Amin Kharraz
- Signal Processing top 2%
- Information Systems top 2%
- Computer Networks and Communications top 5%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Co-authors
- Engin KirdaWilliam RobertsonSajjad ArshadCollin MullinerJoshua MasonMichael BaileyZane MaManos Antonakakis
- Topics
- Advanced Malware Detection Techniques (10 papers)Spam and Phishing Detection (5 papers)Digital and Cyber Forensics (4 papers)
- Journals
- IEEE Communications MagazineIEEE Security & PrivacyUSENIX Security Symposium
- Partner nations
- United StatesMexicoUnited Kingdom
In The Last Decade
Amin Kharraz
13 papers receiving 413 citations
Hit Papers
Peers
Comparison fields: 5 of 41
- Signal Processing 333
- Information Systems 294
- Computer Networks and Communications 254
- Artificial Intelligence 123
- Computer Vision and Pattern Recognition 27
Countries citing papers authored by Amin Kharraz
This map shows the geographic impact of Amin Kharraz'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 Amin Kharraz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amin Kharraz more than expected).
Fields of papers citing papers by Amin Kharraz
This network shows the impact of papers produced by Amin Kharraz. 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 Amin Kharraz. The network helps show where Amin Kharraz may publish in the future.
Co-authorship network of co-authors of Amin Kharraz
This figure shows the co-authorship network connecting the top 25 collaborators of Amin Kharraz. A scholar is included among the top collaborators of Amin Kharraz 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 Amin Kharraz. Amin Kharraz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 16 | |
| 8 | 13 | |
| 9 | {USBESAFE}: An End-Point Solution to Protect Against USB-Based Attacks | 4 |
| 10 | 63 | |
| 11 | 33 | |
| 12 | 24 | |
| 13 | UNVEIL: a large-scale, automated approach to detecting ransomwarebreakdown → | 232 |
| 14 | 33 |
About Amin Kharraz
Amin Kharraz is a scholar working on Signal Processing, Information Systems and Software, having authored 14 papers that have together received 427 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (10 papers), Spam and Phishing Detection (5 papers) and Digital and Cyber Forensics (4 papers). The work is most often cited by research in Signal Processing (333 citations), Information Systems (294 citations) and Computer Networks and Communications (254 citations). Amin Kharraz has collaborated with scholars based in United States, Mexico and United Kingdom. Frequent co-authors include Engin Kirda, William Robertson, Sajjad Arshad, Collin Mulliner, Joshua Mason, Michael Bailey, Zane Ma, Manos Antonakakis, Andrew N. Miller and Charles Lever. Their work appears in journals such as IEEE Communications Magazine, IEEE Security & Privacy and USENIX Security Symposium.
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.