In a contemporary data center, Linux applications often generate a large quantity of real-time
system call traces, which are not suitable for traditional host-based intrusion detection …

In the current network-based computing world, where the number of interconnected devices
grows exponentially, their diversity, malfunctions, and cybersecurity threats are increasing at …

According to the Fire-eye's M-Trends Annual Threat Report 2022, there are many advanced
persistent threat (APT) attacks that are currently in use, and such continuous and specialized …

Abstract Host-based Intrusion Detection System (HIDS) is an effective last line of defense for
defending against cyber security attacks after perimeter defenses (eg, Network-based …

Intrusion detection systems have proliferated with varying capabilities for data generation
and learning towards detecting abnormal behavior. The goal of green intrusion detection …

Cybercrime has led to the loss of billions of dollars, the malfunctioning of computer systems,
the destruction of critical information, the compromising of network integrity and …

Machine Learning (ML) has been widely applied to cybersecurity and is considered state-of-
the-art for solving many of the open issues in that field. However, it is very difficult to evaluate …

Zero-day vulnerabilities continue to be a threat as they are unknown to vendors; when
attacks occur, vendors have zero days to provide remedies. New techniques for the …

Linux containers are gaining increasing traction in both individual and industrial use, and as
these containers get integrated into mission-critical systems, real-time detection of malicious …

In this paper, we present the results of using bags of system calls for learning the behavior of
Linux containers for use in anomaly-detection based intrusion detection system. By using …