Matching Items (29)
Filtering by
- All Subjects: robotics
- All Subjects: Security
- Creators: Computer Science and Engineering Program
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Description
Many researchers aspire to create robotics systems that assist humans in common office tasks, especially by taking over delivery and messaging tasks. For meaningful interactions to take place, a mobile robot must be able to identify the humans it interacts with and communicate successfully with them. It must also be able to successfully navigate the office environment. While mobile robots are well suited for navigating and interacting with elements inside a deterministic office environment, attempting to interact with human beings in an office environment remains a challenge due to the limits on the amount of cost-efficient compute power onboard the robot. In this work, I propose the use of remote cloud services to offload intensive interaction tasks. I detail the interactions required in an office environment and discuss the challenges faced when implementing a human-robot interaction platform in a stochastic office environment. I also experiment with cloud services for facial recognition, speech recognition, and environment navigation and discuss my results. As part of my thesis, I have implemented a human-robot interaction system utilizing cloud APIs into a mobile robot, enabling it to navigate the office environment, identify humans within the environment, and communicate with these humans.
ContributorsDSouza, Daniel Anand (Author) / Kambhampati, Subbarao (Thesis director) / Zhang, Yu (Committee member) / Computer Science and Engineering Program (Contributor) / School of Computing, Informatics, and Decision Systems Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Preventive maintenance is a practice that has become popular in recent years, largely due to the increased dependency on electronics and other mechanical systems in modern technologies. The main idea of preventive maintenance is to take care of maintenance-type issues before they fully appear or cause disruption of processes and daily operations. One of the most important parts is being able to predict and foreshadow failures in the system, in order to make sure that those are fixed before they turn into large issues. One specific area where preventive maintenance is a very big part of daily activity is the automotive industry. Automobile owners are encouraged to take their cars in for maintenance on a routine schedule (based on mileage or time), or when their car signals that there is an issue (low oil levels for example). Although this level of maintenance is enough when people are in charge of cars, the rise of autonomous vehicles, specifically self-driving cars, changes that. Now instead of a human being able to look at a car and diagnose any issues, the car needs to be able to do this itself. The objective of this project was to create such a system. The Electronics Preventive Maintenance System is an internal system that is designed to meet all these criteria and more. The EPMS system is comprised of a central computer which monitors all major electronic components in an autonomous vehicle through the use of standard off-the-shelf sensors. The central computer compiles the sensor data, and is able to sort and analyze the readings. The filtered data is run through several mathematical models, each of which diagnoses issues in different parts of the vehicle. The data for each component in the vehicle is compared to pre-set operating conditions. These operating conditions are set in order to encompass all normal ranges of output. If the sensor data is outside the margins, the warning and deviation are recorded and a severity level is calculated. In addition to the individual focus, there's also a vehicle-wide model, which predicts how necessary maintenance is for the vehicle. All of these results are analyzed by a simple heuristic algorithm and a decision is made for the vehicle's health status, which is sent out to the Fleet Management System. This system allows for accurate, effortless monitoring of all parts of an autonomous vehicle as well as predictive modeling that allows the system to determine maintenance needs. With this system, human inspectors are no longer necessary for a fleet of autonomous vehicles. Instead, the Fleet Management System is able to oversee inspections, and the system operator is able to set parameters to decide when to send cars for maintenance. All the models used for the sensor and component analysis are tailored specifically to the vehicle. The models and operating margins are created using empirical data collected during normal testing operations. The system is modular and can be used in a variety of different vehicle platforms, including underwater autonomous vehicles and aerial vehicles.
ContributorsMian, Sami T. (Author) / Collofello, James (Thesis director) / Chen, Yinong (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Technical innovation has always played a part in live theatre, whether in the form of mechanical pieces like lifts and trapdoors to the more recent integration of digital media. The advances of the art form encourage the development of technology, and at the same time, technological development enables the advancement of theatrical expression. As mechanics, lighting, sound, and visual media have made their way into the spotlight, advances in theatrical robotics continue to push for their inclusion in the director's toolbox. However, much of the technology available is gated by high prices and unintuitive interfaces, designed for large troupes and specialized engineers, making it difficult to access for small schools and students new to the medium. As a group of engineering students with a vested interest in the development of the arts, this thesis team designed a system that will enable troupes from any background to participate in the advent of affordable automation. The intended result of this thesis project was to create a robotic platform that interfaces with custom software, receiving commands and transmitting position data, and to design that software so that a user can define intuitive cues for their shows. In addition, a new pathfinding algorithm was developed to support free-roaming automation in a 2D space. The final product consisted of a relatively inexpensive (< $2000) free-roaming platform, made entirely with COTS and standard materials, and a corresponding control system with cue design, wireless path following, and position tracking. This platform was built to support 1000 lbs, and includes integrated emergency stopping. The software allows for custom cue design, speed variation, and dynamic path following. Both the blueprints and the source code for the platform and control system have been released to open-source repositories, to encourage further development in the area of affordable automation. The platform itself was donated to the ASU School of Theater.
ContributorsHollenbeck, Matthew D. (Co-author) / Wiebel, Griffin (Co-author) / Winnemann, Christopher (Thesis director) / Christensen, Stephen (Committee member) / Computer Science and Engineering Program (Contributor) / School of Film, Dance and Theatre (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Modern computer processors contain an embedded firmware known as microcode that controls decode and execution of x86 instructions. Although proprietary and relatively obscure, this microcode can be modified using updates released by hardware manufacturers to correct processor logic flaws (errata). At the same time, a malicious microcode update could compromise a processor by implementing new malicious instructions or altering the functionality of existing instructions, including processor-accelerated virtualization or cryptographic primitives. Not only is this attack vector capable of subverting all software-enforced security policies and access controls, but it also leaves behind no postmortem forensic evidence since the write-only patch memory is cleared upon system reset. Although supervisor privileges (ring zero) are required to update processor microcode, this attack cannot be easily mitigated due to the implementation of microcode update functionality within processor silicon. In this paper, we reveal the microarchitecture and mechanism of microcode updates, present a security analysis of this attack vector, and provide some mitigation suggestions.
ContributorsChen, Daming Dominic (Author) / Ahn, Gail-Joon (Thesis director) / Lee, Joohyung (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of International Letters and Cultures (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2014-05
Description
We discuss processes involved in user-centric security design, including the synthesis of goals based on security and usability tasks. We suggest the usage of implicit security and the facilitation of secureuser actions. We propose a process for evaluating usability flaws by treating them as security threats and adapting traditional HCI methods. We discuss how to correct these flaws once they are discovered. Finally, we discuss the Usable Security Development Model for developing usable secure systems.
ContributorsJorgensen, Jan Drake (Author) / Ahn, Gail-Joon (Thesis director) / VanLehn, Kurt (Committee member) / Wilkerson, Kelly (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05
Description
Radio Frequency Identification (RFID) technology allows objects to be identified electronically by way of a small electronic tag. RFID is quickly becoming quite popular, and there are many security hurdles for this technology to overcome. The iCLASS line of RFID, produced by HID Global, is one such technology that is widely used for secure access control and applications where a contactless authentication element is desirable. Unfortunately, iCLASS has been shown to have security issues. Nevertheless customers continue to use it because of the great cost that would be required to completely replace it. This Honors Thesis will address attacks against iCLASS and means for countering them that do not require such an overhaul.
ContributorsMellott, Matthew John (Author) / Ahn, Gail-Joon (Thesis director) / Thorstenson, Tina (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2014-05
Description
IoT Media broadcast devices, such as the Roku stick, Amazon Fire, and Chromecast have been emerging onto the market recently as a portable and inexpensive alternative to cable and disk players, allowing easy integration between home and business Wi-Fi networks and television systems capable of supporting HDMI inputs without the additional overhead of setting up a heavy or complicated player or computer. The rapid expansion of these products as a mechanism to provide for TV Everywhere services for entertainment as well as cheap office appliances brings yet another node in the rapidly expanding network of IoT that surrounds us today. However, the security implications of these devices are nearly unexplored, despite their prevalence. In this thesis, I will go over the structure and mechanisms of Chromecast, and explore some of the potential exploits and consequences of the device. The thesis contains an overview of the inner workings of Chromecast, goes over the segregation and limited control and fundamental design choices of the Android based OS. It then identifies the objectives of security, four different potential methods of exploit to compromise those objectives on a Chromecast and/or its attached network, including rogue applications, traffic sniffing, evil access points and the most effective one: deauthentication attack. Tests or relevant analysis were carried out for each of these methods, and conclusions were drawn on their effectiveness. There is then a conclusion revolving around the consequences, mitigation and the future implications of security issues on Chromecast and the larger IoT landscape.
ContributorsHuang, Kaiyi (Author) / Zhao, Ziming (Thesis director) / Ahn, Gail-Joon (Committee member) / W. P. Carey School of Business (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
In order to adequately introduce students to computer science and robotics in an exciting and engaging manner certain teaching techniques should be used. In recent years some of the most popular paradigms are Visual Programming Languages. Visual Programming Languages are meant to introduce problem solving skills and basic programming constructs inherent to all modern day languages by allowing users to write programs visually as opposed to textually. By bypassing the need to learn syntax students can focus on the thinking behind developing an algorithm and see immediate results that help generate excitement for the field and reduce disinterest due to startup complexity and burnout. The Introduction to Engineering course at Arizona State University supports this approach by teaching students the basics of autonomous maze traversing algorithms and using ASU VIPLE, a Visual Programming Language developed to connect with and direct real-world robots. However, some startup time is needed to learn how to interface with these robots using ASU VIPLE. That is why the HTML5 Autonomous Robot Web Simulator was created -- by encouraging students to use the simulator the problem solving behind autonomous maze traversing algorithms can be introduced more quickly and with immediate affirmation. Our goal was to improve this simulator and add features so that the simulator could be accessed and used for a more wide variety of introductory Computer Science lessons. Features scattered across past implementations of robotic simulators were aggregated in a cross platform solution. Upon initial development, a classroom test group revealed usability concerns and a demonstration of students' mental models. Mean time for task completion was 8.1min - compared to 2min for the authors. The simulator was updated in response to test group feedback and new instructor requirements. The new implementation reduces programming overhead while maintaining a learning environment with support for even the most complex applications.
ContributorsRodewald, Spencer (Co-author, Co-author) / Patel, Ankit (Co-author) / Chen, Yinong (Thesis director) / Chattin, Linda (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Classical planning is a field of Artificial Intelligence concerned with allowing autonomous agents to make reasonable decisions in complex environments. This work investigates
the application of deep learning and planning techniques, with the aim of constructing generalized plans capable of solving multiple problem instances. We construct a Deep Neural Network that, given an abstract problem state, predicts both (i) the best action to be taken from that state and (ii) the generalized “role” of the object being manipulated. The neural network was tested on two classical planning domains: the blocks world domain and the logistic domain. Results indicate that neural networks are capable of making such
predictions with high accuracy, indicating a promising new framework for approaching generalized planning problems.
the application of deep learning and planning techniques, with the aim of constructing generalized plans capable of solving multiple problem instances. We construct a Deep Neural Network that, given an abstract problem state, predicts both (i) the best action to be taken from that state and (ii) the generalized “role” of the object being manipulated. The neural network was tested on two classical planning domains: the blocks world domain and the logistic domain. Results indicate that neural networks are capable of making such
predictions with high accuracy, indicating a promising new framework for approaching generalized planning problems.
ContributorsNakhleh, Julia Blair (Author) / Srivastava, Siddharth (Thesis director) / Fainekos, Georgios (Committee member) / Computer Science and Engineering Program (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Third-party mixers are used to heighten the anonymity of Bitcoin users. The mixing techniques implemented by these tools are often untraceable on the blockchain, making them appealing to money launderers. This research aims to analyze mixers currently available on the deep web. In addition, an in-depth case study is done on an open-source bitcoin mixer known as Penguin Mixer. A local version of Penguin Mixer was used to visualize mixer behavior under specific scenarios. This study could lead to the identification of vulnerabilities in mixing tools and detection of these tools on the blockchain.
ContributorsPakki, Jaswant (Author) / Doupe, Adam (Thesis director) / Shoshitaishvili, Yan (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2018-12