Nir Nissim

2.4k citations
51 papers · 1.5k · 1 hit paper · h-index 25

Impact in

Papers in

Nir Nissim

48 papers receiving 1.5k citations

Nir Nissim's Hit Papers

Dynamic Malware Analysis in the Modern Era—A State of the Art Survey 2019 · 208 citations
2080+2+4Years since publication50100150200

Peers

Nir Nissim
Comparison fields: 5 of 90
  • Signal Processing 1.2k
  • Computer Networks and Communications 984
  • Information Systems 777
  • Software 77
  • Artificial Intelligence 556
Replace N. Cercone with:
N. Cercone Canada
Tao Ban Japan
Parvez Faruki India
Robert K. Cunningham United States
Jack W. Stokes United States
Yinzhi Cao United States
Udaya Tupakula Australia
Deguang Kong United States
Golden G. Richard United States
Nir Nissim relative to N. Cercone Canada N. Cercone's profile →
Citations per field
00.5×10×20×32.3×
N. Cercone · 1×
Citations per year

Countries citing papers authored by Nir Nissim

Since Specialization
Citations

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

Fields of papers citing papers by Nir Nissim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Nir Nissim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nir Nissim Line = papers co-authored together Nir Nissim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Dynamic Malware Analysis in the Modern Era—A State of the Art Survey
Hit paper breakdown →
2019208
2 201892
3 201483
4 200877
5 201666
6 201463
7 201754
8 201654
9 201252
10 200945
11 201844
12 202039
13 202137
14 201934
15 202234
16 201630
17 201429
18 202129
19 201629
20 201827

About Nir Nissim

Nir Nissim is a scholar working on Signal Processing, Computer Networks and Communications, Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 51 papers that have together received 1.5k indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (36 papers), Network Security and Intrusion Detection (30 papers), Spam and Phishing Detection (12 papers), Anomaly Detection Techniques and Applications (7 papers), Digital and Cyber Forensics (6 papers), User Authentication and Security Systems (5 papers), Time Series Analysis and Forecasting (4 papers) and Functional Brain Connectivity Studies (3 papers). The work is most often cited by research in Signal Processing (1.2k citations), Computer Networks and Communications (984 citations), Information Systems (777 citations), Software (77 citations) and Artificial Intelligence (556 citations). Nir Nissim has collaborated with scholars based in Israel, United States and United Kingdom. Frequent co-authors include Yuval Elovici, Aviad Cohen, Lior Rokach, Robert Moskovitch, Clint Feher, Yuval Shaḥar, Chanan Glezer, Denis Klimov, Rami Puzis and Nathalie Japkowicz. Their work appears in journals such as Computers & Security, IEEE Access, Expert Systems with Applications, Knowledge-Based Systems and Neural Networks.

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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