Preventing pollution attacks in multi-source network coding

Network coding is a method for achieving channel capacity in networks. The key idea is to allow network routers to linearly mix packets as they traverse the network so that recipients receive linear combinations of packets. Network coded systems are vulnerable to pollution attacks where a single malicious node floods the network with bad packets and prevents the receiver from decoding correctly. Cryptographic defenses to these problems are based on homomorphic signatures and MACs. These proposals, however, cannot handle mixing of packets from multiple sources, which is needed to achieve the full benefits of network coding. In this paper we address integrity of multi-source mixing. We propose a security model for this setting and provide a generic construction.

Multi-party computation with conversion of secret sharing

Classical results in unconditionally secure multi-party computation (MPC) protocols with a passive adversary indicate that every n-variate function can be computed by n participants, such that no set of size t < n/2 participants learns any additional information other than what they could derive from their private inputs and the output of the protocol. We study unconditionally secure MPC protocols in the presence of a passive adversary in the trusted setup (‘semi-ideal’) model, in which the participants are supplied with some auxiliary information (which is random and independent from the participant inputs) ahead of the protocol execution (such information can be purchased as a “commodity” well before a run of the protocol). We present a new MPC protocol in the trusted setup model, which allows the adversary to corrupt an arbitrary number t < n of participants. Our protocol makes use of a novel subprotocol for converting an additive secret sharing over a field to a multiplicative secret sharing, and can be used to securely evaluate any n-variate polynomial G over a field F, with inputs restricted to non-zero elements of F. The communication complexity of our protocol is O(ℓ · n 2) field elements, where ℓ is the number of non-linear monomials in G. Previous protocols in the trusted setup model require communication proportional to the number of multiplications in an arithmetic circuit for G; thus, our protocol may offer savings over previous protocols for functions with a small number of monomials but a large number of multiplications.

An intuitive multi-touch surface and gesture based interaction for video surveillance systems

This paper discusses the idea and demonstrates an early prototype of a novel method of interacting with security surveillance footage using natural user interfaces in place of traditional mouse and keyboard interaction. Current surveillance monitoring stations and systems provide the user with a vast array of video feeds from multiple locations on a video wall, relying on the user’s ability to distinguish locations of the live feeds from experience or list based key-value pair of location and camera IDs. During an incident, this current method of interaction may cause the user to spend increased amounts time obtaining situational and location awareness, which is counter-productive. The system proposed in this paper demonstrates how a multi-touch screen and natural interaction can enable the surveillance monitoring station users to quickly identify the location of a security camera and efficiently respond to an incident.

Online self-supervised multi-instance segmentation of dynamic objects

This paper presents a method for the continuous segmentation of dynamic objects using only a vehicle mounted monocular camera without any prior knowledge of the object’s appearance. Prior work in online static/dynamic segmentation is extended to identify multiple instances of dynamic objects by introducing an unsupervised motion clustering step. These clusters are then used to update a multi-class classifier within a self-supervised framework. In contrast to many tracking-by-detection based methods, our system is able to detect dynamic objects without any prior knowledge of their visual appearance shape or location. Furthermore, the classifier is used to propagate labels of the same object in previous frames, which facilitates the continuous tracking of individual objects based on motion. The proposed system is evaluated using recall and false alarm metrics in addition to a new multi-instance labelled dataset to evaluate the performance of segmenting multiple instances of objects.

Blast response and safety evaluation of a composite column for use as key element in structural systems

This paper presents the blast response, damage mechanism and evaluation of residual load capacity of a concrete–steel composite (CSC) column using dynamic computer simulation techniques. This study is an integral part of a comprehensive research program which investigated the vulnerability of structural framing systems to catastrophic and progressive collapse under blast loading and is intended to provide design information on blast mitigation and safety evaluation of load bearing vulnerable columns that are key elements in a building. The performance of the CSC column is compared with that of a reinforced concrete (RC) column with the same dimensions and steel ratio. Results demonstrate the superior performance of the CSC column, compared to the RC column in terms of residual load carrying capacity, and its potential for use as a key element in structural systems. The procedure and results presented herein can be used in the design and safety evaluation of key elements of multi-storey buildings for mitigating the impact of blast loads.

Binary image steganographic techniques classification based on multi-class steganalysis

In this paper, we propose a new multi-class steganalysis for binary image. The proposed method can identify the type of steganographic technique used by examining on the given binary image. In addition, our proposed method is also capable of differentiating an image with hidden message from the one without hidden message. In order to do that, we will extract some features from the binary image. The feature extraction method used is a combination of the method extended from our previous work and some new methods proposed in this paper. Based on the extracted feature sets, we construct our multi-class steganalysis from the SVM classifier. We also present the empirical works to demonstrate that the proposed method can effectively identify five different types of steganography.

Multi-party computation with omnipresent adversary

Secure multi-party computation (MPC) protocols enable a set of n mutually distrusting participants P 1, ..., P n , each with their own private input x i , to compute a function Y = F(x 1, ..., x n ), such that at the end of the protocol, all participants learn the correct value of Y, while secrecy of the private inputs is maintained. Classical results in the unconditionally secure MPC indicate that in the presence of an active adversary, every function can be computed if and only if the number of corrupted participants, t a , is smaller than n/3. Relaxing the requirement of perfect secrecy and utilizing broadcast channels, one can improve this bound to t a  < n/2. All existing MPC protocols assume that uncorrupted participants are truly honest, i.e., they are not even curious in learning other participant secret inputs. Based on this assumption, some MPC protocols are designed in such a way that after elimination of all misbehaving participants, the remaining ones learn all information in the system. This is not consistent with maintaining privacy of the participant inputs. Furthermore, an improvement of the classical results given by Fitzi, Hirt, and Maurer indicates that in addition to t a actively corrupted participants, the adversary may simultaneously corrupt some participants passively. This is in contrast to the assumption that participants who are not corrupted by an active adversary are truly honest. This paper examines the privacy of MPC protocols, and introduces the notion of an omnipresent adversary, which cannot be eliminated from the protocol. The omnipresent adversary can be either a passive, an active or a mixed one. We assume that up to a minority of participants who are not corrupted by an active adversary can be corrupted passively, with the restriction that at any time, the number of corrupted participants does not exceed a predetermined threshold. We will also show that the existence of a t-resilient protocol for a group of n participants, implies the existence of a t’-private protocol for a group of n′ participants. That is, the elimination of misbehaving participants from a t-resilient protocol leads to the decomposition of the protocol. Our adversary model stipulates that a MPC protocol never operates with a set of truly honest participants (which is a more realistic scenario). Therefore, privacy of all participants who properly follow the protocol will be maintained. We present a novel disqualification protocol to avoid a loss of privacy of participants who properly follow the protocol.

The development of a simple multi-nodal tool to identify performance issues in existing commercial buildings

Australia’s building stock includes many older commercial buildings with numerous factors that impact energy performance and indoor environment quality. The built environment industry has generally focused heavily on improving physical building design elements for greater energy efficiency (such as retrofits and environmental upgrades), however there are noticeable ‘upper limits’ to performance improvements in these areas. To achieve a stepchange improvement in building performance, the authors propose that additional components need to be addressed in a whole of building approach, including the way building design elements are managed and the level of stakeholder engagement between owners, tenants and building managers. This paper focuses on the opportunities provided by this whole-of-building approach, presenting the findings of a research project undertaken through the Sustainable Built Environment National Research Centre (SBEnrc) in Australia. Researchers worked with a number of industry partners over two years to investigate issues facing stakeholders at base building and tenancy levels, and the barriers to improving building performance. Through a mixed-method, industry-led research approach, five ‘nodes’ were identified in whole-of-building performance evaluation, each with interlinking and overlapping complexities that can influence performance. The nodes cover building management, occupant experience, indoor environment quality, agreements and culture, and design elements. This paper outlines the development and testing of these nodes and their interactions, and the resultant multi-nodal tool, called the ‘Performance Nexus’ tool. The tool is intended to be of most benefit in evaluating opportunities for performance improvement in the vast number of existing low-performing building stock.

Verifiable multi-secret sharing schemes for multiple threshold access structures

A multi-secret sharing scheme allows several secrets to be shared amongst a group of participants. In 2005, Shao and Cao developed a verifiable multi-secret sharing scheme where each participant’s share can be used several times which reduces the number of interactions between the dealer and the group members. In addition some secrets may require a higher security level than others involving the need for different threshold values. Recently Chan and Chang designed such a scheme but their construction only allows a single secret to be shared per threshold value. In this article we combine the previous two approaches to design a multiple time verifiable multi-secret sharing scheme where several secrets can be shared for each threshold value. Since the running time is an important factor for practical applications, we will provide a complexity comparison of our combined approach with respect to the previous schemes.

Perceived obstacles to multi-storey timber-frame construction : an Australian study

The contemporary default materials for multi-storey buildings – namely concrete and steel – are all significant generators of carbon and the use of timber products provides a technically, economically and environmentally viable alternative. In particular, timber’s sustainability can drive increased use and subsequent evolution of the Blue economy as a new economic model. National research to date, however, indicates a resistance to the uptake of timber technologies in Australia. To investigate this further, a preliminary study involving a convenience sample of 15 experts was conducted to identify the main barriers involved in the use of timber frames in multi-storey buildings. A closed-ended questionnaire survey involving 74 experienced construction industry participants was then undertaken to rate the relative importance of the barriers. The survey confirmed the most significant barriers to be a perceived increase in maintenance costs and fire risk, together with a limited awareness of the emerging timber technologies available. It is expected that the results will benefit government and the timber industry, contributing to environmental improvement by developing strategies to increase the use of timber technologies in multi-storey buildings by countering perceived barriers in the Australian context.

Fault diagnosis of low speed bearing based on acoustic emission signal and multi-class relevance vector machine

This study presents an acoustic emission (AE) based fault diagnosis for low speed bearing using multi-class relevance vector machine (RVM). A low speed test rig was developed to simulate the various defects with shaft speeds as low as 10 rpm under several loading conditions. The data was acquired using anAEsensor with the test bearing operating at a constant loading (5 kN) andwith a speed range from20 to 80 rpm. This study is aimed at finding a reliable method/tool for low speed machines fault diagnosis based on AE signal. In the present study, component analysis was performed to extract the bearing feature and to reduce the dimensionality of original data feature. The result shows that multi-class RVM offers a promising approach for fault diagnosis of low speed machines.

A multi-genome analysis approach enables tracking of the invasion of a single Russian wheat aphid (Diuraphis noxia) clone throughout the New World

This study investigated the population genetics, demographic history and pathway of invasion of the Russian wheat aphid (RWA) from its native range in Central Asia, the Middle East and Europe to South Africa and the Americas. We screened microsatellite markers, mitochondrial DNA and endosymbiont genes in 504 RWA clones from nineteen populations worldwide. Following pathway analyses of microsatellite and endosymbiont data, we postulate that Turkey and Syria were the most likely sources of invasion to Kenya and South Africa, respectively. Furthermore, we found that one clone transferred between South Africa and the Americas was most likely responsible for the New World invasion. Finally, endosymbiont DNA was found to be a high resolution population genetic marker, extremely useful for studies of invasion over a relatively short evolutionary history time frame. This study has provided valuable insights into the factors that may have facilitated the recent global invasion by this damaging pest.

Proton-transfer and non-transfer compounds of the multi-purpose drug dapsone [4-(4-Aminophenylsulfonyl)aniline] with 3,5-dinitrosalicylic acid and 5-nitroisophthalic acid

The structures of the compounds from the reaction of the drug dapsone [4-(4-aminophenylsulfonyl)aniline] with 3,5-dinitrosalicylic acid, the salt hydrate [4-(4-aminohenylsulfonyl)anilinium 2-carboxy-4,6-dinitrophenolate monohydrate] (1) and the 1:1 adduct with 5-nitroisophthalic acid [4-(4-aminophenylsulfonyl)aniline 5-nitrobenzene-1,3-dicarboxylic acid] (2) have been determined. Crystals of 1 are triclinic, space group P-1, with unit cell dimensions a = 8.2043(3), b = 11.4000(6), c = 11.8261(6)Å, α = 110.891(5), β = 91.927(3), γ = 98.590(4)deg. and Z = 4. Compound 2 is orthorhombic, space group Pbcn, with unit cell dimensions a = 20.2662(6), b = 12.7161(4), c = 15.9423(5)Å and Z = 8. In 1, intermolecular analinium N-H…O and water O-H…O and O-H…N hydrogen-bonding interactions with sulfone, carboxyl, phenolate and nitro O-atom and aniline N-atom acceptors give a two-dimensional layered structure. With 2, the intermolecular interactions involve both aniline N-H…O and carboxylic acid O-H…O and O-H…N hydrogen bonds to sulfone, carboxyl, nitro and aniline acceptors, giving a three-dimensional network structure. In both structures π--π aromatic ring associations are present.

The IKBALS project: multi-modal reasoning in legal knowledge based systems

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work integrates rule based and case based reasoning with intelligent information retrieval. When using the case based reasoning methodology, or in our case the specialisation of case based retrieval, we need to be aware of how to retrieve relevant experience. Our research, in the legal domain, specifies an approach to the retrieval problem which relies heavily on an extended object oriented/rule based system architecture that is supplemented with causal background information. We use a distributed agent architecture to help support the reasoning process of lawyers. Our approach to integrating rule based reasoning, case based reasoning and case based retrieval is contrasted to the CABARET and PROLEXS architectures which rely on a centralised blackboard architecture. We discuss in detail how our various cooperating agents interact, and provide examples of the system at work. The IKBALS system uses a specialised induction algorithm to induce rules from cases. These rules are then used as indices during the case based retrieval process. Because we aim to build legal support tools which can be modified to suit various domains rather than single purpose legal expert systems, we focus on principles behind developing legal knowledge based systems. The original domain chosen was theAccident Compensation Act 1989 (Victoria, Australia), which relates to the provision of benefits for employees injured at work. For various reasons, which are indicated in the paper, we changed our domain to that ofCredit Act 1984 (Victoria, Australia). This Act regulates the provision of loans by financial institutions. The rule based part of our system which provides advice on the Credit Act has been commercially developed in conjunction with a legal firm. We indicate how this work has lead to the development of a methodology for constructing rule based legal knowledge based systems. We explain the process of integrating this existing commercial rule based system with the case base reasoning and retrieval architecture.