Multiple-time signature schemes against adaptive chosen message attacks

Multiple-time signatures are digital signature schemes where the signer is able to sign a predetermined number of messages. They are interesting cryptographic primitives because they allow to solve many important cryptographic problems, and at the same time offer substantial efficiency advantage over ordinary digital signature schemes like RSA. Multiple-time signature schemes have found numerous applications, in ordinary, on-line/off-line, forward-secure signatures, and multicast/stream authentication. We propose a multiple-time signature scheme with very efficient signing and verifying. Our construction is based on a combination of one-way functions and cover-free families, and it is secure against the adaptive chosen-message attack.

Determining epithelial contribution to in vivo mesenchymal tumour expression signature using species-specific microarray profiling analysis of xenografts

Gene expression profiling using microarrays and xenograft transplants of human cancer cell lines are both popular tools to investigate human cancer. However, the undefined degree of cross hybridization between the mouse and human genomes hinders the use of microarrays to characterize gene expression of both the host and the cancer cell within the xenograft. Since an increasingly recognized aspect of cancer is the host response (or cancer-stroma interaction), we describe here a bioinformatic manipulation of the Affymetrix profiling that allows interrogation of the gene expression of both the mouse host and the human tumour. Evidence of microenvironmental regulation of epithelial mesenchymal transition of the tumour component in vivo is resolved against a background of mesenchymal gene expression. This tool could allow deeper insight to the mechanism of action of anti-cancer drugs, as typically novel drug efficacy is being tested in xenograft systems.

How to strengthen any weakly unforgeable signature into a strongly unforgeable signature

Standard signature schemes are usually designed only to achieve weak unforgeability – i.e. preventing forgery of signatures on new messages not previously signed. However, most signature schemes are randomised and allow many possible signatures for a single message. In this case, it may be possible to produce a new signature on a previously signed message. Some applications require that this type of forgery also be prevented – this requirement is called strong unforgeability. At PKC2006, Boneh Shen and Waters presented an efficient transform based on any randomised trapdoor hash function which converts a weakly unforgeable signature into a strongly unforgeable signature and applied it to construct a strongly unforgeable signature based on the CDH problem. However, the transform of Boneh et al only applies to a class of so-called partitioned signatures. Although many schemes fall in this class, some do not, for example the DSA signature. Hence it is natural to ask whether one can obtain a truly generic efficient transform based on any randomised trapdoor hash function which converts any weakly unforgeable signature into a strongly unforgeable one. We answer this question in the positive by presenting a simple modification of the Boneh-Shen-Waters transform. Our modified transform uses two randomised trapdoor hash functions.

The elaborated intrusion theory of desire : a 10-year retrospective and implications for addiction treatments

Introduction: Ten years after the publication of Elaborated Intrusion (EI) Theory, there is now substantial research into its key predictions. The distinction between intrusive thoughts, which are driven by automatic processes, and their elaboration, involving controlled processing, is well established. Desires for both addictive substances and other desired targets are typically marked by imagery, especially when they are intense. Attention training strategies such as body scanning reduce intrusive thoughts, while concurrent tasks that introduce competing sensory information interfere with elaboration, especially if they compete for the same limited-capacity working memory resources. Conclusion: EI Theory has spawned new assessment instruments that are performing strongly and offer the ability to more clearly delineate craving from correlated processes. It has also inspired new approaches to treatment. In particular, training people to use vivid sensory imagery for functional goals holds promise as an intervention for substance misuse, since it is likely to both sustain motivation and moderate craving.

Approximate nearest-neighbour search with inverted signature slice lists

In this paper we present an original approach for finding approximate nearest neighbours in collections of locality-sensitive hashes. The paper demonstrates that this approach makes high-performance nearest-neighbour searching feasible on Web-scale collections and commodity hardware with minimal degradation in search quality.

Parallel streaming signature EM-tree: A clustering algorithm for web scale applications

The proliferation of the web presents an unsolved problem of automatically analyzing billions of pages of natural language. We introduce a scalable algorithm that clusters hundreds of millions of web pages into hundreds of thousands of clusters. It does this on a single mid-range machine using efficient algorithms and compressed document representations. It is applied to two web-scale crawls covering tens of terabytes. ClueWeb09 and ClueWeb12 contain 500 and 733 million web pages and were clustered into 500,000 to 700,000 clusters. To the best of our knowledge, such fine grained clustering has not been previously demonstrated. Previous approaches clustered a sample that limits the maximum number of discoverable clusters. The proposed EM-tree algorithm uses the entire collection in clustering and produces several orders of magnitude more clusters than the existing algorithms. Fine grained clustering is necessary for meaningful clustering in massive collections where the number of distinct topics grows linearly with collection size. These fine-grained clusters show an improved cluster quality when assessed with two novel evaluations using ad hoc search relevance judgments and spam classifications for external validation. These evaluations solve the problem of assessing the quality of clusters where categorical labeling is unavailable and unfeasible.

We don’t want your must-see TV: Transatlantic television and the failed “Coupling” format

NBC's failed attempt to remake the BBC's Coupling generated a significant amount of press coverage in summer 2003. At the core of the debate was a struggle to reconcile an increasingly integrated transatlantic television market with traditional assumptions about culture and its authentic connection to space and place. The interest in the remake not only created a space where certain national differences were played out and performed but also facilitated an equally compelling transatlantic dialogue about creative ownership, appropriation, and a network's responsibility to its audiences. In doing so, the media attention highlighted how television formats are best understood not as innocuous commodities of international trade but as potential sites of articulation, contestation, and community in an increasingly transnational television environment.

Email negotiations form a binding land contract without a 'signature'

Email is rapidly replacing other forms of communication as the preferred means of communication between contracting parties. The recent decision of Stellard Pty Ltd v North Queensland Fuel Pty Ltd [2015] QSC 119 reinforces the judicial acceptance of email as an effective means of creating a binding agreement and the willingness to adopt a liberal concept of ‘signing’ in an electronic environment.

Improvement in Intrusion Detection With Advances in Sensor Fusion

Various intrusion detection systems (IDSs) reported in the literature have shown distinct preferences for detecting a certain class of attack with improved accuracy, while performing moderately on the other classes. In view of the enormous computing power available in the present-day processors, deploying multiple IDSs in the same network to obtain best-of-breed solutions has been attempted earlier. The paper presented here addresses the problem of optimizing the performance of IDSs using sensor fusion with multiple sensors. The trade-off between the detection rate and false alarms with multiple sensors is highlighted. It is illustrated that the performance of the detector is better when the fusion threshold is determined according to the Chebyshev inequality. In the proposed data-dependent decision ( DD) fusion method, the performance optimization of ndividual IDSs is first addressed. A neural network supervised learner has been designed to determine the weights of individual IDSs depending on their reliability in detecting a certain attack. The final stage of this DD fusion architecture is a sensor fusion unit which does the weighted aggregation in order to make an appropriate decision. This paper theoretically models the fusion of IDSs for the purpose of demonstrating the improvement in performance, supplemented with the empirical evaluation.

Intrusion warning and assessment method for site safety enhancement

Intrusion (unauthorized stepping-into/staying-in a hazardous area), as a common type of near-miss, is the prime cause of the majority of incidents on construction sites including fall from heights, and striking against or being struck by moving objects. Accidents often occur because workers take shortcuts moving about the site without fully perceiving the potential dangers. A number of researches have been devoted to developing methods to prevent such behaviors mainly based on the theory of Behavior-Based Safety (BBS), which aims to cultivate safety behaviors among workers in accordance with safety regulations. In current BBS practice, trained observers and safety supervisors are responsible for safety behavior inspections following safety plans and operation regulations. The observation process is time-consuming and its effectiveness depends largely on the observer’s safety knowledge and experience, which often results in omissions or bias. This paper presents a reformed safety behavior modification approach by integrating a location-based technology with BBS. Firstly, a detailed background is provided, covering current intrusion problems on site, existing use of BBS for behavior improvement, difficulties in achieving widespread adoption and potential technologies for location tracking and in-time feedback. Then, a conceptual framework of positioning technology-enhanced BBS is developed, followed by details of the corresponding on-line supporting system, Real Time Location System (RTLS) and Virtual Construction System (VCS). The application of the system is then demonstrated and tested in a construction site in Hong Kong. Final comments are made concerning further research direction and prospects for wider adoption.

Genome-wide DNA methylation profiling of CD8+ T cells shows a distinct epigenetic signature to CD4+ T cells in multiple sclerosis patients

Background Multiple sclerosis (MS) is thought to be a T cell-mediated autoimmune disorder. MS pathogenesis is likely due to a genetic predisposition triggered by a variety of environmental factors. Epigenetics, particularly DNA methylation, provide a logical interface for environmental factors to influence the genome. In this study we aim to identify DNA methylation changes associated with MS in CD8+ T cells in 30 relapsing remitting MS patients and 28 healthy blood donors using Illumina 450K methylation arrays. Findings Seventy-nine differentially methylated CpGs were associated with MS. The methylation profile of CD8+ T cells was distinctive from our previously published data on CD4+ T cells in the same cohort. Most notably, there was no major CpG effect at the MS risk gene HLA-DRB1 locus in the CD8+ T cells. Conclusion CD8+ T cells and CD4+ T cells have distinct DNA methylation profiles. This case–control study highlights the importance of distinctive cell subtypes when investigating epigenetic changes in MS and other complex diseases.

Functional Imagery Training to reduce snacking: Testing a novel motivational intervention based on Elaborated Intrusion theory

Functional Imagery Training (FIT) is a new theory-based, manualized intervention that trains positive goal imagery. Multisensory episodic imagery of proximal personal goals is elicited and practised, to sustain motivation and compete with less functional cravings. This study tested the impact of a single session of FIT plus a booster phone call on snacking. In a stepped-wedge design, 45 participants who wanted to lose weight or reduce snacking were randomly assigned to receive a session of FIT immediately or after a 2-week delay. High-sugar and high-fat snacks were recorded using timeline follow back for the previous 3 days, at baseline, 2 and 4 weeks. At 2 weeks, snacking was lower in the immediate group than in the delayed group, and the reduction after FIT was replicated in the delayed group between 2 and 4 weeks. Frequencies of motivational thoughts about snack reduction rose following FIT for both groups, and this change correlated with reductions in snacking and weight loss. By showing that FIT can support change in eating behaviours, these findings show its potential as a motivational intervention for weight management.

A method of fraud & intrusion detection for e-payment systems in mobile

The need for paying with mobile devices has urged the development of payment systems for mobile electronic commerce. In this paper we have considered two important abuses in electronic payments systems for detection. The fraud, which is an intentional deception accomplished to secure an unfair gain, and an intrusion which are any set of actions that attempt to compromise the integrity, confidentiality or availability of a resource. Most of the available fraud and intrusion detection systems for e-payments are specific to the systems where they have been incorporated. This paper proposes a generic model called as Activity-Event-Symptoms(AES) model for detecting fraud and intrusion attacks which appears during payment process in the mobile commerce environment. The AES model is designed to identify the symptoms of fraud and intrusions by observing various events/transactions occurs during mobile commerce activity. The symptoms identification is followed by computing the suspicion factors for event attributes, and the certainty factor for a fraud and intrusion is generated using these suspicion factors. We have tested the proposed system by conducting various case studies, on the in-house established mobile commerce environment over wired and wire-less networks test bed.