Data Poison Detection Schemes for Distributed Machine Learning

Asynchronous Distributed Data Parallelism for Machine Learning

Distributed machine learning has gained much attention due to recent proliferation of large scale learning problems. Designing a high-performance framework poses many challenges and opportunities for system engineers. This paper presents a novel architecture for solving distributed learning problems in framework of data parallelism where model replicas are trained over multiple worker nodes. Wo...

A Hybrid Machine Learning Method for Intrusion Detection

Data security is an important area of concern for every computer system owner. An intrusion detection system is a device or software application that monitors a network or systems for malicious activity or policy violations. Already various techniques of artificial intelligence have been used for intrusion detection. The main challenge in this area is the running speed of the available implemen...

Machine Learning Models for Housing Prices Forecasting using Registration Data

This article has been compiled to identify the best model of housing price forecasting using machine learning methods with maximum accuracy and minimum error. Five important machine learning algorithms are used to predict housing prices, including Nearest Neighbor Regression Algorithm (KNNR), Support Vector Regression Algorithm (SVR), Random Forest Regression Algorithm (RFR), Extreme Gradient B...

Can you Poison a Machine Learning Algorithm ?

A Review on Malware Detection Schemes Using Machine Learning Techniques

Malware is a one type of software which can harm the computer’s operating system and it may also steal the personal information from the computer. Malware can be made by using any programming language by the programmer. It is very difficult to define a malware with a single term or a single name. A malware can be considered as a malicious software or malcode or it is also known as a malicious c...