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1. Authentication and PHY-Security Schemes for Electric Vehicle Dynamic Wireless Charging

   https://doi.org/10.1109/TVT.2023.3318472  

   Nguyen, Toan-Van; Sun, Haijian; Wang, Hongjie; Hu, Rose Qingyang (February 2024, IEEE Transactions on Vehicular Technology)

   This article proposes authentication and physical layer security schemes to improve secure communications between the electric vehicle (EV) and charging infrastructure in dynamic wireless power transfer (DWPT) systems. In particular, a double-encryption with the signature (DoES) scheme is proposed for session key exchange between EV and charging station which provides data authenticity and integrity. To enable low-latency authentication between EV and power transmitter (PT) in DWPT systems, a sign-encrypt-message (SEM) authentication code scheme is designed leveraging symmetric keys for dynamic charging, which ensures privacy and resistance to tampering attacks. The artificial noise-based physical layer security (AN-based PLS) scheme is also proposed at the physical layer to degrade the wiretapped signal quality of multiple eavesdroppers operating in non-colluding and colluding cases. Closed-form expressions for the secrecy outage probability (SOP) and intercept probability (IP) of the considered system with the non-colluding case are derived to show that the proposed AN-based PLS scheme provides lower SOP and IP than the conventional ones without AN. The distance between eavesdroppers and the PT also affects the system SOP and IP in both non-colluding and colluding cases. Moreover, the EV using the DoES scheme takes 52 ms for obtaining session keys from the charging station while it only spends 8.23 ms with the SEM scheme to authenticate with PT for the charging process. 

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2. Continuous User Authentication: A Vital Component of Mobile Security

   Johnson, Sydney; Muhammad, Jean (March 2025, The 2025 ADMI Symposium.)

   As mobile devices become increasingly integral to daily life, the need for robust security measures has intensified. Continuous user authentication (CUA) is an emerging paradigm designed to enhance security by verifying user identity throughout device usage, rather than solely at login. This study aims to explore user perceptions, experiences, and preferences concerning CUA methods, such as biometric scans (e.g., fingerprints, facial recognition) and behavioral analytics (e.g., typing patterns, swipe gestures). We will investigate the importance users place on continuous authentication for safeguarding personal data, as well as the usability challenges they encounter. Specifically, we will delve into how users perceive the reliability and accuracy of biometric and behavioral authentication methods, considering factors such as the perceived invasiveness of biometric scans and concerns about data privacy. Additionally, we will examine how perceptions and preferences for CUA vary across different age groups, as younger generations may be more accustomed to biometric authentication and less concerned about privacy implications, while older generations may have different preferences and concerns. The findings of this study will provide insights into user trust, privacy concerns, and the overall effectiveness of CUA in improving mobile security. By understanding user attitudes, this research seeks to inform the development of more intuitive and secure authentication solutions that align with user needs and expectations across various demographics. 

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3. Clap On, Clap Off: Usability of Authentication Methods in the Smart Home

   He, Weijia; Hainline, Juliette; Padhi, Roshni; Ur, Blase (January 2018, Proceedings of the Interactive Workshop on the Human Aspect of Smarthome Security and Privacy)

   Despite rapid advancements in authentication technologies, little user testing has been conducted on the various authentication methods proposed for smart homes. Users’ preferences about authentication methods may be affected by their beliefs in the reliability of the method, the type and location of devices for which they must authenticate, the effort required for successful authentication, and more. In this paper, we provide insight into users’ concerns with these methods through a 46-participant user study. In particular, we seek to understand users’ preferences towards different authentication methods in terms of the perceived security and usability implications of each method. 

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4. Knock, Knock. Who's There? On the Security of LG's Knock Codes

   Raina Samuel, Philipp Markert (August 2020, 2020 Symposium on Usable Security and Privacy)

   Knock Codes are a knowledge-based unlock authentication scheme used on LG smartphones where a user enters a code by tapping or "knocking" a sequence on a 2x2 grid. While a lesser-used authentication method, as compared to PINs or Android patterns, there is likely a large number of Knock Code users; we estimate, 700,000--2,500,000 in the US alone. In this paper, we studied Knock Codes security asking participants in an online study to select codes on mobile devices in three settings: a control treatment, a blocklist treatment, and a treatment with a larger, 2x3 grid. We find that Knock Codes are significantly weaker than other deployed authentication, e.g., PINs or Android patterns. In a simulated attacker setting, 2x3 grids offered no additional security. Blocklisting, on the other hand, was more beneficial, making Knock Codes' security similar to Android patterns. Participants expressed positive perceptions of Knock Codes, yet usability was challenged. SUS values were "marginal" or "ok" across treatments. Based on these findings, we recommend deploying blocklists for selecting a Knock Code because they improve security but have a limited impact on usability perceptions. 

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5. Fast Continuous User Authentication Using Distance Metric Fusion of Free-Text Keystroke Data

   Ayotte, Blain; Huang, Jiaju; Banavar, Mahesh; Hou, Daqing Hou; Schuckers, Stephanie (January 2019, IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops)

   Keystroke dynamics are a powerful behavioral biometric capable of determining user identity and for continuous authentication. It is an unobtrusive method that can complement an existing security system such as a password scheme and provides continuous user authentication. Existing methods record all keystrokes and use n-graphs that measure the timing between consecutive keystrokes to distinguish between users. Current state-of-the-art algorithms report EER’s of 7.5% or higher with 1000 characters. With 1000 characters it takes a longer time to detect an imposter and significant damage could be done. In this paper, we investigate how quickly a user is authenticated or how many digraphs are required to accurately detect an imposter in an uncontrolled free-text environment. We present and evaluate the effectiveness of three distance metrics individually and fused with each other. We show that with just 100 digraphs, about the length of a single sentence, we achieve an EER of 35.3%. At 200 digraphs the EER drops to 15.3%. With more digraphs, the performance continues to steadily improve. With 1000 digraphs the EER drops to 3.6% which is an improvement over the state-of-the-art. 

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