Taxonomist: Application Detection Through Rich Monitoring Data
| Autor: | Ozan Tuncer, Emre Ates, Jim Brandt, Manuel Egele, Ayse K. Coskun, Vitus J. Leung, Ata Turk |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Cryptocurrency
business.industry Computer science Password cracking ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology computer.software_genre Supercomputer 01 natural sciences Scheduling (computing) Scripting language Monitoring data 0103 physical sciences 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 010306 general physics Software engineering business computer |
| Zdroj: | Euro-Par 2018: Parallel Processing ISBN: 9783319969824 Euro-Par |
| DOI: | 10.1007/978-3-319-96983-1_7 |
| Popis: | Modern supercomputers are shared among thousands of users running a variety of applications. Knowing which applications are running in the system can bring substantial benefits: knowledge of applications that intensively use shared resources can aid scheduling; unwanted applications such as cryptocurrency mining or password cracking can be blocked; system architects can make design decisions based on system usage. However, identifying applications on supercomputers is challenging because applications are executed using esoteric scripts along with binaries that are compiled and named by users. |
| Databáze: | OpenAIRE |
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