相关论文: How to Model Privacy Threats in the Automotive Dom…

Physical persons playing the role of car drivers consume data that is sourced from the Internet and, at the same time, themselves act as sources of relevant data. It follows that citizens' privacy is potentially at risk while they drive,…

Modern cars are getting so computerised that ENISA's phrase "smart cars" is a perfect fit. The amount of personal data that they process is very large and, yet, increasing. Hence, the need to address citizens' privacy while they drive and,…

As generative AI (GenAI) systems become increasingly prevalent across various technological stacks, the question of how such systems handle sensitive and personal data flows becomes increasingly important. Specifically, both the ability to…

Artificial intelligence systems introduce complex privacy risks throughout their lifecycle, especially when processing sensitive or high-dimensional data. Beyond the seven traditional privacy threat categories defined by the LINDDUN…

This research paper delves into the field of autonomous vehicle technology, examining the vulnerabilities inherent in each component of these transformative vehicles. Autonomous vehicles (AVs) are revolutionizing transportation by…

The rapid evolution of Large Language Models (LLMs) has unlocked new possibilities for applying artificial intelligence across a wide range of fields, including privacy engineering. As modern applications increasingly handle sensitive user…

Autonomous vehicles (AVs) are poised to revolutionize modern transportation, offering enhanced safety, efficiency, and convenience. However, the increasing complexity and connectivity of AV systems introduce significant cybersecurity…

Cyber attacks have become a vital threat to connected autonomous vehicles in intelligent transportation systems. Cyber threat intelligence, as the collection of cyber threat information, provides an ideal approach for responding to emerging…

Research and development of privacy analysis tools currently suffers from a lack of test beds for evaluation and comparison of such tools. In this work, we propose a benchmark application that implements an extensive list of privacy…

The rise of online social networks, user-gene-rated content, and third-party apps made data sharing an inevitable trend, driven by both user behavior and the commercial value of personal information. As service providers amass vast amounts…

Despite increasing uptake, there are still many concerns as to the security of virtual assistant hubs (such as Google Nest and Amazon Alexa) in the home. Consumer fears have been somewhat exacerbated by widely-publicised privacy breaches,…

The growing reliance on software in road vehicles has led to the emergence of Software-Defined Vehicles (SDV). This work analyzes SDV security and privacy through a systematic literature review complemented by an industry questionnaire…

Digital forensics is a cornerstone of modern crime investigations, yet it raises significant privacy concerns due to the collection, processing, and storage of digital evidence. Despite that, privacy threats in digital forensics crime…

When it comes to in-vehicle networks (IVNs), the controller area network -- CAN -- bus dominates the market; automobiles manufactured and sold around the world depend on the CAN bus for safety-critical communications between various…

Nowadays, autonomous driving has attracted much attention from both industry and academia. Convolutional neural network (CNN) is a key component in autonomous driving, which is also increasingly adopted in pervasive computing such as…

The growing integration of vehicles with external networks has led to a surge in attacks targeting their Controller Area Network (CAN) internal bus. As a countermeasure, various Intrusion Detection Systems (IDSs) have been suggested in the…

Analyzing privacy threats in software products is an essential part of software development to ensure systems are privacy-respecting; yet it is still a far from trivial activity. While there have been many advancements in the past decade,…

Addressing trust concerns in Smart Home (SH) systems is imperative due to the limited study on preservation approaches that focus on analyzing and evaluating privacy threats for effective risk management. While most research focuses…

Advanced electronic units inside modern vehicles have enhanced the driving experience, but also introduced a myriad of security problems due to the inherent limitations of the internal communication protocol. In the last two decades, a…

In the automotive industry there is a need to handle broad quality deficiencies, eg, performance, maintainability, cybersecurity, safety, and privacy, to mention a few. The idea is to prevent these issues from reaching end-users, ie, road…