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Description
Hardware-Assisted Security (HAS) is an emerging technology that addresses the shortcomings of software-based virtualized environment. There are two major weaknesses of software-based virtualization that HAS attempts to address - performance overhead and security issues. Performance overhead caused by software-based virtualization is due to the use of additional software layer (i.e.,

Hardware-Assisted Security (HAS) is an emerging technology that addresses the shortcomings of software-based virtualized environment. There are two major weaknesses of software-based virtualization that HAS attempts to address - performance overhead and security issues. Performance overhead caused by software-based virtualization is due to the use of additional software layer (i.e., hypervisor). Since the performance is highly related to efficiency of processing data and providing services, reducing performance overhead is one of the major concerns in data centers and enterprise networks. Software-based virtualization also imposes additional security issues in the virtualized environments. To resolve those issues, HAS is developed to offload security functions from application layer to a dedicated hardware, thereby achieving almost bare-metal performance and enhanced security. As a result, HAS gained

more popularity and the number of studies regarding efficiency of the technology is increasing.

However, there exists no attempt to our knowledge that provides a generic test mechanism that is universally applicable to all HAS devices. Preparing such a testbed for each specific HAS device is a time-consuming and costly task for hardware manufacturers and network administrators. Therefore, we try to address the demands of hardware vendors and researchers for a generic testbed that can evaluate both performance and security functions of the HAS-enabled systems.

In this thesis, the HAS device evaluation framework (HEF) is defined for hardware vendors, network administrators, and researchers to measure performance of the system with HAS devices. HEF provides a generic test environments for a given HAS device by providing generic test metrics and evaluation mechanisms. HEF is also designed to take user-defined test metrics and test cases to support various hardware. The framework performs the entire process in an automated fashion, and thus it requires no user intervention. Finally, the efficacy of HEF is demonstrated by performing a case study using Intel QuickAssist Technology (QAT) adapter, which is a dedicated PCI express device for cryptographic tasks.
ContributorsKyung, Sukwha (Author) / Ahn, Gail-Joon (Thesis advisor) / Doupe, Adam (Committee member) / Zhao, Ziming (Committee member) / Arizona State University (Publisher)
Created2017
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Description
E-Mail header injection vulnerability is a class of vulnerability that can occur in web applications that use user input to construct e-mail messages. E-Mail injection is possible when the mailing script fails to check for the presence of e-mail headers in user input (either form fields or URL parameters). The

E-Mail header injection vulnerability is a class of vulnerability that can occur in web applications that use user input to construct e-mail messages. E-Mail injection is possible when the mailing script fails to check for the presence of e-mail headers in user input (either form fields or URL parameters). The vulnerability exists in the reference implementation of the built-in “mail” functionality in popular languages like PHP, Java, Python, and Ruby. With the proper injection string, this vulnerability can be exploited to inject additional headers and/or modify existing headers in an e-mail message, allowing an attacker to completely alter the content of the e-mail.

This thesis develops a scalable mechanism to automatically detect E-Mail Header Injection vulnerability and uses this mechanism to quantify the prevalence of E- Mail Header Injection vulnerabilities on the Internet. Using a black-box testing approach, the system crawled 21,675,680 URLs to find URLs which contained form fields. 6,794,917 such forms were found by the system, of which 1,132,157 forms contained e-mail fields. The system used this data feed to discern the forms that could be fuzzed with malicious payloads. Amongst the 934,016 forms tested, 52,724 forms were found to be injectable with more malicious payloads. The system tested 46,156 of these and was able to find 496 vulnerable URLs across 222 domains, which proves that the threat is widespread and deserves future research attention.
ContributorsChandramouli, Sai Prashanth (Author) / Doupe, Adam (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Zhao, Ziming (Committee member) / Arizona State University (Publisher)
Created2016