Posts

Introduction

DevSecOps

CONTINUE READING

Link: https://www.igi-global.com/publish/call-for-papers/call-details/5243 Introduction Machine Learning is making our daily lives as digital as possible, and this new era is called Artificial Intelligence. The binding force behind the rapid growth of machine learning (or deep learning) is enterprises’ technological advances. In recent years, machine learning algorithms have been applied widely in various fields, such as healthcare, transportation, energy, autonomous car, and many more. With the rapid developments of deep learning applications, it is crucial to understand the security concern into account when implementing the models.

CONTINUE READING

6G and Artificial Intelligence With Security Problems 6G solutions with Adversarial Machine Learning Attacks: Millimeter Wave Beam Prediction Use-Case 6G is the next generation for the communication systems. In recent years, machine learning algorithms have been applied widely in various fields such as health, transportation, and the autonomous car. The predictive algorithms will be used in 6G problems. With the rapid developments of deep learning techniques, it is critical to take the security concern into account to apply the algorithms.

CONTINUE READING

My Deep Learning based Malware Detection and Classification presentation.

Presentation Link

CONTINUE READING

Data Privacy and Privacy Preserving Techniques

CONTINUE READING

There are several attacks against deep learning models in the literature, including fast-gradient sign method (FGSM), basic iterative method (BIM) or momentum iterative method (MIM) attacks. These attack are the purest form of the gradient-based evading technique that is used by attackers to evade the classification model. Cite The Code If you find those results useful please cite this paper : @PROCEEDINGS{catak-adv-ml-2020, title = {Deep Neural Network based Malicious Network Activity Detection Under Adversarial Machine Learning Attacks}, booktitle = {Proc.

CONTINUE READING

A GENERATIVE MODEL BASED ADVERSARIAL SECURITY OF DEEP LEARNING AND LINEAR CLASSIfiER MODELS____________________ A PREPRINT Ferhat Ozgur Catak Simula Research laboratory Oslo, Norway ozgur@simula.no Samed Sivaslioglu TUBITAK BILGEM, Kocaeli, Turkey samedsivaslioglu@gmail.com Kevser Sahinbas Department of Management Information System Istanbul Medipol University Istanbul, Turkey ksahinbas@medipol.edu.tr October 17, 2020 ABSTRACT In recent years, machine learning algorithms have been applied widely in various fields such as health, transportation, and the autonomous car.

CONTINUE READING

Homomorphic encryption based border control

CONTINUE READING

Hadoop Mapreduce based Extreme learning machine for Big Data

CONTINUE READING

CONTINUE READING