Biblio

The relevance of data protection is related to the intensive informatization of various aspects of society and the need to prevent unauthorized access to them. World spending on ensuring information security (IS) for the current state: expenses in the field of IS today amount to \$81.7 billion. Expenditure forecast by 2020: about \$105 billion [1]. Information protection of military facilities is the most critical in the public sector, in the non-state - financial organizations is one of the leaders in spending on information protection. An example of the importance of IS research is the Trojan encoder WannaCry, which infected hundreds of thousands of computers around the world, attacks are recorded in more than 116 countries. The attack of the encoder of WannaCry (Wana Decryptor) happens through a vulnerability in service Server Message Block (protocol of network access to file systems) of Windows OS. Then, a rootkit (a set of malware) was installed on the infected system, using which the attackers launched an encryption program. Then each vulnerable computer could become infected with another infected device within one local network. Due to these attacks, about \$70,000 was lost (according to data from 18.05.2017) [2]. It is assumed in the presented work, that the software level of information protection is fundamentally insufficient to ensure the stable functioning of critical objects. This is due to the possible hardware implementation of undocumented instructions, discussed later. The complexity of computing systems and the degree of integration of their components are constantly growing. Therefore, monitoring the operation of the computer hardware is necessary to achieve the maximum degree of protection, in particular, data processing methods.

Application whitelisting software allows only examined and trusted applications to run on user's machine. Since many malicious files don't require administrative privileges in order for them to be executed, whitelisting can be the only way to block the execution of unauthorized applications in enterprise environment and thus prevent infection or data breach. In order to assess the current state of such solutions, the access to three whitelisting solution licenses was obtained with the purpose to test their effectiveness against different modern types of ransomware found in the wild. To conduct this study a virtual environment was used with Windows Server and Enterprise editions installed. The objective of this paper is not to evaluate each vendor or make recommendations of purchasing specific software but rather to assess the ability of application control solutions to block execution of ransomware files, as well as assess the potential for future research. The results of the research show the promise and effectiveness of whitelisting solutions.

This is very true for the Windows operating system (OS) used by government and private organizations. With Windows, the closed source nature of the operating system has unfortunately meant that hidden security issues are discovered very late and the fixes are not found in real time. There needs to be a reexamination of current static methods of malware detection. This paper presents an integrated system for automated and real-time monitoring and prediction of rootkit and malware threats for the Windows OS. We propose to host the target Windows machines on the widely used Xen hypervisor, and collect process behavior using virtual memory introspection (VMI). The collected data will be analyzed using state of the art machine learning techniques to quickly isolate malicious process behavior and alert system administrators about potential cyber breaches. This research has two focus areas: identifying memory data structures and developing prediction tools to detect malware. The first part of research focuses on identifying memory data structures affected by malware. This includes extracting the kernel data structures with VMI that are frequently targeted by rootkits/malware. The second part of the research will involve development of a prediction tool using machine learning techniques.

The advancement in technology has changed how people work and what software and hardware people use. From conventional personal computer to GPU, hardware technology and capability have dramatically improved so does the operating systems that come along. Unfortunately, current industry practice to compare OS is performed with single perspective. It is either benchmark the hardware level performance or performs penetration testing to check the security features of an OS. This rigid method of benchmarking does not really reflect the true performance of an OS as the performance analysis is not comprehensive and conclusive. To illustrate this deficiency, the study performed hardware level and operational level benchmarking on Windows XP, Windows 7 and Windows 8 and the results indicate that there are instances where Windows XP excels over its newer counterparts. Overall, the research shows Windows 8 is a superior OS in comparison to its predecessors running on the same hardware. Furthermore, the findings also show that the automated benchmarking tools are proved less efficient benchmark systems that run on Windows XP and older OS as they do not support DirectX 11 and other advanced features that the hardware supports. There lies the need to have a unified benchmarking approach to compare other aspects of OS such as user oriented tasks and security parameters to provide a complete comparison. Therefore, this paper is proposing a unified approach for Operating System (OS) comparisons with the help of a Windows OS case study. This unified approach includes comparison of OS from three aspects which are; hardware level, operational level performance and security tests.