preprintOct 12, 2017GREEN OA

DeepXplore

Columbia University · Lehigh University

Indexed inarxivcrossref

Abstract

Deep learning (DL) systems are increasingly deployed in safety- and security-critical domains including self-driving cars and malware detection, where the correctness and predictability of a system's behavior for corner case inputs are of great importance. Existing DL testing depends heavily on manually labeled data and therefore often fails to expose erroneous behaviors for rare inputs.

Citation impact

1,245
total citations
FWCI
99.72
Percentile
100%
References
81
Citations per year

Authors

4

Topics & keywords

Keywords
  • Correctness
  • Computer science
  • Malware
  • Predictability
  • Computer security
  • Artificial intelligence
  • Algorithm
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