21 research outputs found

    Recovering fitness gradients for interprocedural Boolean flags in search-based testing

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    National Research Foundation (NRF) Singapore under Corp Lab @ University scheme; National Research Foundation (NRF) Singapore under its NSoE Programm

    The Influences of International Trade on Sustainable Economic Growth: An Economic Policy Perspective

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    This study uses the Gregory–Hansen cointegration method and the vector error correction model in the vector autoregression system to reveal how international trade contributes to economic sustainability. The Gregory–Hansen test for cointegration method reveals a permanent equilibrium relation among sustainably economic growth, exports, and imports and shows that exports facilitate GDP growth and accelerate improvements in the capability of imports in the long-run. The causality between GDP and exports is unidirectional, indicating that exports area determinant of sustainable economic growth. The bidirectional causality from imports to GDP also sheds light on the important influence of imports on economic sustainability; however, GDP growth also drives import growth. The interaction between imports and exports corresponds to their bidirectional causal relationship, which is indicative of imports contributing to export production and of export growth expanding the capacity for imports. This finding indicates that imports are both exogenous and endogenous factors for exports

    Enforced privacy: from practice to theory

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    Formal analysis of privacy in an eHealth protocol

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    Abstract. Given the sensitive nature of health data, privacy of eHealth systems is of prime importance. An eHealth system must enforce that users remain private, even if they are bribed or coerced to reveal themselves or others. Consider e.g. a pharmaceutical company that bribes a pharmacist to reveal information which breaks a doctor’s privacy. In this paper, we first identify and formalise several new but important privacy notions on enforcing doctor privacy. Then we analyse privacy of a complicated and practical eHealth protocol (DLVV08). Our analysis shows to what extent these new properties as well as properties such as anonymity and untraceability are satisfied by the protocol. Finally, we address the found am-biguities which result in privacy flaws, and propose suggestions for fixing them.

    Challenges in eHealth: from enabling to enforcing privacy

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    Abstract. Privacy is recognised as a fundamental requirement for eHealth systems. Proposals to achieve privacy have been put forth in literature, most of which approach patient privacy as either an access control or an authentication problem. In this paper, we investigate privacy in eHealth as a communication problem, since future eHealth systems will be highly distributed and require interoperability of many sub-systems. In addi-tion, we research privacy needs for others than patients. In our study, we identify two key privacy challenges in eHealth: enforced privacy and privacy in the presence of others. We believe that these privacy chal-lenges are vital for secure eHealth systems, and more research is needed to understand these challenges. We propose to use formal techniques to understand and define these new privacy notions in a precise and unam-biguous manner, and to build an efficient verification framework.

    Formal Analysis of a Proof-of-Stake Blockchain

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    Blockchain technology relies on consensus algorithms to resolve conflicts in Byzantine environments. New blockchain algorithms are rapidly designed and implemented without a properly conducted formal analysis and verification. In this paper, we conducted a study on Tendermint which is a proof of-stake consensus algorithm. We verified that the consensus protocol is deadlock-free and is able to reach consensus when at least 2/3 of the network is in agreement. We also proved that a minority set of nodes that compose more than 1/3 of the network is enough to censor the majority of the network and prevent the network from reaching consensus and conclude that the algorithm has some shortcomings on availability

    Callback2Vec: Callback-aware hierarchical embedding for mobile application

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    Although numerous embedding approaches have been proposed for code representation of mobile applications, insufficient attention has been paid to its essential running nature: event-driven. As a result, the contextual semantics of event-driven callbacks re hardly captured. Existing solutions either discard the information of event callbacks such as their sequences, or simply treat event callbacks as ordinary APIs. Both of the solutions deviate from the actual running behavior of the applications and thus suffer from critical information loss of the callback contexts. To address the problem, in this paper, a callback based hierarchical embedding approach Callback2Vec is proposed, in which ordinary APIs and callbacks are distinguished and tackled at different levels in a top-down fashion. As such, the contextual semantics of callbacks can be reasonably represented by the embedding vectors. In particular, a fine-grained callback-sequence-generation algorithm is devised to capture the running behavior of callbacks. To evaluate the representation capability of Callback2Vec, a systematic analysis targeting at the embedding results is conducted, whereby the conventional embedding characteristics are rigorously investigated and new implications are identified. Of significance, the proposed embedding approach has been validated to be capable of providing novel solutions for typical downstream applications, through comprehensive experiments with large scale public datasets
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