Spaceprint: a Mobility-based Fingerprinting Scheme for Public Spaces

In this paper, we address the problem of how automated situation-awareness can be achieved by learning real-world situations from ubiquitously generated mobility data. Without semantic input about the time and space where situations take place, this turns out to be a fundamental challenging problem. Uncertainties also introduce technical challenges when data is generated in irregular time intervals, being mixed with noise, and errors. Purely relying on temporal patterns observable in mobility data, in this paper, we propose Spaceprint, a fully automated algorithm for finding the repetitive pattern of similar situations in spaces. We evaluate this technique by showing how the latent variables describing the category, and the actual identity of a space can be discovered from the extracted situation patterns. Doing so, we use different real-world mobility datasets with data about the presence of mobile entities in a variety of spaces. We also evaluate the performance of this technique by showing its robustness against uncertainties

Towards a Versatile Problem Diagnosis Infrastructure for LargeWireless Sensor Networks

In this position paper, we address the issue of durable maintenance of a wireless sensor network, which will be crucial if the vision of large, long-lived sensornets is to become reality. Durable maintenance requires tools for diagnosing and fixing occurring problems, which can range from internode connectivity losses, to time synchronization problems, to software bugs. While there are solutions for fixing problems, an appropriate diagnostic infrastructure is essentially still lacking. We argue that diagnosing a sensornet application requires the ability to dynamically and temporarily extend the application on a selected group of nodes with virtually any functionality. We motivate this claim based on deployment experiences to date and propose a highly nonintrusive solution to dynamically extending a running application on a resource-constrained sensor node

Simplified Distributed Programming with Micro Objects

Developing large-scale distributed applications can be a daunting task. object-based environments have attempted to alleviate problems by providing distributed objects that look like local objects. We advocate that this approach has actually only made matters worse, as the developer needs to be aware of many intricate internal details in order to adequately handle partial failures. The result is an increase of application complexity. We present an alternative in which distribution transparency is lessened in favor of clearer semantics. In particular, we argue that a developer should always be offered the unambiguous semantics of local objects, and that distribution comes from copying those objects to where they are needed. We claim that it is often sufficient to provide only small, immutable objects, along with facilities to group objects into clusters.Comment: In Proceedings FOCLASA 2010, arXiv:1007.499

LocKey:Location-Based Key Extraction from the WiFi Environment in the User′s Vicinity

We investigate extracting persistent information from semi-volatile signals in the user’s vicinity to extend existing authentication factors. We use WiFi as a representative of semi-volatile signals, as WiFi signals and WiFi receiver hardware are ubiquitous. WiFi hardware is mostly bound to a physical location and WiFi signals are semi-volatile by nature. By comparing different locations, we confirm our expectation that location-specific information is present in the received WiFi signals. In this work, we study whether and how this information can be transformed to satisfy the following properties of a cryptographic key so that we can use it as an extension of an authentication factor: it must be uniformly random, contain sufficient entropy, and the information must be secret. We further discuss two primary use cases in the authentication domain: using extracted low-entropy information (48 bits) for password hardening and using extracted high-entropy information (128 bits and 256 bits) as a location-specific key. Using the WiFi-signal composition as an authentication component increases the usability, introduces the factor of ‘location’ to the authentication claims, and introduces another layer of defense against key or password extraction attacks. Next to these advantages, it has intrinsic limitations, such as the need for the receiver to be in proximity to the signal and the reliance on WiFi signals, which are outside the user’s control. Despite these challenges, using signals in the proximity of a user works in situations with a fallback routine in place while increasing usability and transparency. LocKey is capable to extract low-entropy information at all locations measured, and high-entropy from 68% locations for 128-bit keys (48% of the locations respectively for 256-bit keys). We further show that with an initial measurement time of at most five minutes, we can reconstruct the key in at least 75% of the cases in less than 15, 30, and 40 s depending on the desired key strength

The Measurable Environment as Nonintrusive Authentication Factor on the Example of WiFi Beacon Frames

We explore a method to fingerprint a location in terms of its measurable environment to create an authentication factor that is nonintrusive in the sense that a user is not required to engage in the authentication process actively. Exemplary, we describe the measurable environment by beacon frames from the WiFi access points in the user’s proximity. To use the measurable environment for authentication, measurements must be sufficiently discriminating between locations and similar at the same location. An authentication factor built from the measurable environment allows us to describe a user’s location in terms of measurable signals. Describing a location in terms of its measurable signals implies that we do not require an actual geographical mapping of the user’s location; comparing the measured signals is sufficient to create a location-based authentication factor. Only recognizing an earlier observed environment distinguishes our approach from other location-based authentication factors. We elaborate on using signals in the user’s environment in the background without user involvement to create a privacy-preserving but nonintrusive authentication factor suitable for integration into existing multi-factor authentication schemes.</p

RoomKey:Extracting a Volatile Key with Information from the Local WiFi Environment Reconstructable Within a Designated Area

We present a WiFi signal-based, volatile key extraction system called RoomKey. We derive a room’s key by creating a deterministic key from the ever-changing WiFi environment and investigating the extraction capabilities of a designated area. RoomKey uses wireless beacon frames as a component, which we combine with a strong random key to generate and reconstruct the same volatile key in the room. We provide an exemplary use case using RoomKeyas an authentication factor using the location-specific WiFi environment as an authentication claim. We identified and solved two problems in using location as an authentication factor: location being sensitive to privacy and the location of a user constantly changing. We mitigate privacy concerns by recognizing a particular location without the need to localize its precise geographical coordinates. To overcome the problem of location change, we restrict locations to work environments for laptop usage and allow a per-location-predetermined, designated area (e.g., a room). With the concept RoomKey, we demonstrate the potential of including environmental WiFi measurements for volatile key extraction and show the possibility of creating location-aware and privacy-preserving authentication systems for continuous authentication and adaptive security measures.</p

The Globe Infrastructure Directory Service

To implement adaptive replication strategies for Web documents, we have developed a wide area resource management system. This system allows servers to be managed on a local and global level. On a local level the system manages information about the resources and services provided by the servers, while on a global level the system allows servers to be searched for, added to, and removed from the system. As part of the system, and also in order to implement adaptive replication strategies, we introduce a hierarchical location representation for network elements such as servers, objects, and clients. This location representation allows us to easily and efficiently find and group network elements based on their location in a worldwide network. Our resource management system can be implemented using standard Internet technologies and has a broader range of applications besides making adaptive replication strategies possible for Web documents