ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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Description
Cyber-systems and networks are the target of different types of cyber-threats and attacks, which are becoming more common, sophisticated, and damaging. Those attacks can vary in the way they are performed. However, there are similar strategies
and tactics often used because they are time-proven to be effective. The motivations behind cyber-attacks play an important role in designating how attackers plan and proceed to achieve their goals. Generally, there are three categories of motivation
are: political, economical, and socio-cultural motivations. These indicate that to defend against possible attacks in an enterprise environment, it is necessary to consider what makes such an enterprise environment a target. That said, we can understand
what threats to consider and how to deploy the right defense system. In other words, detecting an attack depends on the defenders having a clear understanding of why they become targets and what possible attacks they should expect. For instance,
attackers may preform Denial of Service (DoS), or even worse Distributed Denial of Service (DDoS), with intention to cause damage to targeted organizations and prevent legitimate users from accessing their services. However, in some cases, attackers are very skilled and try to hide in a system undetected for a long period of time with the incentive to steal and collect data rather than causing damages.
Nowadays, not only the variety of attack types and the way they are launched are important. However, advancement in technology is another factor to consider. Over the last decades, we have experienced various new technologies. Obviously, in the beginning, new technologies will have their own limitations before they stand out. There are a number of related technical areas whose understanding is still less than satisfactory, and in which long-term research is needed. On the other hand, these new technologies can boost the advancement of deploying security solutions and countermeasures when they are carefully adapted. That said, Software Defined Networking i(SDN), its related security threats and solutions, and its adaption in enterprise environments bring us new chances to enhance our security solutions. To reach the optimal level of deploying SDN technology in enterprise environments, it is important to consider re-evaluating current deployed security solutions in traditional networks before deploying them to SDN-based infrastructures. Although DDoS attacks are a bit sinister, there are other types of cyber-threats that are very harmful, sophisticated, and intelligent. Thus, current security defense solutions to detect DDoS cannot detect them. These kinds of attacks are complex, persistent, and stealthy, also referred to Advanced Persistent Threats (APTs) which often leverage the bot control and remotely access valuable information. APT uses multiple stages to break into a network. APT is a sort of unseen, continuous and long-term penetrative network and attackers can bypass the existing security detection systems. It can modify and steal the sensitive data as well as specifically cause physical damage the target system. In this dissertation, two cyber-attack motivations are considered: sabotage, where the motive is the destruction; and information theft, where attackers aim to acquire invaluable information (customer info, business information, etc). I deal with two types of attacks (DDoS attacks and APT attacks) where DDoS attacks are classified under sabotage motivation category, and the APT attacks are classified under information theft motivation category. To detect and mitigate each of these attacks, I utilize the ease of programmability in SDN and its great platform for implementation, dynamic topology changes, decentralized network management, and ease of deploying security countermeasures.
and tactics often used because they are time-proven to be effective. The motivations behind cyber-attacks play an important role in designating how attackers plan and proceed to achieve their goals. Generally, there are three categories of motivation
are: political, economical, and socio-cultural motivations. These indicate that to defend against possible attacks in an enterprise environment, it is necessary to consider what makes such an enterprise environment a target. That said, we can understand
what threats to consider and how to deploy the right defense system. In other words, detecting an attack depends on the defenders having a clear understanding of why they become targets and what possible attacks they should expect. For instance,
attackers may preform Denial of Service (DoS), or even worse Distributed Denial of Service (DDoS), with intention to cause damage to targeted organizations and prevent legitimate users from accessing their services. However, in some cases, attackers are very skilled and try to hide in a system undetected for a long period of time with the incentive to steal and collect data rather than causing damages.
Nowadays, not only the variety of attack types and the way they are launched are important. However, advancement in technology is another factor to consider. Over the last decades, we have experienced various new technologies. Obviously, in the beginning, new technologies will have their own limitations before they stand out. There are a number of related technical areas whose understanding is still less than satisfactory, and in which long-term research is needed. On the other hand, these new technologies can boost the advancement of deploying security solutions and countermeasures when they are carefully adapted. That said, Software Defined Networking i(SDN), its related security threats and solutions, and its adaption in enterprise environments bring us new chances to enhance our security solutions. To reach the optimal level of deploying SDN technology in enterprise environments, it is important to consider re-evaluating current deployed security solutions in traditional networks before deploying them to SDN-based infrastructures. Although DDoS attacks are a bit sinister, there are other types of cyber-threats that are very harmful, sophisticated, and intelligent. Thus, current security defense solutions to detect DDoS cannot detect them. These kinds of attacks are complex, persistent, and stealthy, also referred to Advanced Persistent Threats (APTs) which often leverage the bot control and remotely access valuable information. APT uses multiple stages to break into a network. APT is a sort of unseen, continuous and long-term penetrative network and attackers can bypass the existing security detection systems. It can modify and steal the sensitive data as well as specifically cause physical damage the target system. In this dissertation, two cyber-attack motivations are considered: sabotage, where the motive is the destruction; and information theft, where attackers aim to acquire invaluable information (customer info, business information, etc). I deal with two types of attacks (DDoS attacks and APT attacks) where DDoS attacks are classified under sabotage motivation category, and the APT attacks are classified under information theft motivation category. To detect and mitigate each of these attacks, I utilize the ease of programmability in SDN and its great platform for implementation, dynamic topology changes, decentralized network management, and ease of deploying security countermeasures.
ContributorsAlshamrani, Adel (Author) / Huang, Dijiang (Thesis advisor) / Doupe, Adam (Committee member) / Ahn, Gail-Joon (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2018
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
A firewall is a necessary component for network security and just like any regular equipment it requires maintenance. To keep up with changing cyber security trends and threats, firewall rules are modified frequently. Over time such modifications increase the complexity, size and verbosity of firewall rules. As the rule set grows in size, adding and modifying rule becomes a tedious task. This discourages network administrators to review the work done by previous administrators before and after applying any changes. As a result the quality and efficiency of the firewall goes down.
Modification and addition of rules without knowledge of previous rules creates anomalies like shadowing and rule redundancy. Anomalous rule sets not only limit the efficiency of the firewall but in some cases create a hole in the perimeter security. Detection of anomalies has been studied for a long time and some well established procedures have been implemented and tested. But they all have a common problem of visualizing the results. When it comes to visualization of firewall anomalies, the results do not fit in traditional matrix, tree or sunburst representations.
This research targets the anomaly detection and visualization problem. It analyzes and represents firewall rule anomalies in innovative ways such as hive plots and dynamic slices. Such graphical representations of rule anomalies are useful in understanding the state of a firewall. It also helps network administrators in finding and fixing the anomalous rules.
Modification and addition of rules without knowledge of previous rules creates anomalies like shadowing and rule redundancy. Anomalous rule sets not only limit the efficiency of the firewall but in some cases create a hole in the perimeter security. Detection of anomalies has been studied for a long time and some well established procedures have been implemented and tested. But they all have a common problem of visualizing the results. When it comes to visualization of firewall anomalies, the results do not fit in traditional matrix, tree or sunburst representations.
This research targets the anomaly detection and visualization problem. It analyzes and represents firewall rule anomalies in innovative ways such as hive plots and dynamic slices. Such graphical representations of rule anomalies are useful in understanding the state of a firewall. It also helps network administrators in finding and fixing the anomalous rules.
ContributorsKhatkar, Pankaj Kumar (Author) / Huang, Dijiang (Thesis advisor) / Ahn, Gail-Joon (Committee member) / Syrotiuk, Violet R. (Committee member) / Arizona State University (Publisher)
Created2014