Chameleon Interference: Assessing Vulnerability of Magnetic Sensors to Spoofing and Signal injection attacks through Environmental interference in Mobile Devices
| dc.contributor.author | Gleason, David Theodore | en |
| dc.contributor.committeechair | Hicks, Matthew | en |
| dc.contributor.committeemember | Bowman, Douglas A. | en |
| dc.contributor.committeemember | Chung, Taejoong Tijay | en |
| dc.contributor.department | Computer Science and Applications | en |
| dc.date.accessioned | 2023-01-07T09:00:17Z | en |
| dc.date.available | 2023-01-07T09:00:17Z | en |
| dc.date.issued | 2023-01-06 | en |
| dc.description.abstract | Embedded sensors are a fixture of most devices in the current computer industry. These small devices are used for a variety of purposes throughout many fields to collect whatever kind of information is needed by the user. From data on device acceleration to data on position relative to the Earth's magnetic field, embedded sensors can provide it for any number of tasks. The advent of these devices has made work and research in the computer industry significantly easier but they are not without their drawbacks. Most of these sensors operate by drawing external data from the environment through send and receive signals. This mode of operation leaves them vulnerable to external malicious users who seek access to the data being stored and handled by the sensors. Concerns over security and privacy of embedded sensor data has become a topic of great concern with the continued digitization of sensitive personal data. Within the last five years, studies have shown the ability to manipulate embedded magnetic sensors in order to gain access to various forms of sensitive personal data. This is of great concern to the developers of mobile devices as most mobile devices possess embedded magnetic sensors. The vulnerability of sensors to external influence leads to concerns for both data privacy and degradation of public trust in the ability of their devices to keep their personal information safe and out of the wrong hands. Degradation of public trust in security methodologies is a major concern to many in the research and tech industry as much of the work conducted to advance both security and technology depends on large amounts of public data. If the public loses trust in the ability of the devices used by researchers to protect and ensure the safety of the data provided to them, then they may stop providing data which would then make the work of researchers and other tech workers considerably more difficult. To address these concerns, this thesis will present an introduction to Magnetic sensor devices (a prominent tool for data collection), how these sensors work and the ways they handle data. We shall then examine the techniques used to interfere with the functioning and output of magnetic sensors employed by mobile devices. Finally, we shall examine existing techniques for defending against these kinds of attacks as well as propose potential new techniques. The end goal of this work is to provide a broader perspective on the nature of environmental/natural interference and its relationship to scientific study and technological advancement. Literature around this topic does exist, however, all existing works currently in the literature focus exclusively on one form of interference i.e., light which leads to a smaller/narrower perspective which this work seeks to remedy. The end result is meant to give a broader perspective of multiple forms of interference and their interrelations between each other than is possible by current perspectives due to their narrow lens. | en |
| dc.description.abstractgeneral | Embedded sensors are small devices integrated into many mobile devices currently in the public market. These devices serve to collect environmental data of all kinds in order to perform a variety of functions. From directional calibration to magnetic orientation in relation to the magnetic north pole, sensors perform it all. This has led to a massive increase in computer power and quality of life for the general public but not without issue. The increase in storing personal/sensitive data to be processed by these devices has prompted a new breed of privacy concerns and problems to confront. In this thesis, we seek to show the influence and effects of five distinct types of interference rooted in the natural world on the functioning of magnetic sensor devices. Through the experiments conducted in this work, it was found that the interference forms of sound, temperature, and electromagnetism could induce a 32-36 percent average decrease in standard deviation in the data being processed by the sensor. Temperature shifting as an interference form also showed the potential for sizeable impacts on sensor functioning in terms of both increases and decreases. The largest decrease in standard deviation observed was 122 percent from the experiments with low temperature shifting. This work shows the incredible power and influence that the forces of nature can have on everyday devices and their need for data from their environment. The results observed from the temperature shift experiments also highlight the danger of leaving temperature based cyber-attacks under researched. The main use of this work is to fill the void in the current literature created by temperature based cyber-attacks and hopefully spur more research to be conducted into this method of cyber threat. | en |
| dc.description.degree | Master of Science | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:35977 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/113086 | en |
| dc.language.iso | en | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | MEMS | en |
| dc.subject | Embedded Sensor | en |
| dc.subject | Mobile device | en |
| dc.subject | Interference | en |
| dc.title | Chameleon Interference: Assessing Vulnerability of Magnetic Sensors to Spoofing and Signal injection attacks through Environmental interference in Mobile Devices | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | Computer Science and Applications | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | masters | en |
| thesis.degree.name | Master of Science | en |
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