Abstract:
An efficient way of predicting the power requirements of electric vehicles is proposed based on a history of vehicle power consumption, speed and acceleration as well as road information. By using this information and the operator's driving pattern, a model extracts the vehicles history of speed and acceleration, which in turn enables the prediction of the vehicle's future power requirements. That is, the power requirement prediction is achieved by combining a real-time power requirement model and the estimation of vehicle's acceleration and speed.
Abstract:
A real-time frame authentication protocol is presented for in-vehicle networks. A frame identifier is made anonymous to unauthorized entities but identifiable by the authorized entities. Anonymous identifiers are generated on a per-frame basis and embedded into each data frame transmitted by a sending ECU. Receiving ECUs use the anonymous identifiers to filter incoming data frames before verifying data integrity. Invalid data frame are filtered without requiring any additional run-time computations.
Abstract:
A computer-implemented method is proposed for coordinating communication amongst wireless communication devices in a wireless network. The coordination scheme creates a side channel between heterogeneous wireless devices to enhance their cooperation. At the transmitter, the coordination scheme appends a customized preamble to a data payload, where the preamble is comprised of a sequence of energy pulses separated by a gap and the duration of the gap encodes coordination data for the receive device. At the receiver, the coordination scheme detects the preamble of the data packet; extracts the coordination data from the preamble of the data packet; and coordinates communication between the transmit device and the receive device using the coordination data.
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:
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:
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:
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:
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.