The Intrusion Detection System (IDS) is an effective tool utilized in cybersecurity systems to
detect and identify intrusion attacks. With the increasing volume of data generation, the …

Intrusions constitute one of the main issues in computer network security. Through malicious
actions, hackers can have unauthorised access that compromises the integrity, the …

The growing prevalence of network attacks is a well-known problem which can impact the
availability, confidentiality, and integrity of critical information for both individuals and …

Anomaly detection in a network is one of the prime concerns for network security. In this
work, a novel Channel Boosted and Residual learning based deep Convolutional Neural …

Feature selection is becoming a major preprocessing phase in which irrelevant and
redundant features are removed, while the more informative ones are retained. The datasets …

We propose a method for DDoS detection by constructing a fuzzy estimator on the mean
packet inter arrival times. We divided the problem into two challenges, the first being the …

Due to the complex and time-varying network environments, traditional methods are difficult
to extract accurate features of intrusion behavior from the high-dimensional data samples …

Proactively forecasting disputes in the initiation phase of public-private partnership (PPP)
projects can considerably reduce the effort, time, and cost of managing potential claims. This …

Anomaly intrusion detection is an important issue in computer network security. As a step of
data preprocessing, attribute normalization is essential to detection performance. However …

While Internet and network technology have been growing rapidly, cyber attack incidents
also increase accordingly. The increasing occurrence of network attacks is an important …