Nikolaos Pitropakis

1.6k total citations
57 papers, 947 citations indexed

About

Nikolaos Pitropakis is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Nikolaos Pitropakis has authored 57 papers receiving a total of 947 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 27 papers in Information Systems and 23 papers in Computer Networks and Communications. Recurrent topics in Nikolaos Pitropakis's work include Advanced Malware Detection Techniques (21 papers), Network Security and Intrusion Detection (19 papers) and Chaos-based Image/Signal Encryption (8 papers). Nikolaos Pitropakis is often cited by papers focused on Advanced Malware Detection Techniques (21 papers), Network Security and Intrusion Detection (19 papers) and Chaos-based Image/Signal Encryption (8 papers). Nikolaos Pitropakis collaborates with scholars based in United Kingdom, Greece and Saudi Arabia. Nikolaos Pitropakis's co-authors include William J. Buchanan, Jawad Ahmad, Eleftherios Anastasiadis, George Loukas, Emmanouil Panaousis, Thanassis Giannetsos, Alexios Mylonas, Christos Chrysoulas, Pavlos Papadopoulos and Muazzam A. Khan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Sensors.

In The Last Decade

Nikolaos Pitropakis

50 papers receiving 908 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nikolaos Pitropakis United Kingdom 16 528 511 411 310 72 57 947
Biju Issac United Kingdom 15 382 0.7× 475 0.9× 302 0.7× 327 1.1× 106 1.5× 79 905
Mohammed M. Alani Canada 17 358 0.7× 385 0.8× 253 0.6× 214 0.7× 68 0.9× 46 669
Martín Ochoa Singapore 15 490 0.9× 630 1.2× 538 1.3× 408 1.3× 71 1.0× 51 1.0k
P. Santhi Thilagam India 19 385 0.7× 537 1.1× 258 0.6× 458 1.5× 31 0.4× 68 938
Marco Barreno United States 6 936 1.8× 558 1.1× 505 1.2× 227 0.7× 80 1.1× 7 1.3k
Mohamed Abomhara Norway 10 275 0.5× 519 1.0× 312 0.8× 412 1.3× 185 2.6× 24 962
Pavol Zavarsky Canada 15 287 0.5× 387 0.8× 361 0.9× 521 1.7× 64 0.9× 102 825
İbrahim Soğukpınar Türkiye 16 240 0.5× 468 0.9× 373 0.9× 496 1.6× 93 1.3× 62 818
Wei You China 16 367 0.7× 463 0.9× 377 0.9× 540 1.7× 49 0.7× 53 1.1k
Weihong Han China 13 405 0.8× 372 0.7× 218 0.5× 422 1.4× 67 0.9× 73 808

Countries citing papers authored by Nikolaos Pitropakis

Since Specialization
Citations

This map shows the geographic impact of Nikolaos Pitropakis'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 Nikolaos Pitropakis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nikolaos Pitropakis more than expected).

Fields of papers citing papers by Nikolaos Pitropakis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nikolaos Pitropakis. 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 Nikolaos Pitropakis. The network helps show where Nikolaos Pitropakis may publish in the future.

Co-authorship network of co-authors of Nikolaos Pitropakis

This figure shows the co-authorship network connecting the top 25 collaborators of Nikolaos Pitropakis. A scholar is included among the top collaborators of Nikolaos Pitropakis 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 Nikolaos Pitropakis. Nikolaos Pitropakis 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.
Saeed, Umer, Sana Ullah Jan, Jawad Ahmad, et al.. (2025). Generative adversarial networks-enabled anomaly detection systems: A survey. Expert Systems with Applications. 296. 128978–128978. 2 indexed citations
2.
Buchanan, William J., et al.. (2025). Leveraging LLMs for Non-Security Experts in Threat Hunting: Detecting Living off the Land Techniques. Machine Learning and Knowledge Extraction. 7(2). 31–31. 3 indexed citations
3.
Yaqoob, Muhammad, et al.. (2025). AutoQALLMs: Automating Web Application Testing Using Large Language Models (LLMs) and Selenium. Computers. 14(11). 501–501.
4.
Radoglou‐Grammatikis, Panagiotis, Antonios Sarigiannidis, Nikolaos Pitropakis, et al.. (2024). Advancements in Federated Learning for Health Applications: A Concise Survey. Edinburgh Napier Research Repository (Edinburgh Napier University). 503–508.
5.
6.
Liu, Xiaodong, et al.. (2023). Explainable AI-Based DDOS Attack Identification Method for IoT Networks. Computers. 12(2). 32–32. 40 indexed citations
7.
Pitropakis, Nikolaos, et al.. (2023). Attacking Windows Hello for Business: Is It What We Were Promised?. Cryptography. 7(1). 9–9. 2 indexed citations
8.
Sayeed, Sarwar, et al.. (2023). TRUSTEE: Towards the creation of secure, trustworthy and privacy-preserving framework. Edinburgh Napier Research Repository (Edinburgh Napier University). 1–10. 10 indexed citations
9.
Khan, Muhammad Shahbaz, et al.. (2023). PermutEx: Feature-Extraction-Based Permutation — A New Diffusion Scheme for Image Encryption Algorithms. Edinburgh Napier Research Repository (Edinburgh Napier University). 3 indexed citations
10.
Ullah, Safi, Muazzam A. Khan, Jawad Ahmad, et al.. (2022). HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles. Sensors. 22(4). 1340–1340. 79 indexed citations
11.
Ullah, Safi, Jawad Ahmad, Muazzam A. Khan, et al.. (2022). A New Intrusion Detection System for the Internet of Things via Deep Convolutional Neural Network and Feature Engineering. Sensors. 22(10). 3607–3607. 53 indexed citations
12.
Alharbi, Adel R., Jawad Ahmad, Arshad Ali, et al.. (2022). A New Multistage Encryption Scheme Using Linear Feedback Register and Chaos‐Based Quantum Map. Complexity. 2022(1). 4 indexed citations
13.
Lo, Owen, William J. Buchanan, Sarwar Sayeed, et al.. (2022). GLASS: A Citizen-Centric Distributed Data-Sharing Model within an e-Governance Architecture. Sensors. 22(6). 2291–2291. 14 indexed citations
14.
Chrysoulas, Christos, et al.. (2022). Using Social Media & Sentiment Analysis to Make Investment Decisions. Future Internet. 15(1). 5–5. 17 indexed citations
15.
Gallagher, Michael, Nikolaos Pitropakis, Christos Chrysoulas, et al.. (2022). Investigating machine learning attacks on financial time series models. Computers & Security. 123. 102933–102933. 9 indexed citations
16.
Papadopoulos, Pavlos, et al.. (2021). Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT. SHILAP Revista de lepidopterología. 1(2). 252–273. 41 indexed citations
17.
Khan, Muhammad Almas, Muazzam A. Khan, Sana Ullah Jan, et al.. (2021). A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT. Sensors. 21(21). 7016–7016. 92 indexed citations
18.
Buchanan, William J., et al.. (2021). PAN-DOMAIN: Privacy-preserving Sharing and Auditing of Infection Identifier Matching. Research Output (Edinburgh Napier University). 1–8. 1 indexed citations
19.
Pitropakis, Nikolaos, et al.. (2020). Exploring Adversarial Attacks and Defences for Fake Twitter Account Detection. SHILAP Revista de lepidopterología. 8(4). 64–64. 15 indexed citations
20.
Müller, Lisa, et al.. (2020). A Traffic Analysis on Serverless Computing Based on the Example of a File Upload Stream on AWS Lambda. Big Data and Cognitive Computing. 4(4). 38–38. 5 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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