Information Security and Privacy : Proceedings of the 9th Australasian Conference, ACISP 2004, Sydney, Australia, July 13-15, 2004.

Preface The 9th Australasian Conference on Information Security and Privacy (ACISP 2004) was held in Sydney, 13–15 July, 2004. The conference was sponsored by the Centre for Advanced Computing – Algorithms and Cryptography (ACAC), Information and Networked Security Systems Research (INSS), Macquarie University and the Australian Computer Society. The aims of the conference are to bring together researchers and practitioners working in areas of information security and privacy from universities, industry and government sectors. The conference program covered a range of aspects including cryptography, cryptanalysis, systems and network security. The program committee accepted 41 papers from 195 submissions. The reviewing process took six weeks and each paper was carefully evaluated by at least three members of the program committee. We appreciate the hard work of the members of the program committee and external referees who gave many hours of their valuable time. Of the accepted papers, there were nine from Korea, six from Australia, five each from Japan and the USA, three each from China and Singapore, two each from Canada and Switzerland, and one each from Belgium, France, Germany, Taiwan, The Netherlands and the UK. All the authors, whether or not their papers were accepted, made valued contributions to the conference. In addition to the contributed papers, Dr Arjen Lenstra gave an invited talk, entitled Likely and Unlikely Progress in Factoring. This year the program committee introduced the Best Student Paper Award. The winner of the prize for the Best Student Paper was Yan-Cheng Chang from Harvard University for his paper Single Database Private Information Retrieval with Logarithmic Communication. We would like to thank all the people involved in organizing this conference. In particular we would like to thank members of the organizing committee for their time and efforts, Andrina Brennan, Vijayakrishnan Pasupathinathan, Hartono Kurnio, Cecily Lenton, and members from ACAC and INSS.

Medical Data Access Accountability in EHR Systems, A Practical Perspective

The world has experienced a large increase in the amount of available data. Therefore, it requires better and more specialized tools for data storage and retrieval and information privacy. Recently Electronic Health Record (EHR) Systems have emerged to fulfill this need in health systems. They play an important role in medicine by granting access to information that can be used in medical diagnosis. Traditional systems have a focus on the storage and retrieval of this information, usually leaving issues related to privacy in the background. Doctors and patients may have different objectives when using an EHR system: patients try to restrict sensible information in their medical records to avoid misuse information while doctors want to see as much information as possible to ensure a correct diagnosis. One solution to this dilemma is the Accountable e-Health model, an access protocol model based in the Information Accountability Protocol. In this model patients are warned when doctors access their restricted data. They also enable a non-restrictive access for authenticated doctors. In this work we use FluxMED, an EHR system, and augment it with aspects of the Information Accountability Protocol to address these issues. The Implementation of the Information Accountability Framework (IAF) in FluxMED provides ways for both patients and physicians to have their privacy and access needs achieved. Issues related to storage and data security are secured by FluxMED, which contains mechanisms to ensure security and data integrity. The effort required to develop a platform for the management of medical information is mitigated by the FluxMED's workflow-based architecture: the system is flexible enough to allow the type and amount of information being altered without the need to change in your source code.

Reconfiguring agriculture through the relocation of production systems for water, environment and food security under climate change

The prospect of climate change has revived both fears of food insecurity and its corollary, market opportunities for agricultural production. In Australia, with its long history of state-sponsored agricultural development, there is renewed interest in the agricultural development of tropical and sub-tropical northern regions. Climate projections suggest that there will be less water available to the main irrigation systems of the eastern central and southern regions of Australia, while net rainfall could be sustained or even increase in the northern areas. Hence, there could be more intensive use of northern agricultural areas, with the relocation of some production of economically important commodities such as vegetables, rice and cotton. The problem is that the expansion of cropping in northern Australia has been constrained by agronomic and economic considerations. The present paper examines the economics, at both farm and regional level, of relocating some cotton production from the east-central irrigation areas to the north where there is an existing irrigation scheme together with some industry and individual interest in such relocation. Integrated modelling and expert knowledge are used to examine this example of prospective climate change adaptation. Farm-level simulations show that without adaptation, overall gross margins will decrease under a combination of climate change and reduction in water availability. A dynamic regional Computable General Equilibrium model is used to explore two scenarios of relocating cotton production from south east Queensland, to sugar-dominated areas in northern Queensland. Overall, an increase in real economic output and real income was realized when some cotton production was relocated to sugar cane fallow land/new land. There were, however, large negative effects on regional economies where cotton production displaced sugar cane. It is concluded that even excluding the agronomic uncertainties, which are not examined here, there is unlikely to be significant market-driven relocation of cotton production.

Relay Selection and Data Transmission Throughput Tradeoff in Cooperative Systems

A common and practical paradigm in cooperative communications is the use of a dynamically selected 'best' relay to decode and forward information from a source to a destination. Such a system consists of two core phases: a relay selection phase, in which the system expends resources to select the best relay, and a data transmission phase, in which it uses the selected relay to forward data to the destination. In this paper, we study and optimize the trade-off between the selection and data transmission phase durations. We derive closed-form expressions for the overall throughput of a non-adaptive system that includes the selection phase overhead, and then optimize the selection and data transmission phase durations. Corresponding results are also derived for an adaptive system in which the relays can vary their transmission rates. Our results show that the optimal selection phase overhead can be significant even for fast selection algorithms. Furthermore, the optimal selection phase duration depends on the number of relays and whether adaptation is used.

Joint Approximately Sparse Channel Estimation and Data Detection in OFDM Systems Using Sparse Bayesian Learning

It is well known that the impulse response of a wide-band wireless channel is approximately sparse, in the sense that it has a small number of significant components relative to the channel delay spread. In this paper, we consider the estimation of the unknown channel coefficients and its support in OFDM systems using a sparse Bayesian learning (SBL) framework for exact inference. In a quasi-static, block-fading scenario, we employ the SBL algorithm for channel estimation and propose a joint SBL (J-SBL) and a low-complexity recursive J-SBL algorithm for joint channel estimation and data detection. In a time-varying scenario, we use a first-order autoregressive model for the wireless channel and propose a novel, recursive, low-complexity Kalman filtering-based SBL (KSBL) algorithm for channel estimation. We generalize the KSBL algorithm to obtain the recursive joint KSBL algorithm that performs joint channel estimation and data detection. Our algorithms can efficiently recover a group of approximately sparse vectors even when the measurement matrix is partially unknown due to the presence of unknown data symbols. Moreover, the algorithms can fully exploit the correlation structure in the multiple measurements. Monte Carlo simulations illustrate the efficacy of the proposed techniques in terms of the mean-square error and bit error rate performance.

Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach

The impulse response of wireless channels between the N-t transmit and N-r receive antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), i.e., NtNt the channels have a small number of significant paths relative to the channel delay spread and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wireless channels are also group approximately cluster-sparse (gac-sparse), i.e., every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this paper, we cast the problem of estimating the ga-sparse and gac-sparse block-fading and time-varying channels in the sparse Bayesian learning (SBL) framework and propose a bouquet of novel algorithms for pilot-based channel estimation, and joint channel estimation and data detection, in MIMO-OFDM systems. The proposed algorithms are capable of estimating the sparse wireless channels even when the measurement matrix is only partially known. Further, we employ a first-order autoregressive modeling of the temporal variation of the ga-sparse and gac-sparse channels and propose a recursive Kalman filtering and smoothing (KFS) technique for joint channel estimation, tracking, and data detection. We also propose novel, parallel-implementation based, low-complexity techniques for estimating gac-sparse channels. Monte Carlo simulations illustrate the benefit of exploiting the gac-sparse structure in the wireless channel in terms of the mean square error (MSE) and coded bit error rate (BER) performance.

The search for gravitational waves from the coalescence of black hole binary systems in data from the LIGO and Virgo detectors. Or: A dark walk through a random forest

The LIGO and Virgo gravitational-wave observatories are complex and extremely sensitive strain detectors that can be used to search for a wide variety of gravitational waves from astrophysical and cosmological sources. In this thesis, I motivate the search for the gravitational wave signals from coalescing black hole binary systems with total mass between 25 and 100 solar masses. The mechanisms for formation of such systems are not well-understood, and we do not have many observational constraints on the parameters that guide the formation scenarios. Detection of gravitational waves from such systems — or, in the absence of detection, the tightening of upper limits on the rate of such coalescences — will provide valuable information that can inform the astrophysics of the formation of these systems. I review the search for these systems and place upper limits on the rate of black hole binary coalescences with total mass between 25 and 100 solar masses. I then show how the sensitivity of this search can be improved by up to 40% by the the application of the multivariate statistical classifier known as a random forest of bagged decision trees to more effectively discriminate between signal and non-Gaussian instrumental noise. I also discuss the use of this classifier in the search for the ringdown signal from the merger of two black holes with total mass between 50 and 450 solar masses and present upper limits. I also apply multivariate statistical classifiers to the problem of quantifying the non-Gaussianity of LIGO data. Despite these improvements, no gravitational-wave signals have been detected in LIGO data so far. However, the use of multivariate statistical classification can significantly improve the sensitivity of the Advanced LIGO detectors to such signals.

Resilient livelihoods and food security in coastal aquatic agricultural systems: Investing in transformational change

Aquatic agricultural systems (AAS) are diverse production and livelihood systems where families cultivate a range of crops, raise livestock, farm or catch fish, gather fruits and other tree crops, and harness natural resources such as timber, reeds, and wildlife. Aquatic agricultural systems occur along freshwater floodplains, coastal deltas, and inshore marine waters, and are characterized by dependence on seasonal changes in productivity, driven by seasonal variation in rainfall, river flow, and/or coastal and marine processes. Despite this natural productivity, the farming, fishing, and herding communities who live in these systems are among the poorest and most vulnerable in their countries and regions. This report provides an overview of the scale and scope of development challenges in coastal aquatic agricultural systems, their significance for poor and vulnerable communities, and the opportunities for partnership and investment that support efforts of these communities to secure resilient livelihoods in the face of multiple risks.

Food and nutrition security in Solomon Islands

This report is a literature review on Food and Nutrition Security in Solomon Islands, based on data from surveys conducted by Solomon Islands National Statistical Office, as well as from national and international organizations working in Solomon Islands. The purpose of the report is to present information outlining the current food and nutrition situation in Solomon Islands before implementation of the CGIAR Research Program on Aquatic Agricultural Systems (AAS), led by WorldFish. The aim of the AAS program is to enhance production in natural freshwater and/or coastal ecosystems to improve household livelihood, including income and food security. This report summarizes national statistics and also focuses in more detail on a subset of provinces: Guadalcanal, Malaita and Western. In 2012, the AAS program was rolled out in Guadalcanal, Central and Malaita Provinces, designated the Central Hub. In 2013, roll out is beginning in the Western Hub (Western and Isabel Provinces). The priority province for the Central Hub has been identified as Malaita.

Food and nutrition security in Timor-Leste

This report is a literature review on Food and Nutrition Security in Timor-Leste based on data from surveys conducted by the Timor-Leste National Statistics Directorate, as well as from national and international organizations working in Timor-Leste. This review was supported by the Australian Centre for International Agricultural Research (ACIAR)-funded project “Strategy for Investment in Fisheries in East Timor”. This report describes the current food and nutrition situation in Timor-Leste for the purpose of planning and implementing interventions aimed at improving food and nutrition security, especially within aquatic agricultural systems. The potential role of aquaculture in improving food and nutrition security is considered, with reference to the recently endorsed Timor-Leste National Aquaculture Development Strategy (2012-2030) developed by the National Directorate of Fisheries and Agriculture, Ministry of Agriculture and Fisheries.

Instruments and data aquisition systems for research on trawl nets

Catching methods and ways to improve them have been engaging the attention of fishermen from time immemorial. This was done mostly by trial and error methods, as most of the earlier investigations were primarily directed towards solution of biological problems related to fisheries. In recent years several fisheries laboratories have taken up studies on the working principles of many gears such as trawls, gill nets, round haul nets etc. with the aid of instruments developed for the purpose. The purpose of this article is to review the progress made in this field and in the development of telemetering instruments and continuous data acquisition systems.

Performance and power dissipation comparisons between 28 Gb/s NRZ, PAM, CAP and optical OFDM systems for data communication applications

Theoretical investigations have been carried out to analyze and compare the link power budget and power dissipation of non-return-to-zero (NRZ), pulse amplitude modulation-4 (PAM-4), carrierless amplitude and phase modulation-16 (CAP-16) and 16-quadrature amplitude modulation-orthogonal frequency division multiplexing (16-QAM-OFDM) systems for data center interconnect scenarios. It is shown that for multimode fiber (MMF) links, NRZ modulation schemes with electronic equalization offer the best link power budget margins with the least power dissipation for short transmission distances up to 200 m; while OOFDM is the only scheme which can support a distance of 300 m albeit with power dissipation as high as 4 times that of NRZ. For short single mode fiber (SMF) links, all the modulation schemes offer similar link power budget margins for fiber lengths up to 15 km, but NRZ and PAM-4 are preferable due to their system simplicity and low power consumption. For lengths of up to 30 km, CAP-16 and OOFDM are required although the schemes consume 2 and 4 times as much power respectively compared to that of NRZ. OOFDM alone allows link operation up to 35 km distances. © 1983-2012 IEEE.

Optimising contributions of goat farming to household economic success and food security in three production systems in Ethiopia

The study aims to analyse factors affecting contributions of goat farming to household economic success and food security in three goat production systems of Ethiopia. A study was conducted in three districts of Ethiopia representing arid agro-pastoral (AAP), semi-arid agro-pastoral (SAAP) and highland mixed crop-livestock (HMCL) systems involving 180 goat keeping households. Gross margin (GM) and net benefit (NB1 and NB2) were used as indicators of economic success of goat keeping. NB1 includes in-kind benefits of goats (consumption and manure), while NB2 additionally constitutes intangible benefits (insurance and finance). Household dietary diversity score (HDDS) was used as a proxy indicator of food security. GM was significantly affected by an off-take rate and flock size interaction (P<0.001). The increment of GM due to increased off-take rate was more prominent for farmers with bigger flocks. Interaction between flock size and production system significantly (P<0.001) affected both NB1 and NB2. The increment of NB1 and NB2 by keeping larger flocks was higher in AAP system, due to higher in-kind and intangible benefits of goats in this system. Effect of goat flock size as a predictor of household dietary diversity was not significant (P>0.05). Nevertheless, a significant positive correlation (P<0.05) was observed between GM from goats and HDDS in AAP system, indicating the indirect role of goat production for food security. The study indicated that extent of utilising tangible and intangible benefits of goats varied among production systems and these differences should be given adequate attention in designing genetic improvement programs.