146 research outputs found

    Q-learning Based Optimal False Data Injection Attack on Probabilistic Boolean Control Networks

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    In this paper, we present a reinforcement learning (RL) method for solving optimal false data injection attack problems in probabilistic Boolean control networks (PBCNs) where the attacker lacks knowledge of the system model. Specifically, we employ a Q-learning (QL) algorithm to address this problem. We then propose an improved QL algorithm that not only enhances learning efficiency but also obtains optimal attack strategies for large-scale PBCNs that the standard QL algorithm cannot handle. Finally, we verify the effectiveness of our proposed approach by considering two attacked PBCNs, including a 10-node network and a 28-node network

    Knowledge landscape of tumor-associated macrophage research: A bibliometric and visual analysis

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    Background and aimsTumor-associated macrophage (TAM) is a highly abundant immune population in tumor microenvironment, which plays an important role in tumor growth and progression. The aim of our study was to explore the development trends and research hotspots of TAM by bibliometric method.MethodsThe publications related to TAM were obtained from the Web of Science Core Collection database. Bibliometric analysis and visualization were conducted using VOSviewer, CiteSpace and R software.ResultsA total of 6,405 articles published between 2001 and 2021 were included. The United States and China received the most citations, whereas the University of Milan, the university of California San Francisco and Sun Yat-sen University were the main research institutions. Mantovani, Alberto from Humanitas University was the most productive authors with the most citations. Cancer Research published the most articles and received the most co-citations. Activation, angiogenesis, breast cancer, NF-κB and endothelial growth factor were important keywords in TAM research. Among them, PD-1/L1, nanoparticle, PI3Kγ, resistance and immune microenvironment have become the focus of attention in more recent research.ConclusionsThe research on TAM is rapidly evolving with active cooperation worldwide. Anticancer therapy targeting TAM is emerging and promising area of future research, especially in translational application. This may provide guidance and new insights for further research in the field of TAM

    Mapping the Intel Last-Level Cache

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    Modern Intel processors use an undisclosed hash function to map memory lines into last-level cache slices. In this work we develop a technique for reverse-engineering the hash function. We apply the technique to a 6-core Intel processor and demonstrate that knowledge of this hash function can facilitate cache-based side channel attacks, reducing the amount of work required for profiling the cache by three orders of magnitude. We also show how using the hash function we can double the number of colours used for page-colouring techniques
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