Ruben Rios

Analysis of location privacy solutions in wireless sensor networks

Extensive work has been done on the protection of wireless sensor networks (WSNs) from the hardware to the application layer. However, only recently, the privacy preservation problem has drawn the attention of the research community because of its challenging nature. This problem is exacerbated in the domain of WSNs owing to the extreme resource limitation of sensor nodes. In this study the authors focus on the location privacy problem in WSNs, which allows an adversary to determine the location of nodes of interest to him. The authors provide a taxonomy of solutions based on the power of the adversary and the main techniques proposed by the various solutions. In addition, the authors describe and analyse the advantages and disadvantages of different approaches. Finally, they discuss some open challenges and future directions of research.

Exploiting Context-Awareness to Enhance Source-Location Privacy in Wireless Sensor Networks

The source-location privacy problem in Wireless Sensor Networks has been traditionally tackled by the creation of random routes for every packet transmitted from the source nodes to the base station. These schemes provide a considerable protection level at a high cost in terms of message delivery time and energy consumption. This overhead is due to the fact that the data routing process is done in a blind way, without knowledge about the location of the attacker. In this work, we propose the Context-Aware Location Privacy (CALP) approach, which takes advantage of the ability of sensor nodes to perceive the presence of a mobile adversary in their vicinity in order to transmit data packets in a more energy-efficient and privacy-preserving manner. In particular, we apply the concepts of CALP to the development of a shortest-path CALP routing algorithm. A permissive and a strict version of the protocol are studied for different adversarial models and the proposed schemes are evaluated through simulation experiments in terms of privacy protection and energy consumption. Finally, we present the conclusions of the paper as well as possible extensions of this work.

Evolving privacy: From sensors to the Internet of Things

Abstract The Internet of Things (IoT) envisions a world covered with billions of smart, interacting things capable of offering all sorts of services to near and remote entities. The benefits and comfort that the IoT will bring about are undeniable, however, these may come at the cost of an unprecedented loss of privacy. In this paper we look at the privacy problems of one of the key enablers of the IoT, namely wireless sensor networks, and analyse how these problems may evolve with the development of this complex paradigm. We also identify further challenges which are not directly associated with already existing privacy risks but will certainly have a major impact in our lives if not taken into serious consideration.

Probabilistic receiver-location privacy protection in wireless sensor networks

Wireless sensor networks (WSNs) are continually exposed to many types of attacks. Among these, the attacks targeted at the base station are the most devastating ones since this essential device processes and analyses all traffic generated in the network. Moreover, this feature can be exploited by a passive adversary to determine its location based on traffic analysis. This receiver-location privacy problem can be reduced by altering the traffic pattern of the network but the adversary may still be able to reach the base station if he gains access to the routing tables of a number of sensor nodes. In this paper we present HISP-NC (Homogenous Injection for Sink Privacy with Node Compromise protection), a receiver-location privacy solution that consists of two complementary schemes which protect the location of the base station in the presence of traffic analysis and node compromise attacks. The HISP-NC data transmission protocol prevents traffic analysis by probabilistically hiding the flow of real traffic with moderate amounts of fake traffic. Moreover, HISP-NC includes a perturbation mechanism that modifies the routing tables of the nodes to introduce some level of uncertainty in attackers capable of retrieving the routing information from the nodes. Our scheme is validated both analytically and experimentally through extensive simulations.

A privacy-aware continuous authentication scheme for proximity-based access control

Continuous authentication is mainly associated with the use of biometrics to guarantee that a resource is being accessed by the same user throughout the usage period. Wireless devices can also serve as a supporting technology for continuous authentication or even as a complete alternative to biometrics when accessing proximity-based services. In this paper we present the implementation of a secure, non-invasive continuous authentication scheme supported by the use of Wearable Wireless Devices (WWD), which allow users to gain access to proximity-based services while preserving their privacy. Additionally we devise an improved scheme that circumvents some of the limitations of our implementation.

HIDE_DHCP: Covert Communications through Network Configuration Messages

Covert channels are a form of hidden communication that may violate the integrity of systems. Since their birth in multilevel security systems in the early 70’s they have evolved considerably, such that new solutions have appeared for computer networks mainly due to vague protocols specifications. We analyze a protocol extensively used today, the Dynamic Host Configuration Protocol (DHCP), in search of new forms of covert communication. From this analysis we observe several features that can be effectively exploited for subliminal data transmission. This results in the implementation of HIDE_DHCP, which integrates three covert channels that accommodate to different stealthiness and bandwidth requirements.

Robust Probabilistic Fake Packet Injection for Receiver-Location Privacy in WSN

The singular communication model in wireless sensor networks (WSNs) originate pronounced traffic patterns that allow a local observer to deduce the location of the base station, which must be kept secret for both strategical and security reasons. In this work we present a new receiver-location privacy solution called HISP (Homogenous Injection for Sink Privacy). Our scheme is based on the idea of hiding the flow of real traffic by carefully injecting fake traffic to homogenize the transmissions from a node to its neighbors. This process is guided by a lightweight probabilistic approach ensuring that the adversary cannot decide with sufficient precision in which direction to move while maintaining a moderate amount of fake traffic. Our system is both validated analytically and experimentally through simulations.

Indistinguishable regions in geographic privacy

The ubiquity of positioning devices poses a natural security challenge: users want to take advantage of location-related services as well as social sharing of their position but at the same time have security concerns about how much information should be shared about their exact position. This paper discusses different location-privacy problems, their formalization and the novel notion of indistinguishability regions that allows one to proof that a given obfuscation function provides a good trade-off between location sharing and privacy.

Location Privacy in WSNs: Solutions, Challenges, and Future Trends

Privacy preservation is gaining popularity in Wireless Sensor Network (WSNs) due to its adoption in everyday scenarios. There are a number of research papers in this area many of which concentrate on the location privacy problem. In this paper we review and categorise these solutions based on the information available to the adversary and his capabilities. But first we analyse whether traditional anonymous communication systems conform to the original requirements of location privacy in sensor networks. Finally, we present and discuss a number of challenges and future trends that demand further attention from the research community.

IoT-Forensics Meets Privacy: Towards Cooperative Digital Investigations

IoT-Forensics is a novel paradigm for the acquisition of electronic evidence whose operation is conditioned by the peculiarities of the Internet of Things (IoT) context. As a branch of computer forensics, this discipline respects the most basic forensic principles of preservation, traceability, documentation, and authorization. The digital witness approach also promotes such principles in the context of the IoT while allowing personal devices to cooperate in digital investigations by voluntarily providing electronic evidence to the authorities. However, this solution is highly dependent on the willingness of citizens to collaborate and they may be reluctant to do so if the sensitive information within their personal devices is not sufficiently protected when shared with the investigators. In this paper, we provide the digital witness approach with a methodology that enables citizens to share their data with some privacy guarantees. We apply the PRoFIT methodology, originally defined for IoT-Forensics environments, to the digital witness approach in order to unleash its full potential. Finally, we show the feasibility of a PRoFIT-compliant digital witness with two use cases.