Securing the Invisible Thread: A Comprehensive Analysis of BLE Tracker Security in Apple AirTags and Samsung SmartTags
- URL: http://arxiv.org/abs/2401.13584v1
- Date: Wed, 24 Jan 2024 16:50:54 GMT
- Title: Securing the Invisible Thread: A Comprehensive Analysis of BLE Tracker Security in Apple AirTags and Samsung SmartTags
- Authors: Hosam Alamleh, Michael Gogarty, David Ruddell, Ali Abdullah S. AlQahtani,
- Abstract summary: This study presents an in-depth analysis of the security landscape in Bluetooth Low Energy (BLE) tracking systems.
Our investigation traverses a wide spectrum of attack vectors such as physical tampering, firmware exploitation, signal spoofing, eavesdropping, jamming, app security flaws, Bluetooth security weaknesses, location spoofing, threats to owner devices, and cloud-related vulnerabilities.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This study presents an in-depth analysis of the security landscape in Bluetooth Low Energy (BLE) tracking systems, with a particular emphasis on Apple AirTags and Samsung SmartTags, including their cryptographic frameworks. Our investigation traverses a wide spectrum of attack vectors such as physical tampering, firmware exploitation, signal spoofing, eavesdropping, jamming, app security flaws, Bluetooth security weaknesses, location spoofing, threats to owner devices, and cloud-related vulnerabilities. Moreover, we delve into the security implications of the cryptographic methods utilized in these systems. Our findings reveal that while BLE trackers like AirTags and SmartTags offer substantial utility, they also pose significant security risks. Notably, Apple's approach, which prioritizes user privacy by removing intermediaries, inadvertently leads to device authentication challenges, evidenced by successful AirTag spoofing instances. Conversely, Samsung SmartTags, designed to thwart beacon spoofing, raise critical concerns about cloud security and user privacy. Our analysis also highlights the constraints faced by these devices due to their design focus on battery life conservation, particularly the absence of secure boot processes, which leaves them susceptible to OS modification and a range of potential attacks. The paper concludes with insights into the anticipated evolution of these tracking systems. We predict that future enhancements will likely focus on bolstering security features, especially as these devices become increasingly integrated into the broader IoT ecosystem and face evolving privacy regulations. This shift is imperative to address the intricate balance between functionality and security in next-generation BLE tracking systems.
Related papers
- Fingerprint Theft Using Smart Padlocks: Droplock Exploits and Defenses [0.0]
A lack of attention to device security and user-awareness beyond the primary function of these IoT devices may be exposing users to invisible risks.
This paper extends upon prior work that defined the "droplock", an attack whereby a smart lock is turned into a wireless fingerprint harvester.
We perform a more in-depth analysis of a broader range of vulnerabilities and exploits that make a droplock attack easier to perform and harder to detect.
arXiv Detail & Related papers (2024-07-31T07:40:05Z) - Rethinking the Vulnerabilities of Face Recognition Systems:From a Practical Perspective [53.24281798458074]
Face Recognition Systems (FRS) have increasingly integrated into critical applications, including surveillance and user authentication.
Recent studies have revealed vulnerabilities in FRS to adversarial (e.g., adversarial patch attacks) and backdoor attacks (e.g., training data poisoning)
arXiv Detail & Related papers (2024-05-21T13:34:23Z) - Is Your Kettle Smarter Than a Hacker? A Scalable Tool for Assessing Replay Attack Vulnerabilities on Consumer IoT Devices [1.5612101323427952]
ENISA and NIST security guidelines emphasize the importance of enabling default local communication for safety and reliability.
We propose a tool, named REPLIOT, able to test whether a replay attack is successful or not, without prior knowledge of the target devices.
We find that 75% of the remaining devices are vulnerable to replay attacks with REPLIOT having a detection accuracy of 0.98-1.
arXiv Detail & Related papers (2024-01-22T18:24:41Z) - DynamiQS: Quantum Secure Authentication for Dynamic Charging of Electric Vehicles [61.394095512765304]
Dynamic Wireless Power Transfer (DWPT) is a novel technology that allows charging an electric vehicle while driving.
Recent advancements in quantum computing jeopardize classical public key cryptography.
We propose DynamiQS, the first post-quantum secure authentication protocol for dynamic wireless charging.
arXiv Detail & Related papers (2023-12-20T09:40:45Z) - Fortress: Securing IoT Peripherals with Trusted Execution Environments [2.2476099815732518]
Internet of Things (IoT) devices often collect confidential information, such as audio and visual data, through peripheral inputs like microphones and cameras.
We propose a generic design to enhance the privacy in IoT-based systems by isolating peripheral I/O memory regions in a secure kernel space of a trusted execution environment (TEE)
The sensitive peripheral data is then securely transferred to a user-space TEE, where obfuscation mechanisms can be applied before it is relayed to third parties, e.g., the cloud.
arXiv Detail & Related papers (2023-12-05T07:12:58Z) - SyzTrust: State-aware Fuzzing on Trusted OS Designed for IoT Devices [67.65883495888258]
We present SyzTrust, the first state-aware fuzzing framework for vetting the security of resource-limited Trusted OSes.
SyzTrust adopts a hardware-assisted framework to enable fuzzing Trusted OSes directly on IoT devices.
We evaluate SyzTrust on Trusted OSes from three major vendors: Samsung, Tsinglink Cloud, and Ali Cloud.
arXiv Detail & Related papers (2023-09-26T08:11:38Z) - When Authentication Is Not Enough: On the Security of Behavioral-Based Driver Authentication Systems [53.2306792009435]
We develop two lightweight driver authentication systems based on Random Forest and Recurrent Neural Network architectures.
We are the first to propose attacks against these systems by developing two novel evasion attacks, SMARTCAN and GANCAN.
Through our contributions, we aid practitioners in safely adopting these systems, help reduce car thefts, and enhance driver security.
arXiv Detail & Related papers (2023-06-09T14:33:26Z) - The Dark (and Bright) Side of IoT: Attacks and Countermeasures for
Identifying Smart Home Devices and Services [4.568911586155096]
We build up a model describing the traffic patterns characterizing three popular IoT smart home devices.
We prove that it is possible to detect and identify with overwhelming probability their presence and the services running by the aforementioned devices.
arXiv Detail & Related papers (2020-09-16T13:28:59Z) - Smart Home, security concerns of IoT [91.3755431537592]
The IoT (Internet of Things) has become widely popular in the domestic environments.
People are renewing their homes into smart homes; however, the privacy concerns of owning many Internet connected devices with always-on environmental sensors remain insufficiently addressed.
Default and weak passwords, cheap materials and hardware, and unencrypted communication are identified as the principal threats and vulnerabilities of IoT devices.
arXiv Detail & Related papers (2020-07-06T10:36:11Z) - Mind the GAP: Security & Privacy Risks of Contact Tracing Apps [75.7995398006171]
Google and Apple have jointly provided an API for exposure notification in order to implement decentralized contract tracing apps using Bluetooth Low Energy.
We demonstrate that in real-world scenarios the GAP design is vulnerable to (i) profiling and possibly de-anonymizing persons, and (ii) relay-based wormhole attacks that basically can generate fake contacts.
arXiv Detail & Related papers (2020-06-10T16:05:05Z) - A Privacy-Preserving Solution for Proximity Tracing Avoiding Identifier
Exchanging [0.0]
We propose a solution leveraging GPS to detect proximity, and Bluetooth to improve accuracy, without enabling exchange of identifiers.
Unlike related existing solutions, no complex cryptographic mechanism is adopted, while ensuring that the server does not learn anything about locations of users.
arXiv Detail & Related papers (2020-05-20T18:48:20Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.