Matching Items (61)
Filtering by
- Genre: Masters Thesis
- Member of: ASU Electronic Theses and Dissertations
Description
On Android, existing security procedures require apps to request permissions for access to sensitive resources.
Only when the user approves the requested permissions will the app be installed.
However, permissions are an incomplete security mechanism.
In addition to a user's limited understanding of permissions, the mechanism does not account for the possibility that different permissions used together have the ability to be more dangerous than any single permission alone.
Even if users did understand the nature of an app's requested permissions, this mechanism is still not enough to guarantee that a user's information is protected.
Applications can potentially send or receive sensitive information from other applications without the required permissions by using intents.
In other words, applications can potentially collaborate in ways unforeseen by the user, even if the user understands the permissions of each app independently.
In this thesis, we present several graph-based approaches to address these issues.
We determine the permissions of an app and generate scores based on our assigned value of certain resources.
We analyze these scores overall, as well as in the context of the app's category as determined by Google Play.
We show that these scores can be used to identify overzealous apps, as well as apps that do not properly fit within their category.
We analyze potential interactions between different applications using intents, and identify several promiscuous apps with low permission scores, showing that permissions alone are not sufficient to evaluate the security risks of an app.
Our analyses can form the basis of a system to assist users in identifying apps that can potentially compromise user privacy.
Only when the user approves the requested permissions will the app be installed.
However, permissions are an incomplete security mechanism.
In addition to a user's limited understanding of permissions, the mechanism does not account for the possibility that different permissions used together have the ability to be more dangerous than any single permission alone.
Even if users did understand the nature of an app's requested permissions, this mechanism is still not enough to guarantee that a user's information is protected.
Applications can potentially send or receive sensitive information from other applications without the required permissions by using intents.
In other words, applications can potentially collaborate in ways unforeseen by the user, even if the user understands the permissions of each app independently.
In this thesis, we present several graph-based approaches to address these issues.
We determine the permissions of an app and generate scores based on our assigned value of certain resources.
We analyze these scores overall, as well as in the context of the app's category as determined by Google Play.
We show that these scores can be used to identify overzealous apps, as well as apps that do not properly fit within their category.
We analyze potential interactions between different applications using intents, and identify several promiscuous apps with low permission scores, showing that permissions alone are not sufficient to evaluate the security risks of an app.
Our analyses can form the basis of a system to assist users in identifying apps that can potentially compromise user privacy.
ContributorsGibson, Aaron (Author) / Bazzi, Rida (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Walker, Erin (Committee member) / Arizona State University (Publisher)
Created2015
Description
Commercial load balancers are often in use, and the production network at Arizona State University (ASU) is no exception. However, because the load balancer uses IP addresses, the solution does not apply to all applications. One such application is Rsyslog. This software processes syslog packets and stores them in files. The loss rate of incoming log packets is high due to the incoming rate of the data. The Rsyslog servers are overwhelmed by the continuous data stream. To solve this problem a software defined networking (SDN) based load balancer is designed to perform a transport-level load balancing over the incoming load to Rsyslog servers. In this solution the load is forwarded to one Rsyslog server at a time, according to one of a Round-Robin, Random, or Load-Based policy. This gives time to other servers to process the data they have received and prevent them from being overwhelmed. The evaluation of the proposed solution is conducted a physical testbed with the same data feed as the commercial solution. The results suggest that the SDN-based load balancer is competitive with the commercial load balancer. Replacing the software OpenFlow switch with a hardware switch is likely to further improve the results.
ContributorsGhaffarinejad, Ashkan (Author) / Syrotiuk, Violet R. (Thesis advisor) / Xue, Guoliang (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2015
Description
The increasing usage of smart-phones and mobile devices in work environment and IT
industry has brought about unique set of challenges and opportunities. ARM architecture
in particular has evolved to a point where it supports implementations across wide spectrum
of performance points and ARM based tablets and smart-phones are in demand. The
enhancements to basic ARM RISC architecture allow ARM to have high performance,
small code size, low power consumption and small silicon area. Users want their devices to
perform many tasks such as read email, play games, and run other online applications and
organizations no longer desire to provision and maintain individual’s IT equipment. The
term BYOD (Bring Your Own Device) has come into being from demand of such a work
setup and is one of the motivation of this research work. It brings many opportunities such
as increased productivity and reduced costs and challenges such as secured data access,
data leakage and amount of control by the organization.
To provision such a framework we need to bridge the gap from both organizations side
and individuals point of view. Mobile device users face issue of application delivery on
multiple platforms. For instance having purchased many applications from one proprietary
application store, individuals may want to move them to a different platform/device but
currently this is not possible. Organizations face security issues in providing such a solution
as there are many potential threats from allowing BYOD work-style such as unauthorized
access to data, attacks from the devices within and outside the network.
ARM based Secure Mobile SDN framework will resolve these issues and enable employees
to consolidate both personal and business calls and mobile data access on a single device.
To address application delivery issue we are introducing KVM based virtualization that
will allow host OS to run multiple guest OS. To address the security problem we introduce
SDN environment where host would be running bridged network of guest OS using Open
vSwitch . This would allow a remote controller to monitor the state of guest OS for making
important control and traffic flow decisions based on the situation.
industry has brought about unique set of challenges and opportunities. ARM architecture
in particular has evolved to a point where it supports implementations across wide spectrum
of performance points and ARM based tablets and smart-phones are in demand. The
enhancements to basic ARM RISC architecture allow ARM to have high performance,
small code size, low power consumption and small silicon area. Users want their devices to
perform many tasks such as read email, play games, and run other online applications and
organizations no longer desire to provision and maintain individual’s IT equipment. The
term BYOD (Bring Your Own Device) has come into being from demand of such a work
setup and is one of the motivation of this research work. It brings many opportunities such
as increased productivity and reduced costs and challenges such as secured data access,
data leakage and amount of control by the organization.
To provision such a framework we need to bridge the gap from both organizations side
and individuals point of view. Mobile device users face issue of application delivery on
multiple platforms. For instance having purchased many applications from one proprietary
application store, individuals may want to move them to a different platform/device but
currently this is not possible. Organizations face security issues in providing such a solution
as there are many potential threats from allowing BYOD work-style such as unauthorized
access to data, attacks from the devices within and outside the network.
ARM based Secure Mobile SDN framework will resolve these issues and enable employees
to consolidate both personal and business calls and mobile data access on a single device.
To address application delivery issue we are introducing KVM based virtualization that
will allow host OS to run multiple guest OS. To address the security problem we introduce
SDN environment where host would be running bridged network of guest OS using Open
vSwitch . This would allow a remote controller to monitor the state of guest OS for making
important control and traffic flow decisions based on the situation.
ContributorsChowdhary, Ankur (Author) / Huang, Dijiang (Thesis advisor) / Tong, Hanghang (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2015
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
With the software-defined networking trend growing, several network virtualization controllers have been developed in recent years. These controllers, also called network hypervisors, attempt to manage physical SDN based networks so that multiple tenants can safely share the same forwarding plane hardware without risk of being affected by or affecting other tenants. However, many areas remain unexplored by current network hypervisor implementations. This thesis presents and evaluates some of the features offered by network hypervisors, such as full header space availability, isolation, and transparent traffic forwarding capabilities for tenants. Flow setup time and throughput are also measured and compared among different network hypervisors. Three different network hypervisors are evaluated: FlowVisor, VeRTIGO and OpenVirteX. These virtualization tools are assessed with experiments conducted on three different testbeds: an emulated Mininet scenario, a physical single-switch testbed, and also a remote GENI testbed. The results indicate that network hypervisors bring SDN flexibility to network virtualization, making it easier for network administrators to define with precision how the network is sliced and divided among tenants. This increased flexibility, however, may come with the cost of decreased performance, and also brings additional risks of interoperability due to a lack of standardization of virtualization methods.
ContributorsStall Rechia, Felipe (Author) / Syrotiuk, Violet R. (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2016
Description
Data protection has long been a point of contention and a vastly researched field. With the advent of technology and advances in Internet technologies, securing data has become much more challenging these days. Cloud services have become very popular. Given the ease of access and availability of the systems, it is not easy to not use cloud to store data. This however, pose a significant risk to data security as more of your data is available to a third party. Given the easy transmission and almost infinite storage of data, securing one's sensitive information has become a major challenge.
Cloud service providers may not be trusted completely with your data. It is not very uncommon to snoop over the data for finding interesting patterns to generate ad revenue or divulge your information to a third party, e.g. government and law enforcing agencies. For enterprises who use cloud service, it pose a risk for their intellectual property and business secrets. With more and more employees using cloud for their day to day work, business now face a risk of losing or leaking out information.
In this thesis, I have focused on ways to protect data and information over cloud- a third party not authorized to use your data, all this while still utilizing cloud services for transfer and availability of data. This research proposes an alternative to an on-premise secure infrastructure giving exibility to user for protecting the data and control over it. The project uses cryptography to protect data and create a secure architecture for secret key migration in order to decrypt the data securely for the intended recipient. It utilizes Intel's technology which gives it an added advantage over other existing solutions.
Cloud service providers may not be trusted completely with your data. It is not very uncommon to snoop over the data for finding interesting patterns to generate ad revenue or divulge your information to a third party, e.g. government and law enforcing agencies. For enterprises who use cloud service, it pose a risk for their intellectual property and business secrets. With more and more employees using cloud for their day to day work, business now face a risk of losing or leaking out information.
In this thesis, I have focused on ways to protect data and information over cloud- a third party not authorized to use your data, all this while still utilizing cloud services for transfer and availability of data. This research proposes an alternative to an on-premise secure infrastructure giving exibility to user for protecting the data and control over it. The project uses cryptography to protect data and create a secure architecture for secret key migration in order to decrypt the data securely for the intended recipient. It utilizes Intel's technology which gives it an added advantage over other existing solutions.
ContributorsSrivastava, Abhijeet (Author) / Ahn, Gail-Joon (Thesis advisor) / Zhao, Ziming (Committee member) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Created2016
Description
In traditional networks the control and data plane are highly coupled, hindering development. With Software Defined Networking (SDN), the two planes are separated, allowing innovations on either one independently of the other. Here, the control plane is formed by the applications that specify an organization's policy and the data plane contains the forwarding logic. The application sends all commands to an SDN controller which then performs the requested action on behalf of the application. Generally, the requested action is a modification to the flow tables, present in the switches, to reflect a change in the organization's policy. There are a number of ways to control the network using the SDN principles, but the most widely used approach is OpenFlow.
With the applications now having direct access to the flow table entries, it is easy to have inconsistencies arise in the flow table rules. Since the flow rules are structured similar to firewall rules, the research done in analyzing and identifying firewall rule conflicts can be adapted to work with OpenFlow rules.
The main work of this thesis is to implement flow conflict detection logic in OpenDaylight and inspect the applicability of techniques in visualizing the conflicts. A hierarchical edge-bundling technique coupled with a Reingold-Tilford tree is employed to present the relationship between the conflicting rules. Additionally, a table-driven approach is also implemented to display the details of each flow.
Both types of visualization are then tested for correctness by providing them with flows which are known to have conflicts. The conflicts were identified properly and displayed by the views.
With the applications now having direct access to the flow table entries, it is easy to have inconsistencies arise in the flow table rules. Since the flow rules are structured similar to firewall rules, the research done in analyzing and identifying firewall rule conflicts can be adapted to work with OpenFlow rules.
The main work of this thesis is to implement flow conflict detection logic in OpenDaylight and inspect the applicability of techniques in visualizing the conflicts. A hierarchical edge-bundling technique coupled with a Reingold-Tilford tree is employed to present the relationship between the conflicting rules. Additionally, a table-driven approach is also implemented to display the details of each flow.
Both types of visualization are then tested for correctness by providing them with flows which are known to have conflicts. The conflicts were identified properly and displayed by the views.
ContributorsNatarajan, Janakarajan (Author) / Huang, Dijiang (Thesis advisor) / Syrotiuk, Violet R. (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Arizona State University (Publisher)
Created2016
Description
The success of Bitcoin has generated significant interest in the financial community to understand whether the technological underpinnings of the cryptocurrency paradigm can be leveraged to improve the efficiency of financial processes in the existing infrastructure. Various alternative proposals, most notably, Ripple and Ethereum, aim to provide solutions to the financial community in different ways. These proposals derive their security guarantees from either the computational hardness of proof-of-work or voting based distributed consensus mechanism, both of which can be computationally expensive. Furthermore, the financial audit requirements for a participating financial institutions have not been suitably addressed.
This thesis presents a novel approach of constructing a non-consensus based decentralized financial transaction processing model with a built-in efficient audit structure. The problem of decentralized inter-bank payment processing is used for the model design. The two key insights used in this work are (1) to utilize a majority signature based replicated storage protocol for transaction authorization, and (2) to construct individual self-verifiable audit trails for each node as opposed to a common Blockchain. Theoretical analysis shows that the model provides cryptographic security for transaction processing and the presented audit structure facilitates financial auditing of individual nodes in time independent of the number of transactions.
This thesis presents a novel approach of constructing a non-consensus based decentralized financial transaction processing model with a built-in efficient audit structure. The problem of decentralized inter-bank payment processing is used for the model design. The two key insights used in this work are (1) to utilize a majority signature based replicated storage protocol for transaction authorization, and (2) to construct individual self-verifiable audit trails for each node as opposed to a common Blockchain. Theoretical analysis shows that the model provides cryptographic security for transaction processing and the presented audit structure facilitates financial auditing of individual nodes in time independent of the number of transactions.
ContributorsGupta, Saurabh (Author) / Bazzi, Rida (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Herlihy, Maurice (Committee member) / Arizona State University (Publisher)
Created2016
Description
Detecting cyber-attacks in cyber systems is essential for protecting cyber infrastructures from cyber-attacks. It is very difficult to detect cyber-attacks in cyber systems due to their high complexity. The accuracy of the attack detection in the cyber systems depends heavily on the completeness of the collected sensor information. In this thesis, two approaches are presented: one to detecting attacks in completely observable cyber systems, and the other to estimating types of states in partially observable cyber systems for attack detection in cyber systems. These two approaches are illustrated using three large data sets of network traffic because the packet-level information of the network traffic data provides details about the cyber systems.
The approach to attack detection in cyber systems is based on a multimodal artificial neural network (MANN) using the collected network traffic data from completely observable cyber systems for training and testing. Since the training of MANN is computationally intensive, to reduce the computational overhead, an efficient feature selection algorithm using the genetic algorithm is developed and incorporated in this approach.
In order to detect attacks in cyber systems in partially observable environments, an approach to estimating the types of states in partially observable cyber systems, which is the first phase of attack detection in cyber systems in partially observable environments, is presented. The types of states of such cyber systems are useful to detecting cyber-attacks in such cyber systems. This approach involves the use of a convolutional neural network (CNN), and unsupervised learning with elbow method and k-means clustering algorithm.
The approach to attack detection in cyber systems is based on a multimodal artificial neural network (MANN) using the collected network traffic data from completely observable cyber systems for training and testing. Since the training of MANN is computationally intensive, to reduce the computational overhead, an efficient feature selection algorithm using the genetic algorithm is developed and incorporated in this approach.
In order to detect attacks in cyber systems in partially observable environments, an approach to estimating the types of states in partially observable cyber systems, which is the first phase of attack detection in cyber systems in partially observable environments, is presented. The types of states of such cyber systems are useful to detecting cyber-attacks in such cyber systems. This approach involves the use of a convolutional neural network (CNN), and unsupervised learning with elbow method and k-means clustering algorithm.
ContributorsGuha, Sayantan (Author) / Yau, Stephen S. (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2016
Description
Passwords are ubiquitous and are poised to stay that way due to their relative usability, security and deployability when compared with alternative authentication schemes. Unfortunately, humans struggle with some of the assumptions or requirements that are necessary for truly strong passwords. As administrators try to push users towards password complexity and diversity, users still end up using predictable mangling patterns on old passwords and reusing the same passwords across services; users even inadvertently converge on the same patterns to a surprising degree, making an attacker’s job easier. This work explores using machine learning techniques to pick out strong passwords from weak ones, from a dataset of 10 million passwords, based on how structurally similar they were to the rest of the set.
ContributorsTodd, Margaret Nicole (Author) / Xue, Guoliang (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Huang, Dijiang (Committee member) / Arizona State University (Publisher)
Created2016