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Yizheng Chen

11 papers hereh-index 151.3k citations34 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author6
  • middle author5

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.CR8
  • cs.LG2
  • cs.SI1
same name
  • Yizheng Chen — 6 papers, h 2
  • Yizheng Chen — 5 papers, h 5
  • Yizheng Chen — 3 papers, h 3
  • Yizheng Chen — 2 papers, h 3
  • Yizheng Chen — 1 paper, h 0
  • Yizheng Chen — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172023
most citedHiding in Plain Sight: A Longitudinal Study of Combosquatting Abuse

109 citations · 247 across the 11 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CR2019★ 9 cited

Cost-Aware Robust Tree Ensembles for Security Applications

Yizheng Chen, Shiqi Wang, Weifan Jiang +2

There are various costs for attackers to manipulate the features of security classifiers. The costs are asymmetric across features and to the directions of changes, which cannot be…

cs.CR2019★ 8 cited

Neutaint: Efficient Dynamic Taint Analysis with Neural Networks

Dongdong She, Yizheng Chen, Abhishek Shah +2

Dynamic taint analysis (DTA) is widely used by various applications to track information flow during runtime execution. Existing DTA techniques use rule-based taint-propagation, wh…

cs.LG2019★ 11 cited

Enhancing Gradient-based Attacks with Symbolic Intervals

Shiqi Wang, Yizheng Chen, Ahmed Abdou +1

Recent breakthroughs in defenses against adversarial examples, like adversarial training, make the neural networks robust against various classes of attackers (e.g., first-order gr…

cs.CR2019★ 6 cited

On Training Robust PDF Malware Classifiers

Yizheng Chen, Shiqi Wang, Dongdong She +1

Although state-of-the-art PDF malware classifiers can be trained with almost perfect test accuracy (99%) and extremely low false positive rate (under 0.1%), it has been shown that…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.