How to Defend a Network?

Modern economies rely heavily on their infrastructure networks. These networks face threats ranging from natural disasters to human attacks. As networks are pervasive, the investments needed to protect them are very large; this motivates the study of targeted defence. What are the ���key�� nodes to defend to maximize functionality of the network? What are the incentives of individual nodes to protect themselves in a networked environment and how do these incentives correspond to collective welfare? We provide a characterization of equilibrium attack and defence in terms of two classical concepts in graph theory ��� separators and transversals. We study the welfare costs of decentralized defence. We apply our results to the defence of the US Airport Network and the London Underground

How to Defend a Network?

Modern economies rely heavily on their infrastructure networks. These networks face threats ranging from natural disasters to human attacks. As networks are pervasive, the investments needed to protect them are very large; this motivates the study of targeted defence. What are the ���key�� nodes to defend to maximize functionality of the network? What are the incentives of individual nodes to protect themselves in a networked environment and how do these incentives correspond to collective welfare? We provide a characterization of equilibrium attack and defence in terms of two classical concepts in graph theory ��� separators and transversals. We study the welfare costs of decentralized defence. We apply our results to the defence of the US Airport Network and the London Underground

Using fuzzy set approach in multi-attribute automated auctions

This paper designs a novel fuzzy attributes and competition based bidding strategy (FAC-Bid), in which the final best bid is calculated on the basis of the assessment of multiple attributes of the goods and the competition for the goods in the market. The assessment of attributes adapts the fuzzy sets technique to handle uncertainty of the bidding process. The bidding strategy also uses and determines competition in the market (based on the two factors i.e. no. of the bidders participating and the total time elapsed for an auction) using Mamdani's Direct Method. Then the final price of the best bid will be determined based on the assessed attributes and the competition in the market using fuzzy reasoning technique

How do you defend a network?

Copyright © 2017 The Authors. Modern economies rely heavily on their infrastructure networks. These networks face threats ranging from natural disasters to human attacks. As networks are pervasive, the investments needed to protect them are very large; this motivates the study of targeted defense. What are the “key” nodes to defend to maximize functionality of the network? What are the incentives of individual nodes to protect themselves in a networked environment and how do these incentives correspond to collective welfare?. We first provide a characterization of optimal attack and defense in terms of two classical concepts in graph theory: separators and transversals. This characterization permits a systematic study of the intensity of conflict (the resources spent on attack and defense) and helps us identify a new class of networks—windmill graphs—that minimize conflict. We then study security choices by individual nodes. Our analysis identifies the externalities and shows that the welfare costs of decentralized defense in networks can be very large.Both authors thank the European Research Area Complexity Net for financial support. Marcin Dziubi ́nskiwas supported by the Strategic Resilience of Networks project realized within the Homing Plus program ofthe Foundation for Polish Science and was co-financed by the European Union from the Regional Devel-opment Fund within Operational Programme Innovative Economy (grants for innovation). Sanjeev Goyalacknowledges financial support from a Keynes Fellowship and the Cambridge INET Institute

Contagion Risk and Network Design

Individuals derive bene ts from their connections, but these may, at the same time, transmit external threats. Individuals therefore invest in security to protect themselves. However, the incentives to invest in security depend on their network exposures. We study the problem of designing a network that provides the right individual incentives. Motivated by cybersecurity, we rst study the situation where the threat to the network comes from an intelligent adversary. We show that, by choosing the right topology, the designer can bound the welfare costs of decentralized protection. Both over-investment as well as under-investment can occur depending on the costs of security. At low costs, over-protection is important: this is addressed by discon- necting the network into two unequal components and sacri cing some nodes. At high costs, under-protection becomes salient: it is addressed by disconnecting the network into equal components. Motivated by epidemiology, we then turn to the study of random attacks. The over-protection problem is no longer present, whereas under-protection problems is mitigated in a diametrically opposite way: namely, by creating dense networks that expose the individuals to the risk of contagion

Competitive contagion in networks

We develop a game-theoretic framework for the study of competition between firms who have budgets to “seed” the initial adoption of their products by consumers located in a social network. We identify a general property of the adoption dynamics — namely, decreasing returns to local adoption — for which the inefficiency of resource use at equilibrium (the Price of Anarchy) is uniformly bounded above, across all networks. We also show that if this property is violated, even the Price of Stability can be unbounded, thus yielding sharp threshold behavior for a broad class of dynamics. We provide similar results for a new notion, the Budget Multiplier, that measures the extent to which the imbalances in player budgets can be amplified at equilibrium

Conflict and Networks

Con flict remains a central element in human interaction. Networks - social, economic and infrastructure - are a defining feature of society. The two intersect in a wide range of empirical contexts. This motivates the recent interest in con flict and networks. The aim of the survey is to present the general themes, provide a survey of the nascent research and point to a number of interesting open questions

Conflict and Networks

Con flict remains a central element in human interaction. Networks - social, economic and infrastructure - are a defining feature of society. The two intersect in a wide range of empirical contexts. This motivates the recent interest in con flict and networks. The aim of the survey is to present the general themes, provide a survey of the nascent research and point to a number of interesting open questions

A quantitative comparison of sRNA-based and protein-based gene regulation

Small, non-coding RNAs (sRNAs) play important roles as genetic regulators in prokaryotes. sRNAs act post-transcriptionally via complementary pairing with target mRNAs to regulate protein expression. We use a quantitative approach to compare and contrast sRNAs with conventional transcription factors (TFs) to better understand the advantages of each form of regulation. In particular, we calculate the steady-state behavior, noise properties, frequency-dependent gain (amplification), and dynamical response to large input signals of both forms of regulation. While the mean steady-state behavior of sRNA-regulated proteins exhibits a distinctive tunable threshold-linear behavior, our analysis shows that transcriptional bursting leads to significantly higher intrinsic noise in sRNA-based regulation than in TF-based regulation in a large range of expression levels and limits the ability of sRNAs to perform quantitative signaling. Nonetheless, we find that sRNAs are better than TFs at filtering noise in input signals. Additionally, we find that sRNAs allow cells to respond rapidly to large changes in input signals. These features suggest a niche for sRNAs in allowing cells to transition quickly yet reliably between distinct states. This functional niche is consistent with the widespread appearance of sRNAs in stress-response and quasi-developmental networks in prokaryotes.Comment: 26 pages, 8 figures; accepted for publication in Molecular Systems Biolog