If it's encrypted it's secure! The viability of US state-based encryption exemptions

US state-based data breach notification laws have unveiled serious corporate and government failures regarding the security of personal information. These laws require organisations to notify persons who may be affected by an unauthorized acquisition of their personal information. Safe harbours to notification exist if personal information is encrypted. Three types of safe harbour have been identified in the literature: exemptions, rebuttable presumptions and factors. The underlying assumption of exemptions is that encrypted personal information is secure and therefore unauthorized access does not pose a risk. However, the viability of this assumption is questionable when examined against data breaches involving encrypted information and the demanding practical requirements of effective encryption management. Recent recommendations by the Australian Law Reform Commission (ALRC) would amend the Privacy Act 1988 (Cth) to implement a data breach scheme that includes a different type of safe harbour, factor based analysis. The authors examine the potential capability of the ALRC’s proposed encryption safe harbour in relation to the US experience at the state legislature level.

Augmenting RatSLAM using FAB-MAP-based visual data association

This paper investigates the use of the FAB-MAP appearance-only SLAM algorithm as a method for performing visual data association for RatSLAM, a semi-metric full SLAM system. While both systems have shown the ability to map large (60-70km) outdoor locations of approximately the same scale, for either larger areas or across longer time periods both algorithms encounter difficulties with false positive matches. By combining these algorithms using a mapping between appearance and pose space, both false positives and false negatives generated by FAB-MAP are significantly reduced during outdoor mapping using a forward-facing camera. The hybrid FAB-MAP-RatSLAM system developed demonstrates the potential for successful SLAM over large periods of time.

Analysis and detection of cognitive load and frustration in drivers' speech

Non-driving related cognitive load and variations of emotional state may impact a driver’s capability to control a vehicle and introduces driving errors. Availability of reliable cognitive load and emotion detection in drivers would benefit the design of active safety systems and other intelligent in-vehicle interfaces. In this study, speech produced by 68 subjects while driving in urban areas is analyzed. A particular focus is on speech production differences in two secondary cognitive tasks, interactions with a co-driver and calls to automated spoken dialog systems (SDS), and two emotional states during the SDS interactions - neutral/negative. A number of speech parameters are found to vary across the cognitive/emotion classes. Suitability of selected cepstral- and production-based features for automatic cognitive task/emotion classification is investigated. A fusion of GMM/SVM classifiers yields an accuracy of 94.3% in cognitive task and 81.3% in emotion classification.

Exploring visual features through Gabor representations for facial expression detection

Gabor representations have been widely used in facial analysis (face recognition, face detection and facial expression detection) due to their biological relevance and computational properties. Two popular Gabor representations used in literature are: 1) Log-Gabor and 2) Gabor energy filters. Even though these representations are somewhat similar, they also have distinct differences as the Log-Gabor filters mimic the simple cells in the visual cortex while the Gabor energy filters emulate the complex cells, which causes subtle differences in the responses. In this paper, we analyze the difference between these two Gabor representations and quantify these differences on the task of facial action unit (AU) detection. In our experiments conducted on the Cohn-Kanade dataset, we report an average area underneath the ROC curve (A`) of 92.60% across 17 AUs for the Gabor energy filters, while the Log-Gabor representation achieved an average A` of 96.11%. This result suggests that small spatial differences that the Log-Gabor filters pick up on are more useful for AU detection than the differences in contours and edges that the Gabor energy filters extract.

Temporal-based support vector machines for facial expression recognition

When classifying a signal, ideally we want our classifier to trigger a large response when it encounters a positive example and have little to no response for all other examples. Unfortunately in practice this does not occur with responses fluctuating, often causing false alarms. There exists a myriad of reasons why this is the case, most notably not incorporating the dynamics of the signal into the classification. In facial expression recognition, this has been highlighted as one major research question. In this paper we present a novel technique which incorporates the dynamics of the signal which can produce a strong response when the peak expression is found and essentially suppresses all other responses as much as possible. We conducted preliminary experiments on the extended Cohn-Kanade (CK+) database which shows its benefits. The ability to automatically and accurately recognize facial expressions of drivers is highly relevant to the automobile. For example, the early recognition of “surprise” could indicate that an accident is about to occur; and various safeguards could immediately be deployed to avoid or minimize injury and damage. In this paper, we conducted initial experiments on the extended Cohn-Kanade (CK+) database which shows its benefits.

Public awareness of “green” and “energy efficient” residential property : an empirical survey based on data from New Zealand

Purpose – The purpose of this paper is to examine the buyer awareness and acceptance of environmental and energy efficiency measures in the New Zealand residential property markets. This study aims to provide a greater understanding of consumer behaviour in the residential property market in relation to green housing issues ---------- Design/methodology/approach – The paper is based on an extensive survey of Christchurch real estate offices and was designed to gather data on the factors that were considered important by buyers in the residential property market. The survey was designed to allow these factors to be analysed on a socio-economic basis and to compare buyer behaviour based on property values. ---------- Findings – The results show that regardless of income levels, buyers still consider that the most important factor in the house purchase decision is the location of the property and price. Although the awareness of green housing issues and energy efficiency in housing is growing in the residential property market, it is only a major consideration for young and older buyers in the high income brackets and is only of some importance for all other buyer sectors of the residential property market. Many of the voluntary measures introduced by Governments to improve the energy efficiency of residential housing are still not considered important by buyers, indicating that a more mandatory approach may have to be undertaken to improve energy efficiency in the established housing market, as these measures are not valued by the buyer. ---------- Originality/value – The paper confirms the variations in real estate buyer behaviour across the full range of residential property markets and the acceptance and awareness of green housing issues and measures. These results would be applicable to most established and transparent residential property markets.

Performance analysis of unified enterprise application security framework

Unified Enterprise application security is a new emerging approach for providing protection against application level attacks. Conventional application security approach that consists of embedding security into each critical application leads towards scattered security mechanism that is not only difficult to manage but also creates security loopholes. According to the CSIIFBI computer crime survey report, almost 80% of the security breaches come from authorized users. In this paper, we have worked on the concept of unified security model, which manages all security aspect from a single security window. The basic idea is to keep business functionality separate from security components of the application. Our main focus was on the designing of frame work for unified layer which supports single point of policy control, centralize logging mechanism, granular, context aware access control, and independent from any underlying authentication technology and authorization policy.

TCP-DR an effective protocol for infrastructure based wireless networks

TCP is a dominant protocol for consistent communication over the internet. It provides flow, congestion and error control mechanisms while using wired reliable networks. Its congestion control mechanism is not suitable for wireless links where data corruption and its lost rate are higher. The physical links are transparent from TCP that takes packet losses due to congestion only and initiates congestion handling mechanisms by reducing transmission speed. This results in wasting already limited available bandwidth on the wireless links. Therefore, there is no use to carry out research on increasing bandwidth of the wireless links until the available bandwidth is not optimally utilized. This paper proposed a hybrid scheme called TCP Detection and Recovery (TCP-DR) to distinguish congestion, corruption and mobility related losses and then instructs the data sending host to take appropriate action. Therefore, the link utilization is optimal while losses are either due to high bit error rate or mobility.

Dynamic analysis of on-board mass data to determine tampering in heavy vehicle on-board mass systems

Transport Certification Australia Limited, jointly with the National Transport Commission, has undertaken a project to investigate the feasibility of on-board mass monitoring (OBM) devices for regulatory purposes. OBM increases jurisdictional confidence in operational heavy vehicle compliance. This paper covers technical issues regarding potential use of dynamic data from OBM systems to indicate that tampering has occurred. Tamper-evidence and accuracy of current OBM systems needed to be determined before any regulatory schemes were put in place for its use. Tests performed to determine potential for, and ease of, tampering. An algorithm was developed to detect tamper events. Its results are detailed.

Fixed argument pairings

A common scenario in many pairing-based cryptographic protocols is that one argument in the pairing is fixed as a long term secret key or a constant parameter in the system. In these situations, the runtime of Miller's algorithm can be significantly reduced by storing precomputed values that depend on the fixed argument, prior to the input or existence of the second argument. In light of recent developments in pairing computation, we show that the computation of the Miller loop can be sped up by up to 37 if precomputation is employed, with our method being up to 19.5 faster than the previous precomputation techniques.

Using accelerometer, high sample rate GPS and magnetometer data to develop a cattle movement and behaviour model

The study described in this paper developed a model of animal movement, which explicitly recognised each individual as the central unit of measure. The model was developed by learning from a real dataset that measured and calculated, for individual cows in a herd, their linear and angular positions and directional and angular speeds. Two learning algorithms were implemented: a Hidden Markov model (HMM) and a long-term prediction algorithm. It is shown that a HMM can be used to describe the animal's movement and state transition behaviour within several “stay” areas where cows remained for long periods. Model parameters were estimated for hidden behaviour states such as relocating, foraging and bedding. For cows’ movement between the “stay” areas a long-term prediction algorithm was implemented. By combining these two algorithms it was possible to develop a successful model, which achieved similar results to the animal behaviour data collected. This modelling methodology could easily be applied to interactions of other animal species.

Poster Abstract : A sensor network for compression and streaming of GPS trajectory data

We present the design and deployment results for PosNet - a large-scale, long-duration sensor network that gathers summary position and status information from mobile nodes. The mobile nodes have a fixed-sized memory buffer to which position data is added at a constant rate, and from which data is downloaded at a non-constant rate. We have developed a novel algorithm that performs online summarization of position data within the buffer, where the algorithm naturally accommodates data input and output rate mismatch, and also provides a delay-tolerant approach to data transport. The algorithm has been extensively tested in a large-scale long-duration cattle monitoring and control application.

ERTP : Energy-efficient and reliable transport protocol for data streaming in wireless sensor networks

Emerging data streaming applications in Wireless Sensor Networks require reliable and energy-efficient Transport Protocols. Our recent Wireless Sensor Network deployment in the Burdekin delta, Australia, for water monitoring [T. Le Dinh, W. Hu, P. Sikka, P. Corke, L. Overs, S. Brosnan, Design and deployment of a remote robust sensor network: experiences from an outdoor water quality monitoring network, in: Second IEEE Workshop on Practical Issues in Building Sensor Network Applications (SenseApp 2007), Dublin, Ireland, 2007] is one such example. This application involves streaming sensed data such as pressure, water flow rate, and salinity periodically from many scattered sensors to the sink node which in turn relays them via an IP network to a remote site for archiving, processing, and presentation. While latency is not a primary concern in this class of application (the sampling rate is usually in terms of minutes or hours), energy-efficiency is. Continuous long-term operation and reliable delivery of the sensed data to the sink are also desirable. This paper proposes ERTP, an Energy-efficient and Reliable Transport Protocol for Wireless Sensor Networks. ERTP is designed for data streaming applications, in which sensor readings are transmitted from one or more sensor sources to a base station (or sink). ERTP uses a statistical reliability metric which ensures the number of data packets delivered to the sink exceeds the defined threshold. Our extensive discrete event simulations and experimental evaluations show that ERTP is significantly more energyefficient than current approaches and can reduce energy consumption by more than 45% when compared to current approaches. Consequently, sensor nodes are more energy-efficient and the lifespan of the unattended WSN is increased.

An empirical study of data collection protocols for wireless sensor networks

In the past few years, numerous data collection protocols have been developed for wireless sensor networks (WSNs). However, there has been no comparison of their relative performance in realistic environments. Here we report the results of an empirical study using a Fleck3 sensor network testbed for four different data collection protocols: One phase pull Directed Diffusion (DD), Expected Number of Transmissions (ETX), ETX with explicit acknowledgment (ETX-eAck), and ETX with implicit acknowledgment (ETX-iAck). Our empirical study provides useful insights for future sensor network deployments. When the required application end-to-end reliability is not strict (e.g., 70%) and link quality is good, DD and ETX are the best options because of their simplicity and low routing overhead. Both ETX-eAck and ETX-iAck achieve more than 90% end-to-end reliability when the link quality is reasonable (less than 25% packet loss). When the link quality is good, ETX-iAck introduces significantly less routing overhead (up to 50%) than ETX-eAck. However, if the radio transceiver supports variable packet length, ETX-eAck can outperform ETX-iAck when the link quality is poor. The important message from this paper is that choice of data collection protocol should come after the operating environment is understood. This understanding must include the characteristics of the radio transceiver, and link loss statistics from a long-term (across seasons and weather variation) radio survey of the site.

Data collection, storage and retrieval with an underwater sensor network

In this paper we present a novel platform for underwater sensor networks to be used for long-term monitoring of coral reefs and �sheries. The sensor network consists of static and mobile underwater sensor nodes. The nodes communicate point-to-point using a novel high-speed optical communication system integrated into the TinyOS stack, and they broadcast using an acoustic protocol integrated in the TinyOS stack. The nodes have a variety of sensing capabilities, including cameras, water temperature, and pressure. The mobile nodes can locate and hover above the static nodes for data muling, and they can perform network maintenance functions such as deployment, relocation, and recovery. In this paper we describe the hardware and software architecture of this underwater sensor network. We then describe the optical and acoustic networking protocols and present experimental networking and data collected in a pool, in rivers, and in the ocean. Finally, we describe our experiments with mobility for data muling in this network.