RUNNING XSCOPE 3RD PARTY CMOS WINDOWS

The goal was the extraction of changing dynamics or anomalous activity in the underlying computer system. The data analysis was based on nonlinear dynamics and graph theory to improve detection of anomalous events in cyber applications. To detect cyber-attacks in EDS, we developed a framework for gathering and analyzing timing data that involves establishing a baseline execution profile and then capturing the effect of perturbations in the state from injecting various malware. Hence, there is a critical need for novel methods to detect, prevent, and mitigate effects of such attacks. Consequently, cyber-attacks pose a real and pertinent threat, as evidenced by Stuxnet, Shamoon and Dragonfly.

EDS are increasingly dependent on networked computing assets, as are many Industrial Control Systems.

RUNNING XSCOPE 3RD PARTY CMOS WINDOWS

The experiments show that our system can detect windows kernel rootkits with high accuracy and moderate performance cost.Įnergy Delivery Systems (EDS) are a network of processes that produce, transfer and distribute energy. By combining the hardware assisted virtualization and machine learning techniques, our kernel rootkit detection solution could be potentially applied in the cloud environment. To select the important run-time features for training our detection models, we utilize the TF-IDF method. Compared with previous methods, VKRD can provide a transparent and efficient execution environment for the target kernel module to reveal its run-time behavior. To address these problems, we propose VKRD, a kernel rootkit detection system based on the hardware assisted virtualization technology. However, existing methods suffer from some limitations: 1) most methods focus on user-mode rootkit detection 2) some methods are limited to detect obfuscated kernel modules 2) some methods introduce significant performance overhead. To defeat kernel rootkits, many approaches have been proposed in the past few years.

Once a rootkit is loaded into the kernel space, it can carry out arbitrary malicious operations with high privilege. A popular way to compromise OS kernel is through a kernel rootkit (i.e., malicious kernel module). OS kernel is the core part of the operating system, and it plays an important role for OS resource management. Therefore, the technique is resistant to attempts to conceal the malicious nature of a kernel module. Our technique relies on an abstract model of module behavior that is not affected by small changes in the binary image of the module. Through this method, it is possible to provide additional protection against this type of malicious modification of the kernel. This paper presents a technique that exploits binary analysis to ascertain, at load time, if a module's behavior resembles the behavior of a rootkit. Instead, these rootkits operate within the kernel, modifying critical data structures such as the system call table or the list of currently-loaded kernel modules. These rootkits are implemented as kernel modules, and they do not require modification of user-space binaries to conceal malicious activity. However, for operating systems that support loadable kernel modules (e.g., Linux and Solaris), a new type of rootkit has recently emerged. Originally, root-kits mainly included modified versions of system auditing programs (e.g., ps or netstat on a Unix system). A rootkit is a collection of tools used by intruders to keep the legitimate users and administrators of a compromised machine unaware of their presence.

Running xscope 3rd party cmos