As the technology is advancing so are data storing practices. Nowadays stored online which main reason as to why constantly under threat. Therefore there an urgent need of computer se- curity for securing this confidential data, mostly customer personal if got leaked will not only pose threat but also organization liable and preserving that data. These unwanted activities termed intrusions dete...

An increasing number of Internet application services are relying on encrypted traffic to offer adequate consumer privacy. Anomaly detection in circumvent and mitigate cyber security threats is, however, an open ongoing research challenge due the limitation existing classification techniques. Deep learning is emerging as a promising paradigm, allowing reduction manual determination feature set ...

With an increase in the number and types of network attacks, traditional firewalls data encryption methods can no longer meet needs current security. As a result, intrusion detection systems have been proposed to deal with threats. The mainstream algorithms are aided machine learning but problems low rates need for extensive feature engineering. To address issue accuracy, this paper proposes mo...

The world has experienced a radical change due to the internet. As matter of fact, it assists people in maintaining their social networks and links them other members when they require assistance. In effect sharing professional personal data comes with several risks individuals organizations. Internet became crucial element our daily life, therefore, security DATA could be threatened at any tim...

Attacks in wireless sensor networks (WSNs) aim to prevent or eradicate the network's ability perform its anticipated functions. Intrusion detection is a defense used that can detect unknown attacks. Due incredible development computer-related applications and massive Internet usage, it indispensable provide host network security. The of hacking technology tries compromise computer security thro...

The widespread acceptance and increase of the Internet mobile technologies have revolutionized our existence. On other hand, world is witnessing suffering due to technologically aided crime methods. These threats, including but not limited hacking intrusions are main concern for security experts. Nevertheless, challenges facing effective intrusion detection methods continue closely associated w...

The Internet of Things (IoT) is a global information and communication technology which aims to connect any type device the internet at time in location. Nowadays billions IoT devices are connected world, this leads easily cause vulnerability devices. increasing users different IoT-related applications more data attacks happening networks after fog layer. To detect reduce deep learning model us...

An intrusion detection system collects and analyzes information from different areas within a computer or a network to identify possible security threats that include threats from both outside as well as inside of the organization. It deals with large amount of data, which contains various irrelevant and redundant features and results in increased processing time and low detection rate. Therefo...

The KDD (Knowledge Discovery in Databases) paradigm is a step by step process for finding interesting patterns in large amounts of data. Data mining is one step in the process. This paper defines the KDD process and discusses three data mining algorithms, neural networks, decision trees, and association/dependency rule algorithms. The algorithms' potential as good analytical tools for performan...