Закрыт

design and development of cloud environment using machine learning approaches

Proposed work shall start with the collection of Network logs and user application logs and stored in whether Elastics Block Storage or Dynamo DB or virtual HDFS in Cloud.

2) Extraction of Attack features by preprocessing the Data.

3) Identification of Potential Attack Paths.

4) Various machine learning Classifier techniques will be adopted for extraction of features and their respective classes.

5) Validation of proposed solutions by applying different attacks & compare it with outcome of proposed solution

Навыки: Machine Learning (ML), Java, Алгоритмы, Интеллектуальный анализ данных, Python

Показать больше: design development inventory management using struts framework, Stock Market Prediction using Machine Learning Algorithm, real-time network anomaly detection system using machine learning, aws machine learning, ai cloud computing, machine learning and cloud computing projects, machine learning in cloud security, what is cloud computing, machine learning platform, running machine learning on cloud, machine learning algorithms in cloud computing frameworks, network traffic anomaly detection using machine learning approaches, predicting football scores using machine learning techniques, stock market prediction using machine learning techniques, android apps using machine learning, survey of review spam detection using machine learning techniques, sales prediction using machine learning, stock market prediction using machine learning, data integration using machine learning, twitter sentiment analysis using machine learning techniques

О работодателе:
( 0 отзыв(-а, -ов) ) Bhopal, India

ID проекта: #26282485

1 фрилансер в среднем готов выполнить эту работу за ₹12500

ibrahimanjum330

Hi, I am Ibrahim, and I am a data scienitst, I have great expertise, in statistics, R and Python. I have an experience in predictive algorithms and statistical softwares like SPSS. Please provide more details on the Больше

₹12500 INR за 2 дней(-я)
(29 отзывов(-а))
5.3