40,363 research outputs found

    General conditioned and aimed information on fuzzy setting

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    In this paper our investigation on aimed information, started in 2011, will be completed on fuzzy setting. Here will be given a form of information for fuzzy setting, when it is conditioned and aimed. This information is called "general", because it is defined without using probability or fuzzy measure

    Ground-state Stabilization of Open Quantum Systems by Dissipation

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    Control by dissipation, or environment engineering, constitutes an important methodology within quantum coherent control which was proposed to improve the robustness and scalability of quantum control systems. The system-environment coupling, often considered to be detrimental to quantum coherence, also provides the means to steer the system to desired states. This paper aims to develop the theory for engineering of the dissipation, based on a ground-state Lyapunov stability analysis of open quantum systems via a Heisenberg-picture approach. Algebraic conditions concerning the ground-state stability and scalability of quantum systems are obtained. In particular, Lyapunov stability conditions expressed as operator inequalities allow a purely algebraic treatment of the environment engineering problem, which facilitates the integration of quantum components into a large-scale quantum system and draws an explicit connection to the classical theory of vector Lyapunov functions and decomposition-aggregation methods for control of complex systems. The implications of the results in relation to dissipative quantum computing and state engineering are also discussed in this paper.Comment: 18 pages, to appear in Automatic

    A First Look at the Crypto-Mining Malware Ecosystem: A Decade of Unrestricted Wealth

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    Illicit crypto-mining leverages resources stolen from victims to mine cryptocurrencies on behalf of criminals. While recent works have analyzed one side of this threat, i.e.: web-browser cryptojacking, only commercial reports have partially covered binary-based crypto-mining malware. In this paper, we conduct the largest measurement of crypto-mining malware to date, analyzing approximately 4.5 million malware samples (1.2 million malicious miners), over a period of twelve years from 2007 to 2019. Our analysis pipeline applies both static and dynamic analysis to extract information from the samples, such as wallet identifiers and mining pools. Together with OSINT data, this information is used to group samples into campaigns. We then analyze publicly-available payments sent to the wallets from mining-pools as a reward for mining, and estimate profits for the different campaigns. All this together is is done in a fully automated fashion, which enables us to leverage measurement-based findings of illicit crypto-mining at scale. Our profit analysis reveals campaigns with multi-million earnings, associating over 4.4% of Monero with illicit mining. We analyze the infrastructure related with the different campaigns, showing that a high proportion of this ecosystem is supported by underground economies such as Pay-Per-Install services. We also uncover novel techniques that allow criminals to run successful campaigns.Comment: A shorter version of this paper appears in the Proceedings of 19th ACM Internet Measurement Conference (IMC 2019). This is the full versio
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