Bin Zan

Key Agreement Algorithms for Vehicular Communication Networks Based on Reciprocity and Diversity Theorems

Creating secure communication channels in vehicular communication networks is an important topic that has not been well studied. A critical question is how to distribute secret keys between the communication partners. Vehicular networks typically include two different types of communication modes: vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) modes. In this paper, we propose two key agreement algorithms for V2V and V2I, respectively. The first algorithm allows two legitimate users (vehicles) to derive a common secret key through an information-theoretic manner. The second algorithm uses the channel diversity property to generate a secret key between a central server and the individual user. Through evaluation, we show that the proposed V2V key agreement algorithm achieves strong information-theoretic security with a secret bit generation rate much faster than previous work. Numerical analysis also shows that the proposed V2I key agreement scheme can prevent attacks from an adversary with high probability, even if it has a large number of eavesdroppers following the target user.

An energy-aware and intelligent cluster-based event detection scheme in wireless sensor networks

It is important to consider fast and reliable detections of sensing events occurring in various parts of the sensor network. We propose a cluster-based, energy-aware event-detection scheme where events are reliably relayed to a sink in the form of aggregated data packets. The clustering scheme provides faster and better event detection and reliability control capabilities to the areas of the network where an event is occurring. It also reduces network overhead, latency and loss of even information due to cluster rotation. The proposed scheme has the following new features: a new concept of energy-level-based Cluster Head (CH) selection, event packet(s) being capable of transmitting from the CHs to the sink while the cluster(s) are being formed, the sinks assigning a dynamically adaptable reliability factor to clusters, a mechanism used to control the transmission rate of the sensors according to the assigned cluster reliability, etc.

Improving robustness of key extraction from wireless channels with differential techniques

Secure wireless communications typically rely on secret keys, which are difficult to establish in an ad hoc network without a key management infrastructure. Theoretically, the channel reciprocity and spatial decorrelation properties can be used to extract secret key, especially in a Rayleigh fading channel. However, as shown in some prior work by inserting or removing intermediate objects between the communication nodes, the strength of the secret key generated through such methods is low. Furthermore, the impact of small fluctuations also reduces the bit matching rate of such key agreement methods. In this paper, we propose a differential approach which uses the relative difference between two RSS values to determine the value of a secret bit. Additionally, the moving average method can be more easier and properly adapted to the differential approach which reduces the impact of small fluctuations. Experiment results and numerical evaluation show the proposed method has higher security strength, speed and matching rate comparing to a baseline from prior research work.

Linking anonymous location traces through driving characteristics

Efforts to anonymize collections of location traces have often sought to reduce re-identification risks by dividing longer traces into multiple shorter, unlinkable segments. To ensure unlinkability, these algorithms delete parts from each location trace in areas where multiple traces converge, so that it is difficult to predict the movements of any one subject within this area and identify which follow-on trace segments belongs to the same subject. In this paper, we ask whether it is sufficient to base the definition of unlinkability on movement prediction models or whether the revealed trace segments themselves contain a fingerprint of the data subject that can be used to link segments and ultimately recover private information. To this end, we study a large set of vehicle locations traces collected through the Next Generation Simulation program. We first show that using vehicle moving characteristics related features, it is possible to identify outliers such as trucks or motorcycles from general passenger automobiles. We then show that even in a dataset containing similar passenger automobiles only, it is possible to use outlier driving behaviors to link a fraction of the vehicle trips. These results show that the definition of unlinkability may have to be extended for very precise location traces.

Evaluation of privacy preserving algorithms using traffic knowledge based adversary models

By providing location traces of individual vehicles, mobile traffic sensors have quickly emerged as an important data source for traffic applications. In dealing with the privacy issues associated with this, researchers have been proposing different privacy protection algorithms. In this paper, we propose traffic-knowledge-based adversary models to attack privacy algorithms. By doing so, we can compare and evaluate different privacy algorithms in terms of both privacy protection and the convenience for traffic modeling. Results show that by having a relatively good privacy performance, the released datasets of both the 3.3 level of confusion entropy and the 0.1 individual likelihood can still be applied for a fine level of traffic applications.

VTL zone-aware path cloaking algorithm

Traffic engineering applications often benefit from collecting vehicle GPS traces in well-defined locations. As a motivating example, we will consider a traffic signal performance evaluation technique which requires GPS traces of vehicles traversing intersections. Since these applications do not require vehicle identity information, they are a good candidate for data de-identification techniques. Prior techniques can either provide data from specific locations or guarantee a high degree of anonymity under light traffic conditions but do not achieve both. In this paper, we propose a virtual trip line zone-aware path cloaking algorithm which combines these features. Zones where data should be retained can be predefined over the intersections of interest and the path cloaking algorithm uses entropy-estimates to decide whether the data can be revealed. Result obtained from a traffic simulator show that the application success rate increased from 39 to 82% compared to a zone-unaware path cloaking algorithm, while achieving a similar degree of privacy.

Random channel hopping schemes for key agreement in wireless networks

Secure wireless communications typically rely on secret keys, which are hard to establish in a mobile setting without a key management infrastructure. In this paper, we propose a channel hopping protocol that lets two stations agree on a secret key over an open wireless channel and without use of any pre-existing key. It is secure against an adversary with typical consumer radio hardware that only allows receiving on a single (or a few) channel at a time. Theoretical analysis and simulation results indicate that this approach can generate a 128-bit key in 0.3 seconds. This is significantly faster than prior techniques that extract key material from the wireless channel.

The Boomerang Protocol: Tieing Data to Geographic Locations in Mobile Disconnected Networks

We present the novel boomerang protocol to efficiently retain information at a particular geographic location in a sparse network of highly mobile nodes without use of infrastructure networks. Our proof-of-concept implementation revealed the main challenge in implementing the Boomerang protocol is to accurately detect whether a node is divergent from a recorded trajectory and then followed up with a detailed study to address the challenge. Simulation with automotive traffic traces for a southern New Jersey region shows that the protocol improves packet return rate by 70% compared to a baseline implementation using shortest path geographic routing.

A privacy preserving system for friend locator applications

One interesting application of online social networks is the friend locator, in which the application server informs users through mobile devices if their listed friends are nearby in terms of geographical locations. However, in such services, it is challenging to protect the privacy of an individual user. Previous privacy protection solutions for friend locators do not guarantee a high level of privacy and maintain efficiency. In this paper, we propose a privacy preserving system to guarantee both strong privacy and efficiency. Additionally, we use the polygon decomposition method to achieve both accuracy and flexibility especially for irregular areas of interest. Finally, through numerical analysis and simulation, we show that the proposed system and algorithm can achieve high privacy, efficiency, accuracy and flexibility.

ROME: Road monitoring and alert system through Geocache

We present a road monitoring and alert system implemented using a novel Geocache concept to enable efficient spatial monitoring in a mobile distributed sensing scenario. Technology trends have led to the integration of positioning, communications, and sensing capabilities into mobile entities such as cars and cellular phones, enabling them to monitor and report on their surroundings. We consider scenarios where events of interest must be detected from aggregated readings of multiple devices. For example, road monitoring could infer road defects from increased vibrations or road hazards from repeated emergency braking at the same location. This raises the challenge of aggregating sensor data from multiple mobiles that have passed the same location with efficient usage of communication resources. We introduce the Geocache concept, which allows anchoring sensor information at specific spatial coordinates, rather than storing it in a designated node. The Geocache protocol in either its relayed or delayed variant will then opportunistically determine a storage vehicle near the Geocache and hand the data off as vehicles pass by. We show through simulations with synthetic and realistic automotive position traces that relayed Geocache reduce messaging overhead by 66% compared to a baseline periodic broadcasting scheme and a Boomerang Geocache can provide a further 71% reduction when only few of the passing cars are able to sense the event.