Resul Daş

3.7k total citations · 4 hit papers
101 papers, 2.4k citations indexed

About

Resul Daş is a scholar working on Computer Networks and Communications, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Resul Daş has authored 101 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Computer Networks and Communications, 30 papers in Artificial Intelligence and 26 papers in Signal Processing. Recurrent topics in Resul Daş's work include Network Security and Intrusion Detection (28 papers), Advanced Malware Detection Techniques (22 papers) and Smart Grid Security and Resilience (14 papers). Resul Daş is often cited by papers focused on Network Security and Intrusion Detection (28 papers), Advanced Malware Detection Techniques (22 papers) and Smart Grid Security and Resilience (14 papers). Resul Daş collaborates with scholars based in Türkiye, Spain and Iran. Resul Daş's co-authors include Muhammed Zekeriya Gündüz, İbrahim Türkoğlu, Abdulkadir Şengür, Muhammet Baykara, Gürkan Tuna, Moloud Abdar, Mariam Zomorodi‐Moghadam, I‐Hsien Ting, Bihter Daş and Talha Burak Alakuş and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Resul Daş

86 papers receiving 2.2k citations

Hit Papers

Cyber-security on smart gri... 2008 2026 2014 2020 2020 2008 2023 2024 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Cyber-security on smart grid: Threats and potential solutions
    2020 460 citations Muhammed Zekeriya Gündüz, Resul Daş Computer Networks profile →
  2. Effective diagnosis of heart disease through neural networks ensembles
    2008 436 citations Resul Daş, İbrahim Türkoğlu et al. Expert Systems with Applications profile →
  3. A review on fog computing: Issues, characteristics, challenges, and potential applications
    2023 96 citations Resul Daş et al. SHILAP Revista de lepidopterología profile →
  4. A comparative analysis of various machine learning methods for anomaly detection in cyber attacks on IoT networks
    2024 69 citations Resul Daş et al. Internet of Things profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Resul Daş Türkiye 20 823 718 555 524 494 101 2.4k
Mohd Khanapi Abd Ghani Malaysia 23 703 0.9× 562 0.8× 354 0.6× 212 0.4× 72 0.1× 82 2.1k
Fadi Aloul United Arab Emirates 28 637 0.8× 1.2k 1.7× 742 1.3× 51 0.1× 253 0.5× 137 3.0k
Mangal Sain South Korea 18 503 0.6× 556 0.8× 496 0.9× 66 0.1× 95 0.2× 107 1.6k
Ahmed Ghoneim Saudi Arabia 32 1.0k 1.2× 1.2k 1.7× 701 1.3× 156 0.3× 112 0.2× 78 2.9k
Vinayakumar Ravi Saudi Arabia 31 1.1k 1.3× 1.1k 1.5× 496 0.9× 133 0.3× 102 0.2× 194 2.8k
Roobaea Alroobaea Saudi Arabia 27 661 0.8× 666 0.9× 508 0.9× 88 0.2× 108 0.2× 194 2.3k
G. Sahoo India 25 684 0.8× 586 0.8× 434 0.8× 57 0.1× 121 0.2× 119 1.7k
Mashael Maashi Saudi Arabia 24 674 0.8× 342 0.5× 215 0.4× 74 0.1× 95 0.2× 96 1.7k
Piyush Kumar Shukla India 30 842 1.0× 587 0.8× 369 0.7× 134 0.3× 109 0.2× 181 2.8k
Muhammad Rizwan Pakistan 24 620 0.8× 696 1.0× 407 0.7× 83 0.2× 78 0.2× 75 1.9k

Countries citing papers authored by Resul Daş

Since Specialization
Citations

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

Fields of papers citing papers by Resul Daş

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Resul Daş

This figure shows the co-authorship network connecting the top 25 collaborators of Resul Daş. A scholar is included among the top collaborators of Resul Daş 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 Resul Daş. Resul Daş 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.
Daş, Resul, et al.. (2025). Green IoT for energy efficiency: Enabling technologies, challenges, and future research directions. Thermal Science and Engineering Progress. 62. 103592–103592. 1 indexed citations
2.
Daş, Resul, et al.. (2025). A novel approach for graph-based real-time anomaly detection from dynamic network data listened by Wireshark. SHILAP Revista de lepidopterología. 12(2). 3 indexed citations
3.
Daş, Resul, et al.. (2025). A novel hybrid approach combining GCN and GAT for effective anomaly detection from firewall logs in campus networks. Computer Networks. 259. 111082–111082. 3 indexed citations
4.
Daş, Bihter, et al.. (2024). A systematic review of trimodal affective computing approaches: Text, audio, and visual integration in emotion recognition and sentiment analysis. Expert Systems with Applications. 255. 124852–124852. 18 indexed citations
5.
Daş, Resul, et al.. (2024). TER-CA-WGNN: Trimodel Emotion Recognition Using Cumulative Attribute-Weighted Graph Neural Network. Applied Sciences. 14(6). 2252–2252. 5 indexed citations
6.
Daş, Bihter, et al.. (2024). TAC-Trimodal Affective Computing: Principles, integration process, affective detection, challenges, and solutions. Displays. 83. 102731–102731. 3 indexed citations
7.
Daş, Resul, et al.. (2024). A comparative analysis of various machine learning methods for anomaly detection in cyber attacks on IoT networks. Internet of Things. 26. 101162–101162. 69 indexed citations breakdown →
8.
Daş, Resul, et al.. (2023). A new approach to recognizing the use of attitude markers by authors of academic journal articles. Expert Systems with Applications. 230. 120538–120538. 4 indexed citations
9.
10.
Daş, Resul, et al.. (2022). Yazılım Ürün Ölçütlerinin Uygulamalı İncelenmesi. Fırat Üniversitesi Mühendislik Bilimleri Dergisi. 34(2). 635–645.
11.
Gündüz, Muhammed Zekeriya & Resul Daş. (2022). Kişisel Siber Güvenlik Yaklaşımlarının Değerlendirilmesi. DÜMF Mühendislik Dergisi.
12.
Daş, Resul, et al.. (2020). Analysis of cyber-attacks in IoT-based critical infrastructures. DergiPark (Istanbul University). 8(4). 122–133. 36 indexed citations
13.
Daş, Resul, et al.. (2017). Ağ Benzetim ve Modelleme Araçlarının İncelenmesi. DergiPark (Istanbul University). 1 indexed citations
14.
Baykara, Muhammet, Resul Daş, & Gürkan Tuna. (2016). Web Based Log Analysis Platform for Detection of Web Attacks from Web Server Access Logs. DergiPark (Istanbul University). 1 indexed citations
15.
Ramakrishnan, B., et al.. (2016). Designing a Novel Two-Tier Authentication Algorithm for Web Service Architecture. Journal of Telecommunication Electronic and Computer Engineering (JTEC). 8(9). 67–75. 2 indexed citations
16.
Daş, Resul, et al.. (2016). İmgeler için yeni bir veri gizleme yaklaşımı. DÜMF Mühendislik Dergisi. 7(3). 501–514. 2 indexed citations
17.
Daş, Resul. (2014). An Investigation on Information Hiding Tools for Steganography. DergiPark (Istanbul University). 3(3). 200–208. 2 indexed citations
18.
Daş, Resul & İbrahim Türkoğlu. (2010). EXTRACTION OF INTERESTING PATTERNS THROUGH ASSOCIATION RULE MINING FOR IMPROVEMENT OF WEBSITE USABILITY. DergiPark (Istanbul University). 5 indexed citations
19.
Daş, Resul, et al.. (2008). ANALYZING OF THE USER ACCESS LOGS OF A WEBSITE USING WEB USAGE MINING METHOD: EXAMPLE OF FIRAT UNIVERSITY. DergiPark (Istanbul University). 2 indexed citations
20.
Daş, Resul, İbrahim Türkoğlu, & Mustafa Poyraz. (2007). ANALYZING OF SYSTEM ERRORS FOR INCREASING A WEB SERVER PERFORMANCE BY USING WEB USAGE MINING. DergiPark (Istanbul University). 7 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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