The popularity and usage of Cloud computing is increasing rapidly. Several companies are investing in this field either for their own use or to provide it as a service others. One the results development emergence various security problems both industry consumer. ways secure by using Machine Learning (ML). ML techniques have been used prevent detect attacks gaps on Cloud. In paper, we Systemati...

The SIGMOD conference organized by the ACM Special Interest Group on Management of Data is one of the major conferences in the database area. Since databases play an important role in knowledge discovery, the SIGMOD conference is also an important forum for researchers in the KDD area, especially with respect to aspects of KDD which deal with very large data sets. At this years SIGMOD conferenc...

Although researchers have long studied using statistical modeling techniques to detect anomaly intrusion and profile user behavior, the feasibility of applying multinomial logistic regression modeling to predict multi-attack types has not been addressed, and the risk factors associated with individual major attacks remain unclear. To address the gaps, this study used the KDD-cup 1999 data and b...

The Yahoo! music rating data set in KDD Cup 2011 raises several interesting challenges: (1) The data covers a lengthy time period of more than eight years. (2) Not only are training ratings associated date and time information, so are the test ratings. (3) The items form a hierarchy consisting of four types of items: genres, artists, albums and tracks. To capture the rich temporal dynamics with...

In order to defend against extraordinary intelligent attacks in the era of rapidly growing information and technology nowadays, effective and efficient intrusion detection models are needed to detect and prevent intrusion promptly. Bayesian network (BN) classifiers with powerful reasoning capabilities have been increasingly utilized to detect intrusion attacks with reasonable accuracy and effic...

Intrusion detection systems IDS are increasingly utilizing machine learning methods. IDSs important tools for ensuring the security of network data and resources. The Internet Things (IoT) is an expanding intelligent machines sensors. However, they vulnerable to attackers because ubiquitous extensive IoT networks. Datasets from intrusion (IDS) have been analyzed deep methods such as Bidirection...

Abstract Due to the increasing growth of Internet and its widespread application, number attacks on network has also increased. Therefore, maintaining security using intrusion detection systems is critical importance. The connection between devices leads a large data being generated saved. era “big data” emerges over time. This paper presents new method for selecting effective features based co...

These days, security threats detection, generally discussed to as intrusion, has befitted actual significant and serious problem in network, information data security. Thus, an intrusion detection system (IDS) important element computer or network Avoidance of such intrusions wholly bases on ability Intrusion Detection System which productions necessary job it identifies different kinds attacks...