Ron G. van Schyndel

Accurate positioning using long range active RFID technology to assist visually impaired people

The aim of this paper is to describe a new positioning technique to assist the blind and people with low vision to indicate their location and reach their destinationsin both indoorand outdoorenvironments. The proposedtechniqueis based on a combinationof power attenuation and a signal strength indicator (SSI) using active Radio-frequencyidentification (RFID) technology. The system uses a mobile reader with a power attenuation feature. SSI is used as a distance estimator for a short range and in combination with one of eight receiver attenuation level settings for a wider range of up to 70 meters. A Global Positioning System (GPS) works efficiently in a similar environment but is only accurate to around ten to twenty meters and does not work efficiently in indoor environments. This research produced an identification localization system which identifies various locations such as offices, laboratories, theaters and so on to assist users reach their destination of interest. It was then implemented in an indoor environment as a real empirical case study to identify laboratories based on a combined technique with a successful identification rate of around 98%. The reader has eight attenuation settings, and the geographic range of each level using various tags was calculated. Then, to evaluate reliability, 108 experiments were conducted using three tags with distances from 1 metre to 25 metres, using power settings 1 to 6. A successful detection rate of 93.5% was achieved, as well as a false positive rate of 1%. Following this, the system was implemented in a park to evaluate its ability to indicate the position of the reader among a grid of tags in an open area. A satisfactory result was achieved.

On the Properties of Non-Media Digital Watermarking: A Review of State of the Art Techniques

Over the last 25 years, there has been much work on multimedia digital watermarking. In this domain, the primary limitation to watermark strength has been in its visibility. For multimedia watermarks, invisibility is defined in human terms (that is, in terms of human sensory limitations). In this paper, we review recent developments in the non-media applications of data watermarking, which have emerged over the last decade as an exciting new sub-domain. Since by definition, the intended receiver should be able to detect the watermark, we have to redefine invisibility in an acceptable way that is often application-specific and thus cannot be easily generalized. In particular, this is true when the data is not intended to be directly consumed by humans. For example, a loose definition of robustness might be in terms of the resilience of a watermark against normal host data operations, and of invisibility as resilience of the data interpretation against change introduced by the watermark. In this paper, we classify the data in terms of data mining rules on complex types of data such as time-series, symbolic sequences, data streams, and so forth. We emphasize the challenges involved in non-media watermarking in terms of common watermarking properties, including invisibility, capacity, robustness, and security. With the aid of a few examples of watermarking applications, we demonstrate these distinctions and we look at the latest research in this regard to make our argument clear and more meaningful. As the last aim, we look at the new challenges of digital watermarking that have arisen with the evolution of big data.

Fingerprint image watermarking approach using DTCWT without corrupting minutiae

This paper proposes a new digital watermarking technique for fingerprint images using the Dual-Tree Complex Wavelet Transform (DTCWT). The watermark is embedded into the real and imaginary parts of the DTCWT wavelet coefficients. This work focuses on the study of watermarking techniques for fingerprint images that are collected from different angles without corrupting minutiae points. We investigate the effect of the watermark on the fingerprint features after the watermark embedding process. VeriFinger V5.0 is used to determine the matching score between the template and the watermarked images. The users identity is linked with the fingerprint features to add more authentication factors to the authentication process. The SHA2 hash function is used to encode the user identification number by generating the hash value and convert it into a binary image to construct the watermark data. The original fingerprint image is not required to extract watermark data. The proposed method has been tested using the CASIA fingerprint image database with 500 fingerprint images from 100 persons.

Protecting Consumer Data in Composite Web Services

The increasing number of linkable vendor-operated databases present unique threats to customer privacy and security intrusions, as personal information communicated in online transactions can be misused by the vendor. Existing privacy enhancing technologies fail in the event of a vendor operating against their stated privacy policy, leading to loss of customer privacy and security. Anonymity may not be applicable when transactions require identification of participants. We propose a service-oriented technically enforceable system that preserves privacy and security for customers transacting with untrusted online vendors. The system extends to support protection of customer privacy when multiple vendors interact in composite web services. A semi-trusted processor is introduced for safe execution of sensitive customer information in a protected environment and provides accountability in the case of disputed transactions.

Fingerprint image protection using two watermarks without corrupting minutiae

This paper proposes an approach for embedding two watermarks into fingerprint images using the Discrete Cosine Transform (DCT) algorithm. The main aim of the proposed algorithm is to add more authentication factors based on the watermark messages and to protect the ownership of the fingerprint image. Since the information used for identification or verification of a fingerprint image mainly lies in its minutiae, the introduced watermarking algorithm does not affect fingerprint features. First watermark is constructed based on a unique identification number that can identify the user. The hash function (SHA2) is applied to generate the hash value of the user identification number to encode the watermark pattern. Then, it is embedded into the fingerprint image while avoiding the minutiae locations. The second watermark is a gray image that is inserted into first watermarked image. The extraction stage does not require the original fingerprint image. We measure the affect of the watermarks on the fingerprint features based on the comparison between the total number of extracted minutiae points before and after the embedding process. The presented schema shows a high PSNR value. The robustness of the introduced technique has been tested against Gaussian and Salt & Pepper attacks.

In the shadows we trust: A secure aggregation tolerant watermark for data streams

In many applications such as sensor networks, e-healthcare and environmental monitoring, data is continuously streamed and combined from multiple resources in order to make decisions based on the aggregated data streams. One major concern in these applications is assuring high trustworthiness of the aggregated data stream for correct decision-making. For example, an adversary may compromise a few data-sources and introduce false data into the aggregated data-stream and cause catastrophic consequences. In this work, we propose a novel method for verifying data integrity by embedding several signature codes within data streams known as digital watermarking. Therefore, the integrity of the data streams can be verified by decoding the embedded signatures even as the data go through multiple stages of aggregation process. Although the idea of secure data aggregation based on digital watermarking has been explored before, we aim to improve the efficiency of the scheme by examining several signature codes that could also decrease the watermark detection complexity. This is achieved by simultaneous embedding of several shifted watermark patterns into aggregated data stream, such that the contribution of each data-source is hidden in the relative shifts of the patterns. We, also, derive conditions to preserve the main statistical properties of data-streams prior to the embedding procedure. Therefore, we can guarantee that the embedding procedure does not compromise the usability of data streams for any operations that depends on these statistical characteristics. The simulation results show that the embedded watermarks can successfully be recovered with high confidence if proper hiding codes are chosen.

Safe trajectory estimation at a pedestrian crossing to assist visually impaired people

The aim of this paper is to present a service for blind and people with low vision to assist them to cross the street independently. The presented approach provides the user with significant information such as detection of pedestrian crossing signal from any point of view, when the pedestrian crossing signal light is green, the detection of dynamic and fixed obstacles, predictions of the movement of fellow pedestrians and information on objects which may intersect his path. Our approach is based on capturing multiple frames using a depth camera which is attached to a users headgear. Currently a testbed system is built on a helmet and is connected to a laptop in the users backpack. In this paper, we discussed efficiency of using Speeded-Up Robust Features (SURF) algorithm for object recognition for purposes of blind people assistance. The system predicts the movement of objects of interest to provide the user with information on the safest path to navigate and information on the surrounding area. Evaluation of this approach on real sequence video frames provides 90% of human detection and more than 80% for recognition of other related objects.

M-Identity and its authentication protocol for secure mobile commerce applications

Mobile commerce (m-commerce) delivers value-added services to customers and creates new market opportunities. However, establishing a secure m-commerce platform that offers high level of service can be challenging. This paper proposes a concept of m-identity targeted at control the access of involved parties in an m-commerce transaction. M-identity includes both identities of a user and his/her bound mobile device which is defined as a users biometric feature(s) taken by his/her bound mobile camera. As an additional factor of authentication, a watermark is embedded in the captured biometric images. The embedding key of the watermark is a shared secret between mobile device and central server. Then an m-identity authentication (MA) protocol is proposed. M-identity merges mobile device identity into biometrics images. Only the genuine owner whose biometric information captured by his/her bound mobile device can pass m-identity authentication. Combined with the watermark, this makes a 2 ½ factor authentication process. Fingerprint biometrics taken with the mobile camera is used as an example to show how MA protocol works.

A Shape-Based Vector Watermark for Digital Mapping

Digital vector maps are an expensive commodity. Like any digital data, they are also very easy to copy. Piracy (or unauthorised reselling) of maps will become increasingly common in the future. This project looks at embedding a hidden message or watermark in a digital map so that its original authorship can be ascertained. This information enables a 3rd party to verify a sellers rights to the map and aid in the resolution of copyright disputes. Some other vector watermarking schemes, look at vector maps as a cloud of coordinates, to be perturbed in some way that is independent of actual usage. These papers generally do not discuss how large a subset of the map is needed to reliably retain the watermark. Instead, we concentrate on watermarking map feature lines, so that feature extraction from a watermarked vector map may not necessarily compromise watermark integrity.

X3D-UML: 3D UML State Machine Diagrams

X3D-UML utilises X3D (eXtensible 3D) to enable standards-based advanced 3D UML visualisations. Using X3D-UML, 3D UML State Machine Diagrams have been evaluated against actual user tasks and data, using the Sequential Evaluation methodology. The results of User Task Analysis, Heuristic Evaluation and Formative Evaluation phases provide clear evidence that the use of UML extended with 3D is a practical solution for visualising complex system behaviour. RoseRT model metrics show between 56%-90% of state machine diagram work would benefit from such 3D UML extensions; hence the 3D improvement can deliver considerable benefit to organisations.