Pavel Laskov

5.7k citations
52 papers · 2.1k indexed · 1 hit paper · h-index 24
Topics
Network Security and Intrusion Detection (25 papers)Advanced Malware Detection Techniques (16 papers)Anomaly Detection Techniques and Applications (10 papers)

In The Last Decade

Pavel Laskov

47 papers receiving 2.0k citations

Hit Papers

The Role of Machine Learning in Cybersecurity20222026202320242022255075100

Peers

Pavel Laskov
Comparison fields: 5 of 97
  • Artificial Intelligence 1.3k
  • Signal Processing 956
  • Computer Networks and Communications 880
  • Information Systems 407
  • Computer Vision and Pattern Recognition 360
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Citations per field
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Citations per year

Countries citing papers authored by Pavel Laskov

Since Specialization
Citations

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

Fields of papers citing papers by Pavel Laskov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pavel Laskov

This figure shows the co-authorship network connecting the top 25 collaborators of Pavel Laskov. A scholar is included among the top collaborators of Pavel Laskov 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 Pavel Laskov. Pavel Laskov 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
#WorkIndexed citations
1 0
2
The Role of Machine Learning in Cybersecuritybreakdown →
119
3 7
4
Detection of Malicious PDF Files Based on Hierarchical Document Structure.
89
5 11
6
Support Vector Machines Under Adversarial Label Noise
158
7
Online Anomaly Detection under Adversarial Impact
64
8 3
9
Network attack detection and defense - Manifesto of the Dagstuhl Perspective Workshop
2
10 5
11 30
12 4
13
Linear-Time Computation of Similarity Measures for Sequential Data
65
14
Incremental Support Vector Learning: Analysis, Implementation and Applications
204
15
Detection of intrusions and malware & vulnerability assessment : Third International Conference, DIMVA 2006, Berlin, Germany, July 13-14, 2006 : proceedings
0
16
A Fast Algorithm for Joint Diagonalization with Non-orthogonal Transformations and its Application to Blind Source Separation
147
17 68
18
Curvature-Based Algorithms for Non-Rigid Motion and Correspondence Estimation ⁄
1
19
An Improved Decomposition Algorithm for Regression Support Vector Machines
19
20 11

About Pavel Laskov

Pavel Laskov is a scholar working on Signal Processing, Computer Networks and Communications and Artificial Intelligence, having authored 52 papers that have together received 2.1k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (25 papers), Advanced Malware Detection Techniques (16 papers) and Anomaly Detection Techniques and Applications (10 papers). The work is most often cited by research in Signal Processing (956 citations), Artificial Intelligence (1.3k citations) and Computer Networks and Communications (880 citations). Pavel Laskov has collaborated with scholars based in Germany, United States and Liechtenstein. Frequent co-authors include Nedim Šrndić, Klaus‐Robert Müller, Marius Kloft, Konrad Rieck, Christian Gehl, Blaine Nelson, Battista Biggio, Andreas Ziehe, Christin Schäfer and Guido Nolte. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and BMC Bioinformatics.

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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