pinecone/core-2020-05-10-deduplication huggingface dataset:
Deterministic Public-Key Encryption for Adaptively Chosen Plaintext Distributions

Bellare, Boldyreva, and O’Neill (CRYPTO ’07) initiated the study of deterministic public-key encryption as an alternative in scenarios where randomized encryption has inherent drawbacks. The resulting line of research has so far guaranteed security only for adversarially-chosen plaintext distributions that are independent of the public key used by the scheme. In most scenarios, however, it is typically not realistic to assume that adversaries do not take the public key into account when attacking a scheme.
We show that it is possible to guarantee meaningful security even for plaintext distributions that depend on the public key. We extend the previously proposed notions of security, allowing adversaries to adaptively choose plaintext distributions after seeing the public key, in an interactive manner. The only restrictions we make are that: (1) plaintext distributions are unpredictable (as is essential in deterministic public-key encryption), and (2) the number of plaintext distributions from which each adversary is allowed to adaptively choose is upper bounded by \(2^ p\) , where p can be any predetermined polynomial in the security parameter. For example, with p = 0 we capture plaintext distributions that are independent of the public key, and with p = O(s logs) we capture, in particular, all plaintext distributions that are samplable by circuits of size s.
Within our framework we present both constructions in the random-oracle model based on any public-key encryption scheme, and constructions in the standard model based on lossy trapdoor functions (thus, based on a variety of number-theoretic assumptions). Previously known constructions heavily relied on the independence between the plaintext distributions and the public key for the purposes of randomness extraction. In our setting, however, randomness extraction becomes significantly more challenging once the plaintext distributions and the public key are no longer independent. Our approach is inspired by research on randomness extraction from seed-dependent distributions. Underlying our approach is a new generalization of a method for such randomness extraction, originally introduced by Trevisan and Vadhan (FOCS ’00) and Dodis (PhD Thesis, MIT, ’00).Engineering and Applied Science
Energy Evaluation Model for an Improved Centralized Clustering Hierarchical Algorithm in WSN

Wireless Sensor Networks (WSN) consists of battery-powered sensor nodes which collect data and route the data to the Base Station. Centralized Cluster-based routing protocols efficiently utilize limited energy of the nodes by selecting Cluster Heads (CHs) in each round. Selection of CHs and Cluster formation is performed by the Base Station. In each round, nodes transmit their location information and their residual energy to the Base Station. This operation is a considerable burden on these resource hungry sensor nodes. In this paper we propose a scheme whereby a small number of High-Energy nodes gather location information and residual energy status of the sensing nodes and transmit to the Base Station. This scheme eliminates CH advertisement phase in order to conserve energy. Based on the energy consumption by various types of nodes, we have derived an energy model for our algorithm which depicts the total energy consumption in the network
Change Patterns in Use: A Critical Evaluation

Process model quality has been an area of considerable research efforts. In
this context, the correctness-by-construction principle of change patterns
provides promising perspectives. However, using change patterns for model
creation imposes a more structured way of modeling. While the process of
process modeling (PPM) based on change primitives has been investigated, little
is known about this process based on change patterns. To obtain a better
understanding of the PPM when using change patterns, the arising challenges,
and the subjective perceptions of process designers, we conduct an exploratory
study. The results indicate that process designers face little problems as long
as control-flow is simple, but have considerable problems with the usage of
change patterns when complex, nested models have to be created. Finally, we
outline how effective tool support for change patterns should be realized
Making Sense of Declarative Process Models: Common Strategies and
  Typical Pitfalls

Declarative approaches to process modeling are regarded as well suited for
highly volatile environments as they provide a high degree of flexibility.
However, problems in understanding and maintaining declarative business process
models impede often their usage. In particular, how declarative models are
understood has not been investigated yet. This paper takes a first step toward
addressing this question and reports on an exploratory study investigating how
analysts make sense of declarative process models. We have handed out
real-world declarative process models to subjects and asked them to describe
the illustrated process. Our qualitative analysis shows that subjects tried to
describe the processes in a sequential way although the models represent
circumstantial information, namely, conditions that produce an outcome, rather
than a sequence of activities. Finally, we observed difficulties with single
building blocks and combinations of relations between activities
Process Mining Versus Intention Mining

International audienceProcess mining aims to discover, enhance or check the conformance of activity oriented process models from event logs. A new field of research, called intention mining, recently emerged. This new field has the same objectives than process mining but specifically addresses intentional process models. This paper aims to highlight the differences between these two fields of research and illustrates the use of mining techniques on a dataset of event logs, to discover an activity process model as well as an intentional process model
Change Patterns for Model Creation: Investigating the Role of Nesting
  Depth

Process model quality has been an area of considerable research efforts. In
this context, the correctness-by-construction principle of change patterns
offers a promising perspective. However, using change patterns for model
creation imposes a more structured way of modeling. While the process of
process modeling (PPM) based on change primitives has been investigated, little
is known about this process based on change patterns and factors that impact
the cognitive complexity of pattern usage. Insights from the field of cognitive
psychology as well as observations from a pilot study suggest that the nesting
depth of the model to be created has a significant impact on cognitive
complexity. This paper proposes a research design to test the impact of nesting
depth on the cognitive complexity of change pattern usage in an experiment.Comment: arXiv admin note: substantial text overlap with arXiv:1511.0405
A theoretical basis for using virtual worlds as a personalised process visualisation approach

Communication processes are vital in the lifecycle of BPM projects. With this in mind, much research has been performed into facilitating this key component between stakeholders. Amongst the methods used to support this process are personalized process visualisations. In this paper, we review the development of this visualization trend, then, we propose a theoretical analysis framework based upon communication theory. We use this framework to provide theoretical support to the conjecture that 3D virtual worlds are powerful tools for communicating personalised visualisations of processes within a workplace. Meta requirements are then derived and applied, via 3D virtual world functionalities, to generate example visualisations containing personalized aspects, which we believe enhance the process of communcation between analysts and stakeholders in BPM process (re)design activities
Typing progress in communication-centred systems

We present a type system for the analysis of progress in session-based communication centred systems. Our development is carried out in a minimal setting considering classic (binary) sessions, but building on and generalising previous work on progress analysis in the context of conversation types. Our contributions aim at underpinning forthcoming works on progress for session-typed systems, so as to support richer verification procedures based on a more foundational approach. Although this work does not target expressiveness, our approach already addresses challenging scenarios which are unaccounted for elsewhere in the literature, in particular systems that interleave communications on received session channels
A general model for MAC generation using direct injection

This paper presents a model for generating a MAC tag by injecting the input message directly into the internal state of a nonlinear filter generator. This model generalises a similar model for unkeyed hash functions proposed by Nakano et al. We develop a matrix representation for the accumulation phase of our model and use it to analyse the security of the model against man-in-the-middle forgery attacks based on collisions in the final register contents. The results of this analysis show that some conclusions of Nakano et al regarding the security of their model are incorrect. We also use our results to comment on several recent MAC proposals which can be considered as instances of our model and specify choices of options within the model which should prevent the type of forgery discussed here. In particular, suitable initialisation of the register and active use of a secure nonlinear filter will prevent an attacker from finding a collision in the final register contents which could result in a forged MAC
QuickHeapsort: Modifications and improved analysis

We present a new analysis for QuickHeapsort splitting it into the analysis of
the partition-phases and the analysis of the heap-phases. This enables us to
consider samples of non-constant size for the pivot selection and leads to
better theoretical bounds for the algorithm. Furthermore we introduce some
modifications of QuickHeapsort, both in-place and using n extra bits. We show
that on every input the expected number of comparisons is n lg n - 0.03n + o(n)
(in-place) respectively n lg n -0.997 n+ o (n). Both estimates improve the
previously known best results. (It is conjectured in Wegener93 that the
in-place algorithm Bottom-Up-Heapsort uses at most n lg n + 0.4 n on average
and for Weak-Heapsort which uses n extra-bits the average number of comparisons
is at most n lg n -0.42n in EdelkampS02.) Moreover, our non-in-place variant
can even compete with index based Heapsort variants (e.g. Rank-Heapsort in
WangW07) and Relaxed-Weak-Heapsort (n lg n -0.9 n+ o (n) comparisons in the
worst case) for which no O(n)-bound on the number of extra bits is known
Multi-weighted Automata and MSO Logic

Weighted automata are non-deterministic automata where the transitions are
equipped with weights. They can model quantitative aspects of systems like
costs or energy consumption. The value of a run can be computed, for example,
as the maximum, limit average, or discounted sum of transition weights. In
multi-weighted automata, transitions carry several weights and can model, for
example, the ratio between rewards and costs, or the efficiency of use of a
primary resource under some upper bound constraint on a secondary resource.
Here, we introduce a general model for multi-weighted automata as well as a
multiweighted MSO logic. In our main results, we show that this multi-weighted
MSO logic and multi-weighted automata are expressively equivalent both for
finite and infinite words. The translation process is effective, leading to
decidability results for our multi-weighted MSO logic.Comment: The final version appeared in the Proceedings of the 8th
  International Computer Science Symposium in Russia (CSR 2013
Walking on Data Words

International audienceWe see data words as sequences of letters with additional edges that connect pairs of positions carrying the same data value. We consider a natural model of automaton walking on data words, called Data Walking Automaton, and study its closure properties, expressiveness, and the complexity of paradigmatic problems. We prove that deterministic DWA are strictly included in non-deterministic DWA, that the former subclass is closed under all boolean operations, and that the latter class enjoys a decidable containment problem
Random Generation of Deterministic Acyclic Automata Using the Recursive Method

International audienceIn this article, we propose a uniform random generator for accessible deterministic acyclic automata with n states, which is based on the recursive method. The generator has a preprocessing that requires O(n<sup>3</sup>) arithmetic operations, and, once it is done, can generate acyclic automata using O(n) arithmetic operations for each sample. We also propose a lazy version of the algorithm that takes advantage of the typical shape of random acyclic automata to reduce experimentally the preprocessing. Using this algorithm, we provide some statistics on acyclic automata with up to 1000 states
An effective scalable SQL engine for NoSQL databases

NoSQL databases were initially devised to support a few concrete extreme scale applications. Since the specificity and scale of the target systems justified the investment of manually crafting application code their limited query and indexing capabilities were not a major im- pediment. However, with a considerable number of mature alternatives now available there is an increasing willingness to use NoSQL databases in a wider and more diverse spectrum of applications and, to most of them, hand-crafted query code is not an enticing trade-off. In this paper we address this shortcoming of current NoSQL databases with an effective approach for executing SQL queries while preserving their scalability and schema flexibility. We show how a full-fledged SQL engine can be integrated atop of HBase leading to an ANSI SQL compli- ant database. Under a standard TPC-C workload our prototype scales linearly with the number of nodes in the system and outperforms a NoSQL TPC-C implementation optimized for HBase
Dynamic Deployment of Sensing Experiments in the Wild Using Smartphones

Part 1: Full Research PapersInternational audienceWhile scientific communities extensively exploit simulations to validate their theories, the relevance of their results strongly depends on the realism of the dataset they use as an input. This statement is particularly true when considering human activity traces, which tend to be highly unpredictable. In this paper, we therefore introduce APISENSE, a distributed crowdsensing platform for collecting realistic activity traces. In particular, APISENSE provides to scientists a participative platform to help them to easily deploy their sensing experiments in the wild. Beyond the scientific contributions of this platform, the technical originality of APISENSE lies in its Cloud orientation and the dynamic deployment of scripts within the mobile devices of the participants.We validate this platform by reporting on various crowdsensing experiments we deployed using Android smartphones and comparing our solution to existing crowdsensing platforms
Ajitts: adaptive just-in-time transaction scheduling

Lecture Notes in Computer Science 7891, 2013Distributed transaction processing has benefited greatly from optimistic concurrency control protocols thus avoiding costly fine-grained synchronization. However, the performance of these protocols degrades significantly when the workload increases, namely, by leading to a substantial amount of aborted transactions due to concurrency conflicts. Our approach stems from the observation that when the abort rate increases with the load as already executed transactions queue for longer periods of time waiting for their turn to be certified and committed. We thus propose an adaptive algorithm for judiciously scheduling transactions to minimize the time during which these are vulnerable to being aborted by concurrent transactions, thereby reducing the overall abort rate. We do so by throttling transaction execution using an adaptive mechanism based on the locally known state of globally executing transactions, that includes out-of-order execution.
Our evaluation using traces from the industry standard TPC-E workload shows that the amount of aborted transactions can be kept bounded as system load increases, while at the same time fully utilizing system resources and thus scaling transaction processing throughput
Adapting Lyubashevsky's signature schemes to the ring signature setting

Basing signature schemes on strong lattice problems has been a long standing open issue. Today, two families of lattice-based signature schemes are known: the ones based on the hash-and-sign construction of Gentry et al.; and Lyubashevsky’s schemes, which are based on the Fiat-Shamir framework. In this paper we show for the first time how to adapt the schemes of Lyubashevsky to the ring signature setting. In particular we transform the scheme of ASIACRYPT 2009 into a ring signature scheme that provides strong properties of security under the random oracle model. Anonymity is ensured in the sense that signatures of different users are within negligible statistical distance even under full key exposure. In fact, the scheme satisfies a notion which is stronger than the classical full key exposure setting as even if the keypair of the signing user is adversarially chosen, the statistical distance between signatures of different users remains negligible. Considering unforgeability, the best lattice-based ring signature schemes provide either unforgeability against arbitrary chosen subring attacks or insider corruption in log-sized rings. In this paper we present two variants of our scheme. In the basic one, unforgeability is ensured in those two settings. Increasing signature and key sizes by a factor k (typically 80 − 100), we provide a variant in which unforgeability is ensured against insider corruption attacks for arbitrary rings. The technique used is pretty general and can be adapted to other existing schemes
GRASPing examination board assignments for university-entrance exams

26th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2013, Amsterdam, The Netherlands, June 17-21, 2013The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-38577-3_18In the sequel, we tackle a real-world problem: forming examination boards for the university-entrance exams at the autonomous region of Asturias (Spain). We formulate the problem, propose a heuristic GRASP-like method to solve it and show some experimental results to support our proposa
On using the theory of regular functions to prove the ε-Optimality of the Continuous Pursuit Learning Automaton

Published version of a chapter in the book: Recent Trends in Applied Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-38577-3_27There are various families of Learning Automata (LA) such as Fixed Structure, Variable Structure, Discretized etc. Informally, if the environment is stationary, their ε-optimality is defined as their ability to converge to the optimal action with an arbitrarily large probability, if the learning parameter is sufficiently small/large. Of these LA families, Estimator Algorithms (EAs) are certainly the fastest, and within this family, the set of Pursuit algorithms have been considered to be the pioneering schemes. The existing proofs of the ε-optimality of all the reported EAs follow the same fundamental principles. Recently, it has been reported that the previous proofs for the ε-optimality of all the reported EAs have a common flaw. In other words, people have worked with this flawed reasoning for almost three decades. The flaw lies in the condition which apparently supports the so-called “monotonicity” property of the probability of selecting the optimal action, explained in the paper. In this paper, we provide a new method to prove the ε-optimality of the Continuous Pursuit Algorithm (CPA), which was the pioneering EA. The new proof follows the same outline of the previous proofs, but instead of examining the monotonicity property of the action probabilities, it rather examines their submartingale property, and then, unlike the traditional approach, invokes the theory of Regular functions to prove the ε-optimality. We believe that the proof is both unique and pioneering, and that it can form the basis for formally demonstrating the ε-optimality of other EAs
Ant colony optimisation for planning safe escape routes

Published version of a chapter from the volume: Recent Trends in Applied Artificial Intelligence. Also available on SpringerLink: http://dx.doi.org/10.1007/978-3-642-38577-3_6An emergency requiring evacuation is a chaotic event filled with uncertainties both for the people affected and rescuers. The evacuees are often left to themselves for navigation to the escape area. The chaotic situation increases when a predefined escape route is blocked by a hazard, and there is a need to re-think which escape route is safest. This paper addresses automatically finding the safest escape route in emergency situations in large buildings or ships with imperfect knowledge of the hazards. The proposed solution, based on Ant Colony Optimisation, suggests a near optimal escape plan for every affected person — considering both dynamic spread of hazards and congestion avoidance.The solution can be used both on an individual bases, such as from a personal smart phone of one of the evacuees, or from a remote location by emergency personnel trying to assist large groups
A spatio-temporal probabilistic model of hazard and crowd dynamics in disasters for evacuation planning

Published version of a chapter in the book: Recent Trends in Applied Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-38577-3_7Managing the uncertainties that arise in disasters – such as ship fire – can be extremely challenging. Previous work has typically focused either on modeling crowd behavior or hazard dynamics, targeting fully known environments. However, when a disaster strikes, uncertainty about the nature, extent and further development of the hazard is the rule rather than the exception. Additionally, crowd and hazard dynamics are both intertwined and uncertain, making evacuation planning extremely difficult. To address this challenge, we propose a novel spatio-temporal probabilistic model that integrates crowd with hazard dynamics, using a ship fire as a proof-of-concept scenario. The model is realized as a dynamic Bayesian network (DBN), supporting distinct kinds of crowd evacuation behavior – both descriptive and normative (optimal). Descriptive modeling is based on studies of physical fire models, crowd psychology models, and corresponding flow models, while we identify optimal behavior using Ant-Based Colony Optimization (ACO). Simulation results demonstrate that the DNB model allows us to track and forecast the movement of people until they escape, as the hazard develops from time step to time step. Furthermore, the ACO provides safe paths, dynamically responding to current threats
Semantic Subtyping for Objects and Classes

Part 3: Session 2: TypesInternational audienceWe propose an integration of structural subtyping with boolean connectives and semantic subtyping to define a Java-like programming language that exploits the benefits of both techniques. Semantic subtyping is an approach to defining subtyping relation based on set-theoretic models, rather than syntactic rules. On the one hand, this approach involves some non trivial mathematical machinery in the background. On the other hand, final users of the language need not know this machinery and the resulting subtyping relation is very powerful and intuitive. While semantic subtyping is naturally linked to the structural one, we show how the framework can also accommodate the nominal subtyping. Several examples show the expressivity and the practical advantages of our proposal