Emmanuel S. Pilli

3.2k citations
103 papers · 2.1k indexed · 1 hit paper · h-index 20

Emmanuel S. Pilli

98 papers receiving 2.0k citations

Hit Papers

A Detailed Investigation and Analysis of Using Machine Le...4762018202620202023100200300400

Peers

Emmanuel S. Pilli
Comparison fields: 5 of 91
  • Signal Processing 945
  • Computer Networks and Communications 1.6k
  • Information Systems 920
  • Artificial Intelligence 1.0k
  • Hardware and Architecture 42
Replace Hassan Habibi Gharakheili with:
Hassan Habibi Gharakheili Australia
Qiben Yan United States
Dongho Won South Korea
Constantinos Kolias United States
Rosli Salleh Malaysia
Ibrahim Ghafir United Kingdom
Giovanni Russello New Zealand
Leonardo Aniello Italy
Shahid Raza Sweden
Abdelwahab Hamou‐Lhadj Canada
Emmanuel S. Pilli relative to Hassan Habibi Gharakheili Australia Hassan Habibi Gharakheili's profile →
Citations per field
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Hassan Habibi Gharakheili · 1×
Citations per year

Countries citing papers authored by Emmanuel S. Pilli

Since Specialization
Citations

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

Fields of papers citing papers by Emmanuel S. Pilli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emmanuel S. Pilli. 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 Emmanuel S. Pilli. The network helps show where Emmanuel S. Pilli may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Emmanuel S. Pilli, 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 Emmanuel S. Pilli Line = papers co-authored together Emmanuel S. Pilli links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20240
3 20240
4 202312
5 20233
6 20225
7 202112
8 20212
9 202010
10 20194
11
Survey of Peer-to-Peer Botnets and Detection Frameworks.
201814
12 20180
13 201716
14 20155
15 20151
16 201513
17 20142
18
A Generic Process Model for Botnet Forensic Analysis
20136
19 201375
20 20132

About Emmanuel S. Pilli

Emmanuel S. Pilli is a scholar working on Signal Processing, Computer Networks and Communications and Information Systems, having authored 103 papers that have together received 2.1k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (42 papers), Advanced Malware Detection Techniques (42 papers), IoT and Edge/Fog Computing (20 papers), Internet Traffic Analysis and Secure E-voting (18 papers), Cloud Computing and Resource Management (16 papers), Digital and Cyber Forensics (14 papers), Cloud Data Security Solutions (10 papers) and Spam and Phishing Detection (7 papers). The work is most often cited by research in Signal Processing (945 citations), Computer Networks and Communications (1.6k citations) and Information Systems (920 citations). Emmanuel S. Pilli has collaborated with scholars based in India, Australia and United States. Frequent co-authors include Preeti Mishra, Vijay Varadharajan, Udaya Tupakula, R. C. Joshi, Mahesh Chandra Govil, Rajdeep Niyogi, Girdhari Singh, Arka Prokash Mazumdar, Pankaj Kumar Keserwani and C. Rama Krishna. Their work appears in journals such as IEEE Communications Surveys & Tutorials, IEEE Access and Applied Soft Computing.

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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