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ItemSecurity Analysis of the Masimo MightySat: Data Leakage to a Nosy Neighbor( 2021-01-05)Embedded technology known as the Internet of Things (IoT) has been integrated into everyday life, from the home, to the farm, industry, enterprise, the battlefield, and even for medical devices. With the increased use of networked devices comes an increased attack surface for malicious actors to gather and inject data, putting the privacy of users at risk. This research considers the Masimo MightySat fingertip pulse oximeter and the companion Masimo Professional Health app from a security standpoint, analyzing the Bluetooth Low Energy (BLE) communication from the device to the application and the data leakage between the two. It is found that with some analysis of a personally owned Masimo MightySat Rx through the use of an Ubertooth BLE traffic sniffer, static analysis of the HCI\_snoop.log and application data, and dynamic analysis of the app, data could be reasonably captured for another MightySat and interpret it to learn user health data.
ItemLocation Privacy in the Era of 5G( 2021-01-05)Fifth Generation (5G) wireless technology is usher- ing in a new age of interconnectivity, and as it does definitions of privacy may well change with it. In this paper we will focus on the changing nature of location privacy, while aspiring to increase community cognizance of vulnerabilities within the 5G network that threaten end-user privacy. To this end, we will address the statistical efficacy of a multilateration attack utilizing timing advance commands within the 5G cloud radio access network, by showcasing that such an attack meets the Cramér-Rao Lower Bound across each subcarrier spacing. We will also demonstrate how position estimates within 5G can be further refined using methods previously shown to be effective in Long Term Evolution Networks. Lastly, we will demonstrate the attack in a simulated environment modeled after the conference grounds, using current real-world deployments of 5G on Kauai
ItemA Bio-Inspired Trust Framework in Wireless Ad Hoc Networks( 2021-01-05)Cyber attacks are amongst the most serious threats facing people and organizations. In the face of the increasing complexity and effectiveness of these attacks, creative approaches to defense are required. Groups of insects survive due to their use of collaborative approaches with the unique ability to detect anomalies using primarily local data and very limited computational resources (i.e., limited brain power). These attributes are even more crucial for wireless ad hoc networks where the number of nodes and connections between those nodes are ephemeral. We propose a trust framework inspired by the detection mechanisms exhibited by bee swarms in which a wireless node can only observe and leverage the actions of their neighbors rather than the global knowledge of the network to make a decision. This leveraging of local knowledge is an important aspect of trust in wireless networks in which global state information is difficult to encapsulate. We also utilize models from binary voting to present a straightforward mathematical model for our bee-inspired trust framework in wireless ad hoc networks.