Browse Topic: Data privacy
The added connectivity and transmission of personal and payment information in electric vehicle (EV) charging technology creates larger attack surfaces and incentives for malicious hackers to act. As EV charging stations are a major and direct user interface in the charging infrastructure, ensuring cybersecurity of the personal and private data transmitted to and from chargers is a key component to the overall security. Researchers at Southwest Research Institute® (SwRI®) evaluated the security of direct current fast charging (DCFC) EV supply equipment (EVSE). Identified vulnerabilities included values such as the MAC addresses of both the EV and EVSE, either sent in plaintext or encrypted with a known algorithm. These values allowed for reprogramming of non-volatile memory of power-line communication (PLC) devices as well as the EV’s parameter information block (PIB). Discovering these values allowed the researchers to access the IPv6 layer on the connection between the EV and EVSE
The emergence of data-driven healthcare promises predictive and preventive care through enhanced data integration and analytics. This trend means that medical device companies must navigate challenges related to data privacy and operational efficiency while transitioning to a data-centric approach. Artificial intelligence (AI) is spearheading this shift toward hyper-personalized medicine, enabling precision treatments based on genetic profiles and predictive analytics for early disease detection. Advancements in telemedicine, AI, wearable technology, and data analytics, are reshaping how care is delivered, making it more accessible, personalized, and efficient in 2025.
Cybersecurity, particularly in the automotive sector, is of paramount importance in today’s digital age. With the advent of connected commercial vehicles, which leverage telematics for efficient fleet management, the landscape of automotive cybersecurity is rapidly evolving. These vehicles, integral to logistics and transportation businesses, are becoming increasingly connected, thereby escalating the risks associated with cybersecurity threats. These commercial vehicles are becoming prime targets for cyber-attacks due to their connectivity and the valuable data they hold. The potential consequences of these cyber-attacks can range from data breaches to disruptions in fleet operations, and even safety risks. This paper analyses the unique challenges faced by the commercial vehicle sector, such as the need for robust telematics systems, secure communication channels, and stringent data protection measures. Case studies of notable cybersecurity incidents involving commercial vehicles are
A research team led by Rice University’s Edward Knightly has uncovered an eavesdropping security vulnerability in high-frequency and high-speed wireless backhaul links, widely employed in critical applications such as 5G wireless cell phone signals and low-latency financial trading on Wall Street.
Data privacy questions are particularly timely in the automotive industry as—now more than ever before—vehicles are collecting and sharing data at great speeds and quantities. Though connectivity and vehicle-to-vehicle technologies are perhaps the most obvious, smart city infrastructure, maintenance, and infotainment systems are also relevant in the data privacy law discourse. Facial Recognition Software and Privacy Law in Transportation Technology considers the current legal landscape of privacy law and the unanswered questions that have surfaced in recent years. A survey of the limited recent federal case law and statutory law, as well as examples of comprehensive state data privacy laws, is included. Perhaps most importantly, this report simplifies the balancing act that manufacturers and consumers are performing by complying with data privacy laws, sharing enough data to maximize safety and convenience, and protecting personal information. Click here to access the full SAE EDGETM
The concerns surrounding AV adoption encompass the data protection factor. An online survey was conducted to gain insights into this concern, targeting UAE residents with knowledge about Autonomous Vehicle (AV) technology. The collected data were subjected to statistical analysis to provide valuable information for the UAE government and private sectors. To achieve this goal, we conducted a statistical analysis of the collected data, which resulted in further insights regarding the obstacles impeding the adoption of AV technologies in the United Arab Emirates. This analysis further quantifies the factors that contributed to UAE public concerns. We also examined user group evaluations in terms of their propensity to employ the technology in the future.
By 2030, about 95% of new vehicles sold globally will be connected, up from around 50% today. Around 45% of these vehicles will have intermediate and advanced connectivity features (source: McKinsey, 2021). Modernization, standardization, and automation are the key steps in the roadmap of data handling for connected vehicles. Vehicle software increasingly sits within a connected ecosystem of devices. Consumer expectations are shifting more towards digital compatibility, connectivity, and new functionalities offered in autonomous vehicles. Digitalization is turning the vehicles of the future into commodities that are as experimental as they are useful. Many OEMs are at the beginning of this transformation journey and have struggled on the software side of things. The entire automotive industry is putting its efforts into effectively monetizing the data captured during the development and management of autonomous vehicles. It is not easy to handle the complexity, elasticity, and volume
Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality. Legal Issues Facing Automated Vehicles, Facial Recognition, and Individual Rights seeks to highlight the benefits of using FRS in public and private transportation technology and
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Even though ultrasound has been studied by scientists for many years, its capabilities in practical applications are yet to be fully harnessed.
The connected car has already become a reality. It is a subject not just electrifying customers and manufacturers but also security researchers and IT experts. And in a worst-case scenario, criminal hackers as well. For years, security experts have observed the fact that the desktop PC is not the only target of digital attacks anymore. A large part of the malware is now customized to hit mobile devices. It would be negligent to believe that this development would leave the connected car unmolested.
Autonomous vehicles might one day be able to implement privacy preserving driving patterns which humans may find too difficult to implement. In order to measure the difference between location privacy achieved by humans versus location privacy achieved by autonomous vehicles, this paper measures privacy as trajectory anonymity, as opposed to single location privacy or continuous privacy. This paper evaluates how trajectory privacy for randomized driving patterns could be twice as effective for autonomous vehicles using diverted paths compared to Google Map API generated shortest paths. The result shows vehicles mobility patterns could impact trajectory and location privacy. Moreover, the results show that the proposed metric outperforms both K-anonymity and KDT-anonymity.
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