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- All Subjects: Computer Science
- All Subjects: Materials Science
- Creators: Doupe, Adam
Description
The challenging search for clean, reliable and environmentally friendly energy sources has fueled increased research in thermoelectric materials, which are capable of recovering waste heat. Among the state-of-the-art thermoelectric materials β-Zn4Sb3 is outstanding because of its ultra-low glass-like thermal conductivity. Attempts to explore ternary phases in the Zn-Sb-In system resulted in the discovery of the new intermetallic compounds, stable Zn5Sb4In2-δ (δ=0.15) and metastable Zn9Sb6In2. Millimeter-sized crystals were grown from molten metal fluxes, where indium metal was employed as a reactive flux medium.Zn5Sb4In2-δ and Zn9Sb6In2 crystallize in new structure types featuring complex framework and the presence of structural disorder (defects and split atomic positions). The structure and phase relations between ternary Zn5Sb4In2-δ, Zn9Sb6In2 and binary Zn4Sb3 are discussed. To establish and understand structure-property relationships, thermoelectric properties measurements were carried out. The measurements suggested that Zn5Sb4In2-δ and Zn9Sb6In2 are narrow band gap semiconductors, similar to β-Zn4Sb3. Also, the peculiar low thermal conductivity of Zn4Sb3 (1 W/mK) is preserved. In the investigated temperature range 10 to 350 K Zn5Sb4In2-δ displays higher thermoelectric figure of merits than Zn4Sb3, indicating a potential significance in thermoelectric applications. Finally, the glass-like thermal conductivities of binary and ternary antimonides with complex structures are compared and the mechanism behind their low thermal conductivities is briefly discussed.
ContributorsWu, Yang (Author) / Häussermann, Ulrich (Thesis advisor) / Seo, Dong (Committee member) / Petuskey, William T (Committee member) / Newman, Nathan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Metal hydride materials have been intensively studied for hydrogen storage applications. In addition to potential hydrogen economy applications, metal hydrides offer a wide variety of other interesting properties. For example, hydrogen-dominant materials, which are hydrides with the highest hydrogen content for a particular metal/semimetal composition, are predicted to display high-temperature superconductivity. On the other side of the spectrum are hydrides with small amounts of hydrogen (0.1 - 1 at.%) that are investigated as viable magnetic, thermoelectric or semiconducting materials. Research of metal hydride materials is generally important to gain fundamental understanding of metal-hydrogen interactions in materials. Hydrogenation of Zintl phases, which are defined as compounds between an active metal (alkali, alkaline earth, rare earth) and a p-block metal/semimetal, were attempted by a hot sintering method utilizing an autoclave loaded with gaseous hydrogen (< 9 MPa). Hydride formation competes with oxidative decomposition of a Zintl phase. The oxidative decomposition, which leads to a mixture of binary active metal hydride and p-block element, was observed for investigated aluminum (Al) and gallium (Ga) containing Zintl phases. However, a new phase Li2Al was discovered when Zintl phase precursors were synthesized. Using the single crystal x-ray diffraction (SCXRD), the Li2Al was found to crystallize in an orthorhombic unit cell (Cmcm) with the lattice parameters a = 4.6404(8) Å, b = 9.719(2) Å, and c = 4.4764(8) Å. Increased demand for materials with improved properties necessitates the exploration of alternative synthesis methods. Conventional metal hydride synthesis methods, like ball-milling and autoclave technique, are not responding to the demands of finding new materials. A viable alternative synthesis method is the application of high pressure for the preparation of hydrogen-dominant materials. Extreme pressures in the gigapascal ranges can open access to new metal hydrides with novel structures and properties, because of the drastically increased chemical potential of hydrogen. Pressures up to 10 GPa can be easily achieved using the multi-anvil (MA) hydrogenations while maintaining sufficient sample volume for structure and property characterization. Gigapascal MA hydrogenations using ammonia borane (BH3NH3) as an internal hydrogen source were employed in the search for new hydrogen-dominant materials. Ammonia borane has high gravimetric volume of hydrogen, and additionally the thermally activated decomposition at high pressures lead to a complete hydrogen release at reasonably low temperature. These properties make ammonia borane a desired hydrogen source material. The missing member Li2PtH6 of the series of A2PtH6 compounds (A = Na to Cs) was accessed by employing MA technique. As the known heavier analogs, the Li2PtH6 also crystallizes in a cubic K2PtCl6-type structure with a cell edge length of 6.7681(3) Å. Further gigapascal hydrogenations afforded the compounds K2SiH6 and Rb2SiH6 which are isostructural to Li2PtH6. The cubic K2SiH6 and Rb2SiH6 are built from unique hypervalent SiH62- entities with the lattice parameters of 7.8425(9) and 8.1572(4) Å, respectively. Spectroscopic analysis of hexasilicides confirmed the presence of hypervalent bonding. The Si-H stretching frequencies at 1550 cm-1 appeared considerably decreased in comparison with a normal-valent (2e2c) Si-H stretching frequencies in SiH4 at around 2200 cm-1. However, the observed stretching modes in hypervalent hexasilicides were in a reasonable agreement with Ph3SiH2- (1520 cm-1) where the hydrogen has the axial (3e4c bonded) position in the trigoal bipyramidal environment.
ContributorsPuhakainen, Kati (Author) / Häussermann, Ulrich (Thesis advisor) / Seo, Dong (Thesis advisor) / Kouvetakis, John (Committee member) / Wolf, George (Committee member) / Arizona State University (Publisher)
Created2013
Description
Carbon lacks an extended polyanionic chemistry which appears restricted to carbides with C4-, C22-, and C34- moieties. The most common dimeric anion of carbon atoms is C22- with a triple bond between the two carbon atoms. Compounds containing the dicarbide anion can be regarded as salts of acetylene C2H2 (ethyne) and hence are also called acetylides or ethynides. Inspired by the fact that molecular acetylene undergoes pressure induced polymerization to polyacetylene above 3.5 GPa, it is of particular interest to study the effect of pressure on the crystal structures of acetylides as well. In this work, pressure induced polymerization was attempted with two simple metal acetylides, Li2C2 and CaC2. Li2C2 and CaC2 have been synthesized by a direct reaction of the elements at 800ºC and 1200ºC, respectively. Initial high pressure investigations were performed inside Diamond anvil cell (DAC) at room temperature and in situ Raman spectroscopic measurement were carried out up to 30 GPa. Near 15 GPa, Li2C2 undergoes a transition into a high pressure acetylide phase and around 25 GPa this phase turns amorphous. CaC2 is polymorphic at ambient pressure. Monoclinic CaC2-II does not show stability at pressures above 1 GPa. Tetragonal CaC2-I is stable up to at least 12 GPa above which possibly a pressure-induced distortion occurs. At around 18 GPa, CaC2 turns amorphous. In a subsequent series of experiments both Li2C2 and CaC2 were compressed to 10 GPa in a multi anvil (MA) device and heated to temperatures between 300 and 1100oC for Li2C2, and 300°C to 900°C for CaC2. The recovered products were analyzed by PXRD and Raman spectroscopy. It has been observed that reactions at temperature higher than 900°C were very difficult to control and hitherto only short reaction times could be applied. For Li2C2, a new phase, free of starting material was found at 1100°C. Both the PXRD patterns and Raman spectra of products at 1100oC could not be matched to known forms of carbon or carbides. For CaC2 new reflections in PXRD were visible at 900ºC with the starting material phase.
ContributorsKonar, Sumit (Author) / Häussermann, Ulrich (Thesis advisor) / Seo, Dong (Thesis advisor) / Steimle, Timothy (Committee member) / Wolf, George (Committee member) / Arizona State University (Publisher)
Created2012
Description
The discovery of the superconductor MgB2 led to the increase of research activity for more compounds adopting the AlB2 structure type and containing superconductive properties. The prominent successor compounds were the silicide systems, AeAlSi (Ae=Sr, Ba, Ca). Presented here is an extension of this investigation to the germanides, SrAlGe and BaAlGe. The ternary structures were synthesized through arc-melting elemental stoichiometric mixtures and structurally characterized by x-ray powder diffraction. Both crystallize as the hexagonal SrPtSb structure type, a variant of the AlB2 structure type. The low temperature region was measured on a Vibrating Sample Magnetometer (VSM) and both present the onset of superconductivity below 7K. These compounds are susceptible to hydrogen absorption and the new polyanionic hydrides, SrAlGeH and BaAlGeH, structural and dynamic properties are presented. The hydrides were synthesized via two distinct methods. One method is the reaction of SrH2 (BaH2) with elemental mixture of the Al and Ge under pressurized hydrogen and the other is a hydrogenation of the SrAlGe and BaAlGe. Both crystallize in the trigonal SrAlSiH structure type, as determined from Rietveld analysis on powder neutron diffraction measurements. The hydrogen is coordinated by both the active metal and aluminum atoms, providing a unique environment for studying metal-hydrogen interactions. When exposed to air, both the hydrides and alloys transform from a crystalline grey to an amorphous yellow powder accompanied by a dramatic volume increase. Infrared spectroscopy shows the disappearance of the bands associated with the Al-H bond and the appearance of Ge-H and O-H bands. This indicates the material reacts with atmospheric water.
ContributorsKranak, Verina Franika (Author) / Häussermann, Ulrich (Thesis advisor) / Seo, Dong Kyun (Committee member) / Kouvetakis, John (Committee member) / Arizona State University (Publisher)
Created2011
Description
Honeypots – cyber deception technique used to lure attackers into a trap. They contain fake confidential information to make an attacker believe that their attack has been successful. One of the prerequisites for a honeypot to be effective is that it needs to be undetectable. Deploying sniffing and event logging tools alongside the honeypot also helps understand the mindset of the attacker after successful attacks. Is there any data that backs up the claim that honeypots are effective in real life scenarios? The answer is no.Game-theoretic models have been helpful to approximate attacker and defender actions in cyber security. However, in the past these models have relied on expert- created data. The goal of this research project is to determine the effectiveness of honeypots using real-world data. So, how to deploy effective honeypots? This is where honey-patches come into play. Honey-patches are software patches designed to hinder the attacker’s ability to determine whether an attack has been successful or not. When an attacker launches a successful attack on a software, the honey-patch transparently redirects the attacker into a honeypot. The honeypot contains fake information which makes the attacker believe they were successful while in reality they were not.
After conducting a series of experiments and analyzing the results, there is a clear indication that honey-patches are not the perfect application security solution having both pros and cons.
ContributorsChauhan, Purv Rakeshkumar (Author) / Doupe, Adam (Thesis advisor) / Bao, Youzhi (Committee member) / Wang, Ruoyu (Committee member) / Arizona State University (Publisher)
Created2022
Description
Human civilization within the last two decades has largely transformed into an online one, with many of its associated activities taking place on computers and complex networked systems -- their analog and real-world equivalents having been rendered obsolete.These activities run the gamut from the ordinary and mundane, like ordering food, to complex and large-scale, such as those involving critical infrastructure or global trade and communications.
Unfortunately, the activities of human civilization also involve criminal, adversarial, and malicious ones with the result that they also now have their digital equivalents.
Ransomware, malware, and targeted cyberattacks are a fact of life today and are instigated not only by organized criminal gangs, but adversarial nation-states and organizations as well.
Needless to say, such actions result in disastrous and harmful real-world consequences. As the complexity and variety of software has evolved, so too has the ingenuity of attacks that exploit them; for example modern cyberattacks typically involve sequential exploitation of multiple software vulnerabilities.Compared to a decade ago, modern software stacks on personal computers, laptops, servers, mobile phones, and even Internet of Things (IoT) devices involve a dizzying array of interdependent programs and software libraries, with each of these components presenting attractive attack-surfaces for adversarial actors.
However, the responses to this still rely on paradigms that can neither react quickly enough nor scale to increasingly dynamic, ever-changing, and complex software environments.
Better approaches are therefore needed, that can assess system readiness and vulnerabilities, identify potential attack vectors and strategies (including ways to counter them), and proactively detect vulnerabilities in complex software before they can be exploited. In this dissertation, I first present a mathematical model and associated algorithms to identify attacker strategies for sequential cyberattacks based on attacker state, attributes and publicly-available vulnerability information.Second, I extend the model and design algorithms to help identify defensive courses of action against attacker strategies.
Finally, I present my work to enhance the ability of coverage-based fuzzers to identify software vulnerabilities by providing visibility into complex, internal program-states.
ContributorsPaliath, Vivin Suresh (Author) / Doupe, Adam (Thesis advisor) / Shoshitaishvili, Yan (Thesis advisor) / Wang, Ruoyu (Committee member) / Shakarian, Paulo (Committee member) / Arizona State University (Publisher)
Created2023
Description
The rise in popularity of applications and services that charge for access to proprietary trained models has led to increased interest in the robustness of these models and the security of the environments in which inference is conducted. State-of-the-art attacks extract models and generate adversarial examples by inferring relationships between a model’s input and output. Popular variants of these attacks have been shown to be deterred by countermeasures that poison predicted class distributions and mask class boundary gradients. Neural networks are also vulnerable to timing side-channel attacks. This work builds on top of Subneural, an attack framework that uses floating point timing side channels to extract neural structures. Novel applications of addition timing side channels are introduced, allowing the signs and arrangements of leaked parameters to be discerned more efficiently. Addition timing is also used to leak network biases, making the framework applicable to a wider range of targets. The enhanced framework is shown to be effective against models protected by prediction poisoning and gradient masking adversarial countermeasures and to be competitive with adaptive black box adversarial attacks against stateful defenses. Mitigations necessary to protect against floating-point timing side-channel attacks are also presented.
ContributorsVipat, Gaurav (Author) / Shoshitaishvili, Yan (Thesis advisor) / Doupe, Adam (Committee member) / Srivastava, Siddharth (Committee member) / Arizona State University (Publisher)
Created2023
Description
This thesis presents a study on the fuzzing of Linux binaries to find occluded bugs. Fuzzing is a widely-used technique for identifying software bugs. Despite their effectiveness, state-of-the-art fuzzers suffer from limitations in efficiency and effectiveness. Fuzzers based on random mutations are fast but struggle to generate high-quality inputs. In contrast, fuzzers based on symbolic execution produce quality inputs but lack execution speed. This paper proposes FlakJack, a novel hybrid fuzzer that patches the binary on the go to detect occluded bugs guarded by surface bugs. To dynamically overcome the challenge of patching binaries, the paper introduces multiple patching strategies based on the type of bug detected. The performance of FlakJack was evaluated on ten widely-used real-world binaries and one chaff dataset binary. The results indicate that many bugs found recently were already present in previous versions but were occluded by surface bugs. FlakJack’s approach improved the bug-finding ability by patching surface bugs that usually guard occluded bugs, significantly reducing patching cycles. Despite its unbalanced approach compared to other coverage-guided fuzzers, FlakJack is fast, lightweight, and robust. False- Positives can be filtered out quickly, and the approach is practical in other parts of the target. The paper shows that the FlakJack approach can significantly improve fuzzing performance without relying on complex strategies.
ContributorsPraveen Menon, Gokulkrishna (Author) / Bao, Tiffany (Thesis advisor) / Shoshitaishvili, Yan (Thesis advisor) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Created2023
Description
Reverse engineering is a process focused on gaining an understanding for the intricaciesof a system. This practice is critical in cybersecurity as it promotes the
findings and patching of vulnerabilities as well as the counteracting of malware. Disassemblers
and decompilers have become essential when reverse engineering due to
the readability of information they transcribe from binary files. However, these tools
still tend to produce involved and complicated outputs that hinder the acquisition of
knowledge during binary analysis. Cognitive Load Theory (CLT) explains that this
hindrance is due to the human brain’s inability to process superfluous amounts of
data. CLT classifies this data into three cognitive load types — intrinsic, extraneous,
and germane — that each can help gauge complex procedures.
In this research paper, a novel program call graph is presented accounting for
these CLT principles. The goal of this graphical view is to reduce the cognitive load
tied to the depiction of binary information and to enhance the overall binary analysis
process. This feature was implemented within the binary analysis tool, angr and it’s
user interface counterpart, angr-management. Additionally, this paper will examine a
conducted user study to quantitatively and qualitatively evaluate the effectiveness of
the newly proposed proximity view (PV). The user study includes a binary challenge
solving portion measured by defined metrics and a survey phase to receive direct participant
feedback regarding the view. The results from this study show statistically
significant evidence that PV aids in challenge solving and improves the overall understanding
binaries. The results also signify that this improvement comes with the
cost of time. The survey section of the user study further indicates that users find
PV beneficial to the reverse engineering process, but additional information needs to
be included in future developments.
ContributorsSmits, Sean (Author) / Wang, Ruoyu (Thesis advisor) / Shoshitaishvili, Yan (Thesis advisor) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Created2022
Description
Binary analysis and software debugging are critical tools in the modern softwaresecurity ecosystem. With the security arms race between attackers discovering and
exploiting vulnerabilities and the development teams patching bugs ever-tightening,
there is an immense need for more tooling to streamline the binary analysis and
debugging processes. Whether attempting to find the root cause for a buffer overflow
or a segmentation fault, the analysis process often involves manually tracing the
movement of data throughout a program’s life cycle. Up until this point, there has
not been a viable solution to the human limitation of maintaining a cohesive mental
image of the intricacies of a program’s data flow.
This thesis proposes a novel data dependency graph (DDG) analysis as an addi-
tion to angr’s analyses suite. This new analysis ingests a symbolic execution trace
in order to generate a directed acyclic graph of the program’s data dependencies. In
addition to the development of the backend logic needed to generate this graph, an
angr management view to visualize the DDG was implemented. This user interface
provides functionality for ancestor and descendant dependency tracing and sub-graph
creation. To evaluate the analysis, a user study was conducted to measure the view’s
efficacy in regards to binary analysis and software debugging. The study consisted
of a control group and experimental group attempting to solve a series of 3 chal-
lenges and subsequently providing feedback concerning perceived functionality and
comprehensibility pertaining to the view.
The results show that the view had a positive trend in relation to challenge-solving
accuracy in its target domain, as participants solved 32% more challenges 21% faster
when using the analysis than when using vanilla angr management.
ContributorsCapuano, Bailey Kellen (Author) / Shoshitaishvili, Yan (Thesis advisor) / Wang, Ruoyu (Thesis advisor) / Doupe, Adam (Committee member) / Arizona State University (Publisher)
Created2022