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Xiaojiang Du

92 papers hereh-index 7824.9k citations664 works total

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

author position
  • middle author69
  • last author14

Across the 83 of 92 papers where every author was matched, so the position is known.

fields
  • cs.CR64
  • cs.NI10
  • cs.CV7
  • cs.GT2
  • cs.LG2
  • cs.CL1
same name
  • Xiaojiang Du — 5 papers, h 3
  • Xiaojiang Du — 2 papers, h 1
  • Xiaojiang Du — 2 papers, h 5
  • Xiaojiang Du — 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 citedAdversarial Samples on Android Malware Detection Systems for IoT Systems

79 citations · 199 across the 34 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.CV2020★ 1 cited

Robust Attacks on Deep Learning Face Recognition in the Physical World

Meng Shen, Hao Yu, Liehuang Zhu +3

Deep neural networks (DNNs) have been increasingly used in face recognition (FR) systems. Recent studies, however, show that DNNs are vulnerable to adversarial examples, which can…

cs.IT2020

Performance Analysis and Optimization for the MAC Protocol in UAV-based IoT Network

Bin Li, Xianzhen Guo, Ruonan Zhang +2

Unmanned aerial vehicles (UAVs) have played an important role in air-ground integration network. Especially in Internet of Things (IoT) services, UAV equipped with communication eq…

cs.CR2020★ 1 cited

Privacy-Preserving Machine Learning Training in Aggregation Scenarios

Liehuang Zhu, Xiangyun Tang, Meng Shen +2

To develop Smart City, the growing popularity of Machine Learning (ML) that appreciates high-quality training datasets generated from diverse IoT devices raises natural questions a…

cs.CR2020

SFE-GACN: A Novel Unknown Attack Detection Method Using Intra Categories Generation in Embedding Space

Ao Liu, Yunpeng Wang, Tao Li

In the encrypted network traffic intrusion detection, deep learning based schemes have attracted lots of attention. However, in real-world scenarios, data is often insufficient (fe…

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