Matching Items (6)
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- All Subjects: network security
- Genre: Academic theses
- Genre: Masters Thesis
- Creators: Ahn, Gail-Joon
- Member of: Theses and Dissertations
Description
Corporations invest considerable resources to create, preserve and analyze
their data; yet while organizations are interested in protecting against
unauthorized data transfer, there lacks a comprehensive metric to discriminate
what data are at risk of leaking.
This thesis motivates the need for a quantitative leakage risk metric, and
provides a risk assessment system, called Whispers, for computing it. Using
unsupervised machine learning techniques, Whispers uncovers themes in an
organization's document corpus, including previously unknown or unclassified
data. Then, by correlating the document with its authors, Whispers can
identify which data are easier to contain, and conversely which are at risk.
Using the Enron email database, Whispers constructs a social network segmented
by topic themes. This graph uncovers communication channels within the
organization. Using this social network, Whispers determines the risk of each
topic by measuring the rate at which simulated leaks are not detected. For the
Enron set, Whispers identified 18 separate topic themes between January 1999
and December 2000. The highest risk data emanated from the legal department
with a leakage risk as high as 60%.
their data; yet while organizations are interested in protecting against
unauthorized data transfer, there lacks a comprehensive metric to discriminate
what data are at risk of leaking.
This thesis motivates the need for a quantitative leakage risk metric, and
provides a risk assessment system, called Whispers, for computing it. Using
unsupervised machine learning techniques, Whispers uncovers themes in an
organization's document corpus, including previously unknown or unclassified
data. Then, by correlating the document with its authors, Whispers can
identify which data are easier to contain, and conversely which are at risk.
Using the Enron email database, Whispers constructs a social network segmented
by topic themes. This graph uncovers communication channels within the
organization. Using this social network, Whispers determines the risk of each
topic by measuring the rate at which simulated leaks are not detected. For the
Enron set, Whispers identified 18 separate topic themes between January 1999
and December 2000. The highest risk data emanated from the legal department
with a leakage risk as high as 60%.
ContributorsWright, Jeremy (Author) / Syrotiuk, Violet (Thesis advisor) / Davulcu, Hasan (Committee member) / Yau, Stephen (Committee member) / Arizona State University (Publisher)
Created2014
Description
Cloud computing is known as a new and powerful computing paradigm. This new generation of network computing model delivers both software and hardware as on-demand resources and various services over the Internet. However, the security concerns prevent users from adopting the cloud-based solutions to fulfill the IT requirement for many business critical computing. Due to the resource-sharing and multi-tenant nature of cloud-based solutions, cloud security is especially the most concern in the Infrastructure as a Service (IaaS). It has been attracting a lot of research and development effort in the past few years.
Virtualization is the main technology of cloud computing to enable multi-tenancy.
Computing power, storage, and network are all virtualizable to be shared in an IaaS system. This important technology makes abstract infrastructure and resources available to users as isolated virtual machines (VMs) and virtual networks (VNs). However, it also increases vulnerabilities and possible attack surfaces in the system, since all users in a cloud share these resources with others or even the attackers. The promising protection mechanism is required to ensure strong isolation, mediated sharing, and secure communications between VMs. Technologies for detecting anomalous traffic and protecting normal traffic in VNs are also needed. Therefore, how to secure and protect the private traffic in VNs and how to prevent the malicious traffic from shared resources are major security research challenges in a cloud system.
This dissertation proposes four novel frameworks to address challenges mentioned above. The first work is a new multi-phase distributed vulnerability, measurement, and countermeasure selection mechanism based on the attack graph analytical model. The second work is a hybrid intrusion detection and prevention system to protect VN and VM using virtual machines introspection (VMI) and software defined networking (SDN) technologies. The third work further improves the previous works by introducing a VM profiler and VM Security Index (VSI) to keep track the security status of each VM and suggest the optimal countermeasure to mitigate potential threats. The final work is a SDN-based proactive defense mechanism for a cloud system using a reconfiguration model and moving target defense approaches to actively and dynamically change the virtual network configuration of a cloud system.
Virtualization is the main technology of cloud computing to enable multi-tenancy.
Computing power, storage, and network are all virtualizable to be shared in an IaaS system. This important technology makes abstract infrastructure and resources available to users as isolated virtual machines (VMs) and virtual networks (VNs). However, it also increases vulnerabilities and possible attack surfaces in the system, since all users in a cloud share these resources with others or even the attackers. The promising protection mechanism is required to ensure strong isolation, mediated sharing, and secure communications between VMs. Technologies for detecting anomalous traffic and protecting normal traffic in VNs are also needed. Therefore, how to secure and protect the private traffic in VNs and how to prevent the malicious traffic from shared resources are major security research challenges in a cloud system.
This dissertation proposes four novel frameworks to address challenges mentioned above. The first work is a new multi-phase distributed vulnerability, measurement, and countermeasure selection mechanism based on the attack graph analytical model. The second work is a hybrid intrusion detection and prevention system to protect VN and VM using virtual machines introspection (VMI) and software defined networking (SDN) technologies. The third work further improves the previous works by introducing a VM profiler and VM Security Index (VSI) to keep track the security status of each VM and suggest the optimal countermeasure to mitigate potential threats. The final work is a SDN-based proactive defense mechanism for a cloud system using a reconfiguration model and moving target defense approaches to actively and dynamically change the virtual network configuration of a cloud system.
ContributorsChung, Chun-Jen (Author) / Huang, Dijiang (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Xue, Guoliang (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2015
Description
Compartmentalizing access to content, be it websites accessed in a browser or documents and applications accessed outside the browser, is an established method for protecting information integrity [12, 19, 21, 60]. Compartmentalization solutions change the user experience, introduce performance overhead and provide varying degrees of security. Striking a balance between usability and security is not an easy task. If the usability aspects are neglected or sacrificed in favor of more security, the resulting solution would have a hard time being adopted by end-users. The usability is affected by factors including (1) the generality of the solution in supporting various applications, (2) the type of changes required, (3) the performance overhead introduced by the solution, and (4) how much the user experience is preserved. The security is affected by factors including (1) the attack surface of the compartmentalization mechanism, and (2) the security decisions offloaded to the user. This dissertation evaluates existing solutions based on the above factors and presents two novel compartmentalization solutions that are arguably more practical than their existing counterparts.
The first solution, called FlexICon, is an attractive alternative in the design space of compartmentalization solutions on the desktop. FlexICon allows for the creation of a large number of containers with small memory footprint and low disk overhead. This is achieved by using lightweight virtualization based on Linux namespaces. FlexICon uses two mechanisms to reduce user mistakes: 1) a trusted file dialog for selecting files for opening and launching it in the appropriate containers, and 2) a secure URL redirection mechanism that detects the user’s intent and opens the URL in the proper container. FlexICon also provides a language to specify the access constraints that should be enforced by various containers.
The second solution called Auto-FBI, deals with web-based attacks by creating multiple instances of the browser and providing mechanisms for switching between the browser instances. The prototype implementation for Firefox and Chrome uses system call interposition to control the browser’s network access. Auto-FBI can be ported to other platforms easily due to simple design and the ubiquity of system call interposition methods on all major desktop platforms.
The first solution, called FlexICon, is an attractive alternative in the design space of compartmentalization solutions on the desktop. FlexICon allows for the creation of a large number of containers with small memory footprint and low disk overhead. This is achieved by using lightweight virtualization based on Linux namespaces. FlexICon uses two mechanisms to reduce user mistakes: 1) a trusted file dialog for selecting files for opening and launching it in the appropriate containers, and 2) a secure URL redirection mechanism that detects the user’s intent and opens the URL in the proper container. FlexICon also provides a language to specify the access constraints that should be enforced by various containers.
The second solution called Auto-FBI, deals with web-based attacks by creating multiple instances of the browser and providing mechanisms for switching between the browser instances. The prototype implementation for Firefox and Chrome uses system call interposition to control the browser’s network access. Auto-FBI can be ported to other platforms easily due to simple design and the ubiquity of system call interposition methods on all major desktop platforms.
ContributorsZohrevandi, Mohsen (Author) / Bazzi, Rida A (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Doupe, Adam (Committee member) / Zhao, Ming (Committee member) / Arizona State University (Publisher)
Created2018
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 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.
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
Description
Software-Defined Networking (SDN) is an emerging network paradigm that decouples the control plane from the data plane, which allows network administrators to consolidate common network services into a centralized module named SDN controller. Applications’ policies are transformed into standardized network rules in the data plane via SDN controller. Even though this centralization brings a great flexibility and programmability to the network, network rules generated by SDN applications cannot be trusted because there may exist malicious SDN applications, and insecure network flows can be made due to complex relations across network rules. In this dissertation, I investigate how to identify and resolve these security violations in SDN caused by the combination of network rules and applications’ policies. To this end, I propose a systematic policy management framework that better protects SDN itself and hardens existing network defense mechanisms using SDN.
More specifically, I discuss the following four security challenges in this dissertation: (1) In SDN, generating reliable network rules is challenging because SDN applications cannot be trusted and have complicated dependencies each other. To address this problem, I analyze applications’ policies and remove those dependencies by applying grid-based policy decomposition mechanism; (2) One network rule could accidentally affect others (or by malicious users), which lead to creating of indirect security violations. I build systematic and automated tools that analyze network rules in the data plane to detect a wide range of security violations and resolve them in an automated fashion; (3) A fundamental limitation of current SDN protocol (OpenFlow) is a lack of statefulness, which is extremely important to several security applications such as stateful firewall. To bring statelessness to SDN-based environment, I come up with an innovative stateful monitoring scheme by extending existing OpenFlow specifications; (4) Existing honeynet architecture is suffering from its limited functionalities of ’data control’ and ’data capture’. To address this challenge, I design and implement an innovative next generation SDN-based honeynet architecture.
More specifically, I discuss the following four security challenges in this dissertation: (1) In SDN, generating reliable network rules is challenging because SDN applications cannot be trusted and have complicated dependencies each other. To address this problem, I analyze applications’ policies and remove those dependencies by applying grid-based policy decomposition mechanism; (2) One network rule could accidentally affect others (or by malicious users), which lead to creating of indirect security violations. I build systematic and automated tools that analyze network rules in the data plane to detect a wide range of security violations and resolve them in an automated fashion; (3) A fundamental limitation of current SDN protocol (OpenFlow) is a lack of statefulness, which is extremely important to several security applications such as stateful firewall. To bring statelessness to SDN-based environment, I come up with an innovative stateful monitoring scheme by extending existing OpenFlow specifications; (4) Existing honeynet architecture is suffering from its limited functionalities of ’data control’ and ’data capture’. To address this challenge, I design and implement an innovative next generation SDN-based honeynet architecture.
ContributorsHan, Wonkyu (Author) / Ahn, Gail-Joon (Thesis advisor) / Zhao, Ziming (Thesis advisor) / Doupe, Adam (Committee member) / Huang, Dijiang (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2016
Description
The ease of programmability in Software-Defined Networking (SDN) makes it a great platform for implementation of various initiatives that involve application deployment, dynamic topology changes, and decentralized network management in a multi-tenant data center environment. However, implementing security solutions in such an environment is fraught with policy conflicts and consistency issues with the hardness of this problem being affected by the distribution scheme for the SDN controllers.
In this dissertation, a formalism for flow rule conflicts in SDN environments is introduced. This formalism is realized in Brew, a security policy analysis framework implemented on an OpenDaylight SDN controller. Brew has comprehensive conflict detection and resolution modules to ensure that no two flow rules in a distributed SDN-based cloud environment have conflicts at any layer; thereby assuring consistent conflict-free security policy implementation and preventing information leakage. Techniques for global prioritization of flow rules in a decentralized environment are presented, using which all SDN flow rule conflicts are recognized and classified. Strategies for unassisted resolution of these conflicts are also detailed. Alternately, if administrator input is desired to resolve conflicts, a novel visualization scheme is implemented to help the administrators view the conflicts in an aesthetic manner. The correctness, feasibility and scalability of the Brew proof-of-concept prototype is demonstrated. Flow rule conflict avoidance using a buddy address space management technique is studied as an alternate to conflict detection and resolution in highly dynamic cloud systems attempting to implement an SDN-based Moving Target Defense (MTD) countermeasures.
In this dissertation, a formalism for flow rule conflicts in SDN environments is introduced. This formalism is realized in Brew, a security policy analysis framework implemented on an OpenDaylight SDN controller. Brew has comprehensive conflict detection and resolution modules to ensure that no two flow rules in a distributed SDN-based cloud environment have conflicts at any layer; thereby assuring consistent conflict-free security policy implementation and preventing information leakage. Techniques for global prioritization of flow rules in a decentralized environment are presented, using which all SDN flow rule conflicts are recognized and classified. Strategies for unassisted resolution of these conflicts are also detailed. Alternately, if administrator input is desired to resolve conflicts, a novel visualization scheme is implemented to help the administrators view the conflicts in an aesthetic manner. The correctness, feasibility and scalability of the Brew proof-of-concept prototype is demonstrated. Flow rule conflict avoidance using a buddy address space management technique is studied as an alternate to conflict detection and resolution in highly dynamic cloud systems attempting to implement an SDN-based Moving Target Defense (MTD) countermeasures.
ContributorsPisharody, Sandeep (Author) / Huang, Dijiang (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Syrotiuk, Violet (Committee member) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Created2017