k
Ibrahim Kamel United Arab Emirates 23 563 0.4× 745 0.6× 793 0.7× 925 0.9× 515 0.8× 129 2.1k
Hung–Min Sun Taiwan 31 1.5k 1.0× 830 0.6× 2.0k 1.7× 642 0.6× 1.8k 2.8× 174 3.5k
Rafiqul Islam Australia 21 944 0.6× 313 0.2× 1.1k 0.9× 971 1.0× 739 1.1× 131 2.1k
Jian–Guang Lou China 30 1.9k 1.2× 723 0.6× 2.1k 1.8× 303 0.3× 1.4k 2.2× 114 3.9k
Nhien‐An Le‐Khac Ireland 20 877 0.6× 229 0.2× 877 0.7× 723 0.7× 639 1.0× 121 1.9k
Felix Freiling Germany 27 1.5k 1.0× 259 0.2× 1.9k 1.5× 2.1k 2.0× 1.4k 2.2× 156 3.1k
Luis Javier García Villalba Spain 23 453 0.3× 444 0.3× 1.1k 0.9× 387 0.4× 484 0.7× 180 2.1k
Jingren Zhou United States 31 1.7k 1.1× 872 0.7× 1.5k 1.2× 623 0.6× 1.4k 2.2× 138 3.5k

Countries citing papers authored by Wojciech Mazurczyk

Since Specialization
Citations

This map shows the geographic impact of Wojciech Mazurczyk's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Wojciech Mazurczyk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wojciech Mazurczyk more than expected).

Fields of papers citing papers by Wojciech Mazurczyk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wojciech Mazurczyk. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Wojciech Mazurczyk. The network helps show where Wojciech Mazurczyk may publish in the future.

Co-authorship network of co-authors of Wojciech Mazurczyk

This figure shows the co-authorship network connecting the top 25 collaborators of Wojciech Mazurczyk. A scholar is included among the top collaborators of Wojciech Mazurczyk based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Wojciech Mazurczyk. Wojciech Mazurczyk is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Mazurczyk, Wojciech, et al.. (2024). Federated learning secure model: A framework for malicious clients detection. SoftwareX. 27. 101765–101765.
2.
Mazurczyk, Wojciech, et al.. (2024). A Comparative Study on the Security of Kubernetes Deployments. 718–723. 4 indexed citations
3.
4.
Tian, Hui, et al.. (2023). Steganalysis of adaptive multi-rate speech with unknown embedding rates using clustering and ensemble learning. Computers & Electrical Engineering. 111. 108909–108909.
5.
El‐Latif, Ahmed A. Abd, Yassine Maleh, Wojciech Mazurczyk, Mohammed ElAffendi, & Majeed A. S. Alkanhal. (2023). Advances in Cybersecurity, Cybercrimes, and Smart Emerging Technologies. 1 indexed citations
6.
Kozik, Rafał, Aleksandra Pawlicka, Marek Pawlicki, et al.. (2023). A Meta-Analysis of State-of-the-Art Automated Fake News Detection Methods. IEEE Transactions on Computational Social Systems. 11(4). 5219–5229. 11 indexed citations
7.
Tian, Hui, et al.. (2023). FedSpy: A Secure Collaborative Speech Steganalysis Framework Based on Federated Learning. Electronics. 12(13). 2854–2854.
8.
Kozik, Rafał, Wojciech Mazurczyk, Krzysztof Cabaj, et al.. (2023). Deep Learning for Combating Misinformation in Multicategorical Text Contents. Sensors. 23(24). 9666–9666. 5 indexed citations
9.
Ahvanooey, Milad Taleby, Wojciech Mazurczyk, Qianmu Li, et al.. (2022). CovertSYS: A systematic covert communication approach for providing secure end-to-end conversation via social networks. Journal of Information Security and Applications. 71. 103368–103368. 4 indexed citations
10.
Tian, Hui, et al.. (2022). Towards blind detection of steganography in low‐bit‐rate speech streams. International Journal of Intelligent Systems. 37(12). 12085–12112. 2 indexed citations
11.
Tian, Hui, et al.. (2022). Steganalysis of adaptive multi-rate speech streams with distributed representations of codewords. Journal of Information Security and Applications. 68. 103250–103250. 10 indexed citations
12.
Tian, Hui, et al.. (2022). STFF-SM: Steganalysis Model Based on Spatial and Temporal Feature Fusion for Speech Streams. IEEE/ACM Transactions on Audio Speech and Language Processing. 31. 277–289. 8 indexed citations
13.
Nowakowski, P., et al.. (2021). Detecting Network Covert Channels using Machine Learning, Data Mining and Hierarchical Organisation of Frequent Sets.. 12. 20–43. 11 indexed citations
14.
Caviglione, Luca, Michał Choraś, Igino Corona, et al.. (2020). Tight Arms Race: Overview of Current Malware Threats and Trends in Their Detection. IEEE Access. 9. 5371–5396. 82 indexed citations
15.
Zhang, Yue, Xun Zhang, Rudolf Zetík, et al.. (2019). Smart Television Services Using NFV/SDN Network Management. IEEE Transactions on Broadcasting. 65(2). 404–413. 28 indexed citations
16.
Mazurczyk, Wojciech, et al.. (2018). Countering adaptive network covert communication with dynamic wardens. Future Generation Computer Systems. 94. 712–725. 17 indexed citations
17.
Mazurczyk, Wojciech, et al.. (2015). Insights from Nature for Cybersecurity. Health Security. 13(2). 82–87. 2 indexed citations
18.
Janicki, Artur, Wojciech Mazurczyk, & Krzysztof Szczypiorski. (2014). Evaluation of Efficiency of Transcoding Steganography. Journal of Homeland Security and Emergency Management. 11(4). 555–578. 1 indexed citations
19.
Mazurczyk, Wojciech, et al.. (2011). What more can be learnt about BitTorrent from meta-data files and μTorrent logs?. Horticulture Research. 8(1). 118–118. 1 indexed citations
20.
Mazurczyk, Wojciech & Zbigniew Kotulski. (2006). New security and control protocol for VoIP based on steganography and digital watermarking. Studia Iuridica Lublinensia (Uniwersytet Marii Curie-Skłodowskiej w Lublinie). 5(1). 417–426. 33 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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