• 489 Citations
  • 11 h-Index
20072019
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Fingerprint Dive into the research topics where Xinyu Xing is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 19 Similar Profiles
Wireless sensor networks Engineering & Materials Science
Sensor networks Engineering & Materials Science
Bandwidth Engineering & Materials Science
Mobile agents Engineering & Materials Science
Sensor nodes Engineering & Materials Science
Intelligent agents Engineering & Materials Science
Sensors Engineering & Materials Science
World Wide Web Engineering & Materials Science

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Research Output 2007 2019

  • 489 Citations
  • 11 h-Index
  • 33 Conference contribution
  • 6 Article
  • 2 Conference article
  • 1 Letter

Building a Trustworthy Execution Environment to Defeat Exploits from both Cyber Space and Physical Space for ARM

Guan, L., Cao, C., Liu, P., Xing, X., Ge, X., Zhang, S., Yu, M. & Jaeger, T. R., May 1 2019, In : IEEE Transactions on Dependable and Secure Computing. 16, 3, p. 438-453 16 p., 8423674.

Research output: Contribution to journalArticle

Dynamic random access storage
Random access storage
Dynamic mechanical analysis
Cryptography
Internet of things

PTrix: Efficient hardware-assisted fuzzing for COTS binary

Chen, Y., Mu, D., Xu, J., Sun, Z., Shen, W., Xing, X., Lu, L. & Mao, B., Jul 2 2019, AsiaCCS 2019 - Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security. Association for Computing Machinery, Inc, p. 633-645 13 p. (AsiaCCS 2019 - Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Feedback
Hardware
Defects
Program processors
Testing
5 Citations (Scopus)

An empirical evaluation of rule extraction from recurrent neural networks

Wang, Q., Zhang, K., Ororbia, A. G., Xing, X., Liu, X. & Giles, C. L., Sep 1 2018, In : Neural Computation. 30, 9, p. 2568-2591 24 p.

Research output: Contribution to journalLetter

Nonlinear Dynamics
Learning
Evaluation
Recurrent Neural Networks

Defending Against Adversarial Samples Without Security through Obscurity

Guo, W., Wang, Q., Zhang, K., Ororbia, A. G., Huang, S., Liu, X., Giles, C. L., Lin, L. & Xing, X., Dec 27 2018, 2018 IEEE International Conference on Data Mining, ICDM 2018. Institute of Electrical and Electronics Engineers Inc., p. 137-146 10 p. 8594838. (Proceedings - IEEE International Conference on Data Mining, ICDM; vol. 2018-November).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Learning algorithms
Defects
Deep neural networks
Malware

Explaining deep learning models - A Bayesian non-parametric approach

Guo, W., Huang, S., Tao, Y., Xing, X. & Lin, L., Jan 1 2018, In : Advances in Neural Information Processing Systems. 2018-December, p. 4514-4524 11 p.

Research output: Contribution to journalConference article

Learning systems
Image recognition
Deep learning