Abdurrahman Pektas

According to our database, Abdurrahman Pektas authored at least 15 papers between 2014 and 2020.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2020

Deep learning for effective Android malware detection using API call graph embeddings.

Abdurrahman Pektas, Tankut Acarman

Soft Comput., 2020

Learning to detect Android malware via opcode sequences.

Abdurrahman Pektas, Tankut Acarman

Neurocomputing, 2020

2019

Deep learning to detect botnet via network flow summaries.

Abdurrahman Pektas, Tankut Acarman

Neural Comput. Appl., 2019

A deep learning method to detect network intrusion through flow-based features.

Abdurrahman Pektas, Tankut Acarman

Int. J. Netw. Manag., 2019

2018

HoneyThing: A New Honeypot Design for CPE Devices.

Ömer Erdem, Abdurrahman Pektas, Mehmet Kara

KSII Trans. Internet Inf. Syst., 2018

Botnet detection based on network flow summary and deep learning.

Abdurrahman Pektas, Tankut Acarman

Int. J. Netw. Manag., 2018

Malware classification based on API calls and behaviour analysis.

Abdurrahman Pektas, Tankut Acarman

IET Inf. Secur., 2018

2017

Classification of malware families based on runtime behaviors.

Abdurrahman Pektas, Tankut Acarman

J. Inf. Secur. Appl., 2017

Identification of Application in Encrypted Traffic by Using Machine Learning.

Abdurrahman Pektas, Tankut Acarman

Proceedings of the Man-Machine Interactions 5, 2017

Portable Dynamic Malware Analysis with an Improved Scalability and Automatisation.

Abdurrahman Pektas, Tankut Acarman

Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017, 2017

Ensemble Machine Learning Approach for Android Malware Classification Using Hybrid Features.

Abdurrahman Pektas, Tankut Acarman

Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017, 2017

2016

Android Malware Classification by Applying Online Machine Learning.

Abdurrahman Pektas, Mahmut Çavdar, Tankut Acarman

Proceedings of the Computer and Information Sciences - 31st International Symposium, 2016

2015

Classification des logiciels malveillants basée sur le comportement à l'aide de l'apprentissage automatique en ligne. (Behavior based malware classification using online machine learning).

Abdurrahman Pektas

PhD thesis, 2015

Runtime-behavior based malware classification using online machine learning.

Abdurrahman Pektas, Tankut Acarman, Yliès Falcone, Jean-Claude Fernandez

Proceedings of the 2015 World Congress on Internet Security, 2015

2014

A dynamic malware analyzer against virtual machine aware malicious software.

Abdurrahman Pektas, Tankut Acarman

Secur. Commun. Networks, 2014