DL 4 MD : A Deep Learning Framework for Intelligent Malware Detection

@inproceedings{Hardy2016DL4M,
  title={DL 4 MD : A Deep Learning Framework for Intelligent Malware Detection},
  author={William Hardy and Lingwei Chen and Shifu Hou and Yanfang Ye and Xin Li},
  year={2016}
}
In the Internet-age, malware poses a serious and evolving threat to security, making the detection of malware of utmost concern. Many research efforts have been conducted on intelligent malware detection by applying data mining and machine learning techniques. Though great results have been obtained with these methods, most of them are built on shallow learning architectures, which are still somewhat unsatisfying for malware detection problems. In this paper, based on the Windows Application… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 23 CITATIONS

DLGraph: Malware Detection Using Deep Learning and Graph Embedding

  • 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)
  • 2018
VIEW 12 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Malware Classification with Deep Convolutional Neural Networks

  • 2018 9th IFIP International Conference on New Technologies, Mobility and Security (NTMS)
  • 2018
VIEW 5 EXCERPTS
CITES METHODS
HIGHLY INFLUENCED

CYBER ATTACK DETECTION IN REMOTE TERMINAL UNIT OF SCADA SYSTEMS

Ali Hasan Dakheel, Osman Nuri Uçan, Oğuz Bayat, Hamzah Hameed Jasim
  • 2019
VIEW 1 EXCERPT

Cyber Attack Prevention using Machine Learning

M Megha.S.
  • 2019
VIEW 1 EXCERPT
CITES METHODS

References

Publications referenced by this paper.
SHOWING 1-10 OF 35 REFERENCES

Greedy Layer-Wise Training of Deep Networks

Bernhard Schölkopf, John Platt, Thomas Hofmann
  • 2007
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Data mining methods for detection of new malicious executables

  • Proceedings 2001 IEEE Symposium on Security and Privacy. S&P 2001
  • 2001
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Cluster-oriented ensemble classifiers for intelligent malware detection

  • Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015)
  • 2015
VIEW 2 EXCERPTS

Poster: Deep Learning for Zero-day Flash Malware Detection

W. Jung, S. Kim, S. Choi
  • IEEE Symposium on Security and Privacy,
  • 2015
VIEW 2 EXCERPTS

The Great Bank Robbery

Kaspersky Lab
  • In http://www.kaspersky. com/about/news/virus/2015/Carbanak-cybergang-steals-1-bn-USDfrom-100-financial-institutions-worldwide,
  • 2015
VIEW 1 EXCERPT

Traffic Flow Prediction With Big Data: A Deep Learning Approach

  • IEEE Transactions on Intelligent Transportation Systems
  • 2015
VIEW 2 EXCERPTS

Similar Papers

Loading similar papers…