A coding approach to the multicast stream authentication problem

We study the multicast stream authentication problem when an opponent can drop, reorder and introduce data packets into the communication channel. In such a model, packet overhead and computing efficiency are two parameters to be taken into account when designing a multicast stream protocol. In this paper, we propose to use two families of erasure codes to deal with this problem, namely, rateless codes and maximum distance separable codes. Our constructions will have the following advantages. First, our packet overhead will be small. Second, the number of signature verifications to be performed at the receiver is O(1). Third, every receiver will be able to recover all the original data packets emitted by the sender despite losses and injection occurred during the transmission of information.

A flexible optimisation model for the railway crew scheduling problem

Addressing the Crew Scheduling Problem (CSP) in transportation systems can be too complex to capture all details. The designed models usually ignore or simplify features which are difficult to formulate. This paper proposes an alternative formulation using a Mixed Integer Programming (MIP) approach to the problem. The optimisation model integrates the two phases of pairing generation and pairing optimisation by simultaneously sequencing trips into feasible duties and minimising total elapsed time of any duty. Crew scheduling constraints in which the crew have to return to their home depot at the end of the shift are included in the model. The flexibility of this model comes in the inclusion of the time interval of relief opportunities, allowing the crew to be relieved during a finite time interval. This will enhance the robustness of the schedule and provide a better representation of real-world conditions.

An algebraic analysis of trivium ciphers based on the boolean satisfiability problem

Trivium is a stream cipher candidate of the eStream project. It has successfully moved into phase three of the selection process under the hardware category. No attacks faster than the exhaustive search have so far been reported on Trivium. Bivium-A and Bivium-B are simplified versions of Trivium that are built on the same design principles but with two registers. The simplified design is useful in investigating Trivium type ciphers with a reduced complexity and provides insight into effective attacks which could be extended to Trivium. This paper focuses on an algebraic analysis which uses the boolean satisfiability problem in propositional logic. For reduced variants of the cipher, this analysis recovers the internal state with a minimal amount of keystream observations.

A more efficient and effective heuristic algorithm for the MapReduce placement problem in cloud computing

The placement of the mappers and reducers on the machines directly affects the performance and cost of the MapReduce computation in cloud computing. From the computational point of view, the mappers/reducers placement problem is a generalization of the classical bin packing problem, which is NP-complete. Thus, in this paper we propose a new heuristic algorithm for the mappers/reducers placement problem in cloud computing and evaluate it by comparing with other several heuristics on solution quality and computation time by solving a set of test problems with various characteristics. The computational results show that our heuristic algorithm is much more efficient than the other heuristics. Also, we verify the effectiveness of our heuristic algorithm by comparing the mapper/reducer placement for a benchmark problem generated by our heuristic algorithm with a conventional mapper/reducer placement. The comparison results show that the computation using our mapper/reducer placement is much cheaper while still satisfying the computation deadline.

A new grouping genetic algorithm for the MapReduce placement problem in cloud computing

MapReduce is a computation model for processing large data sets in parallel on large clusters of machines, in a reliable, fault-tolerant manner. A MapReduce computation is broken down into a number of map tasks and reduce tasks, which are performed by so called mappers and reducers, respectively. The placement of the mappers and reducers on the machines directly affects the performance and cost of the MapReduce computation. From the computational point of view, the mappers/reducers placement problem is a generation of the classical bin packing problem, which is NPcomplete. Thus, in this paper we propose a new grouping genetic algorithm for the mappers/reducers placement problem in cloud computing. Compared with the original one, our grouping genetic algorithm uses an innovative coding scheme and also eliminates the inversion operator which is an essential operator in the original grouping genetic algorithm. The new grouping genetic algorithm is evaluated by experiments and the experimental results show that it is much more efficient than four popular algorithms for the problem, including the original grouping genetic algorithm.

Secure computation of the vector dominance problem

Suppose two parties, holding vectors A = (a 1,a 2,...,a n ) and B = (b 1,b 2,...,b n ) respectively, wish to know whether a i  > b i for all i, without disclosing any private input. This problem is called the vector dominance problem, and is closely related to the well-studied problem for securely comparing two numbers (Yao’s millionaires problem). In this paper, we propose several protocols for this problem, which improve upon existing protocols on round complexity or communication/computation complexity.

Distributed private matching and set operations

Motivated by the need of private set operations in a distributed environment, we extend the two-party private matching problem proposed by Freedman, Nissim and Pinkas (FNP) at Eurocrypt’04 to the distributed setting. By using a secret sharing scheme, we provide a distributed solution of the FNP private matching called the distributed private matching. In our distributed private matching scheme, we use a polynomial to represent one party’s dataset as in FNP and then distribute the polynomial to multiple servers. We extend our solution to the distributed set intersection and the cardinality of the intersection, and further we show how to apply the distributed private matching in order to compute distributed subset relation. Our work extends the primitives of private matching and set intersection by Freedman et al. Our distributed construction might be of great value when the dataset is outsourced and its privacy is the main concern. In such cases, our distributed solutions keep the utility of those set operations while the dataset privacy is not compromised. Comparing with previous works, we achieve a more efficient solution in terms of computation. All protocols constructed in this paper are provably secure against a semi-honest adversary under the Decisional Diffie-Hellman assumption.

Prediction with limited advice and multiarmed bandits with paid observations

We study two problems of online learning under restricted information access. In the first problem, prediction with limited advice, we consider a game of prediction with expert advice, where on each round of the game we query the advice of a subset of M out of N experts. We present an algorithm that achieves O(√(N/M)TlnN ) regret on T rounds of this game. The second problem, the multiarmed bandit with paid observations, is a variant of the adversarial N-armed bandit game, where on round t of the game we can observe the reward of any number of arms, but each observation has a cost c. We present an algorithm that achieves O((cNlnN) 1/3 T2/3+√TlnN ) regret on T rounds of this game in the worst case. Furthermore, we present a number of refinements that treat arm- and time-dependent observation costs and achieve lower regret under benign conditions. We present lower bounds that show that, apart from the logarithmic factors, the worst-case regret bounds cannot be improved.

Open problem : adversarial multiarmed bandits with limited advice

Adversarial multiarmed bandits with expert advice is one of the fundamental problems in studying the exploration-exploitation trade-o. It is known that if we observe the advice of all experts on every round we can achieve O(√KTlnN) regret, where K is the number of arms, T is the number of game rounds, and N is the number of experts. It is also known that if we observe the advice of just one expert on every round, we can achieve regret of order O(√NT). Our open problem is what can be achieved by asking M experts on every round, where 1 < M < N.

Retooling Chinese primary school teachers to use technology creatively to promote innovation and problem solving skills in science classrooms

This paper reports on the initial phase of a Professional Learning Program (PLP) undertaken by 100 primary school teachers in China that aimed to facilitate the development of adaptive expertise in using technology to facilitate innovative science teaching and learning such as that envisaged by the Chinese Ministry of Education’s (2010-2020) education reforms. Key principles derived from literature about professional learning and scaffolding of learning informed the design of the PLP. The analysis of data revealed that the participants had made substantial progress towards the development of adaptive expertise. This was manifested not only by advances in the participants’ repertoires of Subject Matter Knowledge and Pedagogical Content Knowledge but also in changes to their levels of confidence and identities as teachers. By the end of the initial phase of the PLP, the participants had coalesced into a professional learning community that readily engaged in the sharing, peer review, reuse and adaption, and collaborative design of innovative science learning and assessment activities. The findings from the study indicate that those engaged in the development of PLPs for teachers in China need to take cognizance of certain cultural factors and traditions idiosyncratic to the Chinese educational system. A set of revised principles is then presented to inform the future design and implementation of PLPs for teachers in China.

Physical inactivity remains the greatest public health problem of the 21st century : evidence, improved methods and solutions using the '7 investments that work' as a framework

In 2009, BJSM's first editorial argued that ‘Physical inactivity is the greatest public health problem of the 21st century’.1 The data supporting that claim have not yet been challenged. Now, 5 years after BJSM published its first dedicated ‘Physical Activity is Medicine’ theme issue (http://bjsm.bmj.com/content/43/1.toc) we are pleased to highlight 23 new contributions from six countries. This issue contains an analysis of the cost of physical inactivity from the US Centre for Diseases Control.2 We also report the cost-effectiveness of one particular physical activity intervention for adults.3

The slumbarumba jumbuck problem

The potential for simple linear relationships arising from a computer game to build student modelling and "world problem" skills is explored. The fundamental capability of the spreadsheet to tabulate and graph possible solutions is used to lay bare the problem structure for the students.

Problem Solving with Delphi

The purpose of the book is to use Delphi as a vehicle to introduce some fundamental algorithms and to illustrate several mathematical and problem-solving techniques. This book is therefore intended to be more of a reference for problem-solving, with the solution expressed in Delphi. It introduces a somewhat eclectic collection of material, much of which will not be found in a typical book on Pascal or Delphi. Many of the topics have been used by the author over a period of about ten years at Bond University, Australia in various subjects from 1993 to 2003. Much of the work was connected with a data structures subject (second programming course) conducted variously in MODULA-2, Oberon and Delphi, at Bond University, however there is considerable other, more recent material, e.g., a chapter on Sudoku.

Asymptotic minimax robust and misspecified Lorden quickest change detection for dependent stochastic processes

The quick detection of an abrupt unknown change in the conditional distribution of a dependent stochastic process has numerous applications. In this paper, we pose a minimax robust quickest change detection problem for cases where there is uncertainty about the post-change conditional distribution. Our minimax robust formulation is based on the popular Lorden criteria of optimal quickest change detection. Under a condition on the set of possible post-change distributions, we show that the widely known cumulative sum (CUSUM) rule is asymptotically minimax robust under our Lorden minimax robust formulation as a false alarm constraint becomes more strict. We also establish general asymptotic bounds on the detection delay of misspecified CUSUM rules (i.e. CUSUM rules that are designed with post- change distributions that differ from those of the observed sequence). We exploit these bounds to compare the delay performance of asymptotically minimax robust, asymptotically optimal, and other misspecified CUSUM rules. In simulation examples, we illustrate that asymptotically minimax robust CUSUM rules can provide better detection delay performance at greatly reduced computation effort compared to competing generalised likelihood ratio procedures.

A non-malleable group key exchange protocol robust against active insiders

In this paper we make progress towards solving an open problem posed by Katz and Yung at CRYPTO 2003. We propose the first protocol for key exchange among n ≥2k+1 parties which simultaneously achieves all of the following properties: 1. Key Privacy (including forward security) against active attacks by group outsiders, 2. Non-malleability — meaning in particular that no subset of up to k corrupted group insiders can ‘fix’ the agreed key to a desired value, and 3. Robustness against denial of service attacks by up to k corrupted group insiders. Our insider security properties above are achieved assuming the availability of a reliable broadcast channel.