scholarly journals Fast Response to Infection Spread and Cyber Attacks on Large-Scale Networks

2012 ◽  
Author(s):  
Ilya Safro ◽  
Sven Leyffer
Keyword(s):  
Large Scale ◽  
Fast Response ◽  
Cyber Attacks ◽  
Large Scale Networks ◽  
Infection Spread

scholarly journals Hierarchical Multi-Stage Cyber Attack Scenario Modeling Based on G&E Model for Cyber Risk Simulation Analysis

2020 ◽  
Vol 10 (4) ◽  
pp. 1426
Author(s):  
Myung Kil Ahn ◽  
Yong Hyun Kim ◽  
Jung-Ryun Lee
Keyword(s):  
Large Scale ◽  
Simulation Analysis ◽  
Cyber Attacks ◽  
Cyber Attack ◽  
Scenario Modeling ◽  
Course Of Action ◽  
Multi Stage ◽  
Attack Scenario ◽  
Analysis System ◽  
Large Scale Networks

With the advancement in cyber-defense capabilities, cyber attacks have continued to evolve like living creatures to breach security. Assuming the possibility of various enemy attacks, it is necessary to select an appropriate course of action by proactively analyzing and predicting the consequences of a particular security event. Cyber attacks, especially in large-scale military network environments, have a fatal effect on security; therefore, various experiments and analyses must be conducted to establish the necessary preparations. Herein, we propose a hierarchical multi-stage cyber attack scenario modeling based on the goal and effect (G&E) model and analysis system, which enables expression of various goals of attack and damage effects without being limited to specific type. The proposed method is applicable to large-scale networks and can be utilized in various scenario-based cyber combat experiments.

scholarly journals Contribution of Ionotropic Glutamatergic Receptors to Excitability and Attentional Signals in Macaque Frontal Eye Field

2021 ◽  
Author(s):  
Miguel Dasilva ◽  
Christian Brandt ◽  
Marc Alwin Gieselmann ◽  
Claudia Distler ◽  
Alexander Thiele
Keyword(s):  
Attentional Control ◽  
Large Scale ◽  
Neuronal Excitability ◽  
Cell Types ◽  
Receptor Activation ◽  
Frontal Eye Field ◽  
Control Signals ◽  
Cognitive Operations ◽  
Eye Field ◽  
Large Scale Networks

Abstract Top-down attention, controlled by frontal cortical areas, is a key component of cognitive operations. How different neurotransmitters and neuromodulators flexibly change the cellular and network interactions with attention demands remains poorly understood. While acetylcholine and dopamine are critically involved, glutamatergic receptors have been proposed to play important roles. To understand their contribution to attentional signals, we investigated how ionotropic glutamatergic receptors in the frontal eye field (FEF) of male macaques contribute to neuronal excitability and attentional control signals in different cell types. Broad-spiking and narrow-spiking cells both required N-methyl-D-aspartic acid and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor activation for normal excitability, thereby affecting ongoing or stimulus-driven activity. However, attentional control signals were not dependent on either glutamatergic receptor type in broad- or narrow-spiking cells. A further subdivision of cell types into different functional types using cluster-analysis based on spike waveforms and spiking characteristics did not change the conclusions. This can be explained by a model where local blockade of specific ionotropic receptors is compensated by cell embedding in large-scale networks. It sets the glutamatergic system apart from the cholinergic system in FEF and demonstrates that a reduction in excitability is not sufficient to induce a reduction in attentional control signals.

scholarly journals How does the position of firms in the supply chain affect their performance? An empirical study

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Siddharth Arora ◽  
Alexandra Brintrup
Keyword(s):  
Supply Chain ◽  
Empirical Data ◽  
Large Scale ◽  
Individual Performance ◽  
Supply Network ◽  
Supply Chain Networks ◽  
Focal Firm ◽  
Cooperative Competition ◽  
Large Scale Networks ◽  
The Relationship

AbstractThe relationship between a firm and its supply chain has been well studied, however, the association between the position of firms in complex supply chain networks and their performance has not been adequately investigated. This is primarily due to insufficient availability of empirical data on large-scale networks. To addresses this gap in the literature, we investigate the relationship between embeddedness patterns of individual firms in a supply network and their performance using empirical data from the automotive industry. In this study, we devise three measures that characterize the embeddedness of individual firms in a supply network. These are namely: centrality, tier position, and triads. Our findings caution us that centrality impacts individual performance through a diminishing returns relationship. The second measure, tier position, allows us to investigate the concept of tiers in supply networks because we find that as networks emerge, the boundaries between tiers become unclear. Performance of suppliers degrade as they move away from the focal firm (i.e., Toyota). The final measure, triads, investigates the effect of buying and selling to firms that supply the same customer, portraying the level of competition and cooperation in a supplier’s network. We find that increased coopetition (i.e., cooperative competition) is a performance enhancer, however, excessive complexity resulting from being involved in both upstream and downstream coopetition results in diminishing performance. These original insights help understand the drivers of firm performance from a network perspective and provide a basis for further research.

scholarly journals BFL: a node and edge betweenness based fast layout algorithm for large scale networks

2009 ◽  
Vol 10 (1) ◽  
pp. 19 ◽  
Author(s):  
Tatsunori B Hashimoto ◽  
Masao Nagasaki ◽  
Kaname Kojima ◽  
Satoru Miyano
Keyword(s):  
Large Scale ◽  
Layout Algorithm ◽  
Edge Betweenness ◽  
Large Scale Networks
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