Abstract: A computer-implemented method is presented for detecting non-compliance with an opt-out decision of a user. The method includes: identifying select statements of a privacy policy for an online tracking entity by analyzing webpages associated with the online tracking entity, where the select statements specify data practices in response to an opt-out decision; detecting transfer of cookies from a web browser to a server, where the cookies are transferred after an opt-out decision by the given user and the server is associated with the given online tracking entity; analyzing content of the detected cookies in relation to the select statements of the privacy policy; and notifying the given user of a violation of the privacy policy in response to determining an inconsistency between the content of the detected cookies and the select statements of the privacy policy.

Abstract: Left turns are known to be one of the most dangerous driving maneuvers. An effective way to mitigate this safety risk is to install a left-turn enforcement—for example, a protected left-turn signal or all-way stop signs—at every turn that preserves a traffic phase exclusively for left turns. Although this protection scheme can significantly increase the driving safety, information on whether or not a road segment (e.g., intersection) has such a setting is not yet available to the public and navigation systems. This disclosure presents a system that exploits mobile crowdsensing and deep learning to classify the protection settings of left turns.

Abstract: A driving authentication system is presented for a vehicle. The system includes: a dongle interfaced with a battery of the vehicle and an authenticator configured to receive a discharge current from the battery. The dongle operates to modulate discharge current from the battery with an input code; and the authenticator demodulate the input code from the discharge current, compares the input code to the one or more known authentication codes and, in response to the input code matching one of the one or more known authentication codes, controls power capacity of the battery.

Abstract: As automotive security concerns are rising, the Controller Area Network (CAN)—the de facto standard of in-vehicle communication protocol—has come under scrutiny due to its lack of encryption and authentication. Several vulnerabilities, such as eavesdropping, spoofing, and replay attacks, have shown that the current implementation needs to be extended. Both academic and commercial solutions for a secure CAN have been proposed, but OEMs have not yet integrated them into their products. The main reasons for this lack of adoption are their heavy use of limited computational resources in the vehicle, increased latency that can lead to missed deadlines for safety-critical messages, as well as insufficient space available in a CAN frame to include a Message Authentication Code (MAC). By making a trade-off between security and performance, this disclosure overcomes the aforementioned problems of a secure CAN.

Abstract: A driving authentication system is presented for a vehicle. The system includes: a dongle interfaced with a battery of the vehicle and an authenticator configured to receive a discharge current from the battery. The dongle operates to modulate discharge current from the battery with an input code; and the authenticator demodulate the input code from the discharge current, compares the input code to the one or more known authentication codes and, in response to the input code matching one of the one or more known authentication codes, controls power capacity of the battery.

Abstract: A method is presented for controlling power output by a battery in a vehicle. The method includes: measuring voltage of the battery during a sequence of vehicle events to form a time series, where each vehicle event is powered by the battery; constructing an unknown fingerprint from the voltage measurements made during the sequence of vehicle events, where the unknown fingerprint is indicative of a sequence of vehicle events; comparing the unknown fingerprint to the at least one fingerprint; receiving a start signal, where the start signal is a request to start the engine of the vehicle; and, in response to receiving the start signal and based on the comparison of the unknown fingerprint to the at least one fingerprint, outputting electric power from the battery to an electric starter motor of the vehicle.

Abstract: One commonality among most vehicular security attacks reported to date is that they ultimately require write access to the CAN bus. In order to cause targeted and intentional changes in the vehicle behavior, malicious CAN injection attacks require knowledge of the CAN message format. However, since this format is proprietary to OEMs and can differ even among different models of a single make of vehicle, one must manually reverse-engineer the CAN message format of each vehicle they target. To mitigate this difficulty, an automated CAN message translator is presented.

Abstract: Lithium-ion cells are widely used in various platforms, such as electric vehicles (EVs) and mobile devices. Complete and fast charging of cells has always been the goal for sustainable system operation. However, fast charging is not always the best solution, especially in view of a new finding that cells need to rest/relax after being charged with high current to avoid accelerated capacity fading. A user aware charging algorithm is proposed which maximizes the charged capacity within a user-specified available charging time (i.e., user-awareness) while ensuring enough relaxation (i.e., cell-awareness) and keeping cell temperature below a safe level.

Abstract: An user-interactive charging paradigm is presented that tailors the device charging to the user's real-time needs. The core of approach is a relaxation-aware charging algorithm that maximizes the charged capacity within the user's available time and slows down the battery's capacity fading. The approach also integrates relaxation-aware charging algorithm existing fast charging algorithms via a user-interactive interface, allowing users to choose a charging method based on their real-time needs. The relaxation-aware charging algorithm is shown to slow down the battery fading by over 36% on average, and up to 60% in extreme cases, when compared with existing fast charging solutions. Such fading slowdown translates to, for instance, an up to 2-hour extension of the LTE time for a Nexus 5X phone after 2-year usage, revealed by a trace-driven analysis based on 976 charging cases collected from 7 users over 3 months.

Abstract: Mobile devices are only as useful as their battery lasts. Unfortunately, the operation and life of a mobile device's battery degrade over time and usage. The state-of-health (SoH) of batteries quantifies their degradation, but mobile devices' support for its estimation is very poor due mainly to the limited hardware and dynamic usage patterns, causing various problems such as shutting off the devices unexpectedly. To remedy this lack of support, a low-cost user-level SoH estimation service is developed for mobile devices based only on their battery voltage, which is already available on all commodity mobile devices. The design of the estimation service is inspired by an empirical observation that the relaxing voltages of a device battery fingerprint its SoH, and is steered by extensive measurements with 13 batteries used for various devices, such as Nexus 6P, Nexus 5X, Xperia Z5, Galaxy S3, iPhone 6 Plus, etc.

Abstract: Driver fingerprinting using sensor data was known to be feasible only with access to in-car data. This disclosure presents a novel technique for identifying a vehicle driver from only one vehicle turn and using zero-permission sensors residing in the mobile device. Through extensive evaluations, extracted features are shown to reflect only the drivers unique turning style and thus functions as the core of driver fingerprinting.

Abstract: Research efforts to detect and prevent possible attacks on vehicles have led to various defense schemes that are capable of preventing attacks and/or determining the presence/absence of an attack on the in-vehicle network. However, these efforts still cannot identify which Electronic Control Unit (ECU) on the in-vehicle network actually mounted the attack. Moreover, they cannot detect attacks by an adversary that impersonates ECUs injecting in-vehicle messages aperiodically. Identifying the source of an attack is essential for efficient forensic, isolation, security patch, etc. To fill these gaps, a method is presented for detecting and identifying compromised ECUs in a vehicle network.

Abstract: An anomaly-based intrusion detection system is presented for use in vehicle networks. The intrusion detection system measures and exploits the intervals of periodic in-vehicle messages for fingerprinting electronic control units. Fingerprints are then used for constructing a baseline of clock behaviors, for example with a Recursive Least Squares algorithm. Based on the baseline, the intrusion detection system uses cumulative sum to detect any abnormal shifts in the identification errors—a clear sign of an intrusion. This approach allows quick identification of in-vehicle network intrusions with low false positive rates.

Abstract: An important new vulnerability was discovered and is applicable to several in-vehicle networks including Control Area Network (CAN), the de facto standard in-vehicle network protocol. Specifically, a bus-off attack exploits the safe mode of CAN to disconnect or shut down uncompromised (healthy) ECUs. This is an important attack that must be thwarted, since once the attacker compromises an ECU, it is easy to mount the attack on safety-critical ECUs while its prevention/detection is very difficult. Based on analysis and experimental results, a mechanism to detect and/or prevent a bus-off attack is proposed and evaluated.

Abstract: People use their mobile devices anywhere and anytime to run various apps, and the information shown on their device screens can be seen by nearby unauthorized parties, referred to as shoulder surfers. To mitigate this privacy threat, techniques have been developed utilizing human vision and optical system properties to hide the users' on-screen information from the shoulder surfers. Specifically, the proposed techniques discretize the device screen into grid patterns to neutralize the low-frequency components so that the on-screen information will “blend into” the background when viewed from the outside of the designed visible range.

Abstract: Left turns are known to be one of the most dangerous driving maneuvers. An effective way to mitigate this safety risk is to install a left-turn enforcement—for example, a protected left-turn signal or all-way stop signs—at every turn that preserves a traffic phase exclusively for left turns. Although this protection scheme can significantly increase the driving safety, information on whether or not a road segment (e.g., intersection) has such a setting is not yet available to the public and navigation systems. This disclosure presents a system that exploits mobile crowdsensing and deep learning to classify the protection settings of left turns.

Abstract: An in-car phone localization scheme is proposed to determine, in real time, the locations of smartphones inside a moving car, with the goal of preventing smartphone-distracted driving. The localization system operates on commodity smartphones, and does not require any additional special/customized sensors or devices to be installed inside the car, making its deployment easy and attractive to users and carmakers. Even when a phone is moved from one location to another inside a moving car, the system will detect this movement, record the sensor data, and estimate the phone's destination location. The system captures the trajectory of each phone movement, the change of magnetic field, and the RSSI readings from the car Bluetooth transceiver, and then estimates the phone's destination location by matching the trajectory with the variation of magnetic field and the Bluetooth RSSI readings.

Abstract: A method is presented for controlling power output by a battery in a vehicle. The method includes: measuring voltage of the battery during a sequence of vehicle events to form a time series, where each vehicle event is powered by the battery; constructing an unknown fingerprint from the voltage measurements made during the sequence of vehicle events, where the unknown fingerprint is indicative of a sequence of vehicle events; comparing the unknown fingerprint to the at least one fingerprint; receiving a start signal, where the start signal is a request to start the engine of the vehicle; and, in response to receiving the start signal and based on the comparison of the unknown fingerprint to the at least one fingerprint, outputting electric power from the battery to an electric starter motor of the vehicle.

Abstract: An in-car phone localization scheme is proposed to determine, in real time, the locations of smartphones inside a moving car, with the goal of preventing smartphone-distracted driving. The localization system operates on commodity smartphones, and does not require any additional special/customized sensors or devices to be installed inside the car, making its deployment easy and attractive to users and carmakers. Even when a phone is moved from one location to another inside a moving car, the system will detect this movement, record the sensor data, and estimate the phone's destination location. The system captures the trajectory of each phone movement, the change of magnetic field, and the RSSI readings from the car Bluetooth transceiver, and then estimates the phone's destination location by matching the trajectory with the variation of magnetic field and the Bluetooth RSSI readings.

Abstract: Data in vehicle networks has been treated as proprietary assets, due to car makers' concern of potential IP infringement via extraction of confidential vehicular data. To address this concern, an intermediate gateway in between internal and external networks translates proprietary in-vehicle data to rich type data, thus preventing the exposure of raw in-vehicle data. The translation relies solely on the gateway which can be a direct target of cyberattacks, making it difficult to trust the data through the gateway. This, in turn, requires authentication of the translated data. A communication protocol is presented that provides secure communications between the vehicle's internal components and external entities. The protocol enables authorization of external servers for in-vehicle ECUs as well as authentication and proof of messages between internal and external components to combat a compromised gateway.