Game theoretic models of networks security

Decision making in the context of crime execution and crime prevention can be successfully investigated with the implementation of game-theoretic tools. Evolutionary and mean-field game theory allow for the consideration of a large number of interacting players organized in social and behavioural structures, which typically characterize this context. Alternatively, `traditional' game-theoretic approaches can be applied for studying the security of an arbitrary network on a two player non-cooperative game. Theoretically underpinned by these instruments, in this thesis we formulate and analyse game-theoretic models of inspection, corruption, counter- terrorism, patrolling, and similarly interpreted paradigms. Our analysis suggests optimal strategies for the involved players, and illustrates the long term behaviour of the introduced systems. Our contribution is towards the explicit formulation and the thorough analysis of real life scenaria involving the security in network structures

Corruption and botnet defense : a mean field game approach

Recently developed toy models for the mean-field games of corruption and botnet defence in cyber-security with three or four states of agents are extended to a more general mean-field-game model with 2d states, d∈N . In order to tackle new technical difficulties arising from a larger state-space we introduce new asymptotic regimes, namely small discount and small interaction asymptotics. Moreover, the link between stationary and time-dependent solutions is established rigorously leading to a performance of the turnpike theory in a mean-field-game setting

Exchange networks, markets and trust

Network-based transactions are attractive as a system for economic exchange because they give network members greater protection against opportunism and exchange hazards compared to more anonymous market transactions. At the same time, net- works restrict the possibilities to exploit economies of scale and other efficiency enhancing properties of markets. When the problem-solving capacity of networks do not make up for the losses generated by not trading with outsiders, trust is important to promote transactions among strangers in the anonymously market. This paper offers an economic analysis of this idea. With the help of a social evolutionary model, it is also demonstrated that mutual trust relations can survive in the anonymous market, even when there is a clear danger of opportunism, and the conventional mechanisms like repetitions and contracts are ruled out

Country output and financial black holes: public–private partnerships and the Laffer curve, fiscal corruption risk, and bailout rate of non-performing loans

This study develops the link between output and fiscal corruption risk in public–private partnership (PPP) schemes and the government bailout rate of non-performing loans (NPLs). The model assumes that corruption is widespread in such public investment programs. The objective functions of the government and PPP firms include fiscal corruption risk, given that the PPP firm and tax inspector can ‘effectively’ negotiate bribes. The model solves for the optimal country output (i.e., aggregate productivity) according to the Lagrange method. Long-term prospects are introduced to solve the problem with commercial banks, as most PPPs borrow from commercial banks. The results reaffirm that tax policy can exacerbate the country’s output loss. Although the equilibria between aggregate productivity and the Laffer curve lack a direct link to fiscal corruption risk, their magnitude does and depends on the number of PPPs. The PPP transfer from the government in period 2 and the number of PPPs rather than government expenditure in period 1 and the Laffer curve (tax revenues) mainly determines the bailout rate of PPPs’ NPLs. The article concludes with suggestions to prevent tax evasion and fiscal corruption risk in PPP schemes by using a cluster of cooperation, and recommends further research into cultural aspects

Norm violation versus punishment risk in a social model of corruption

We analyze the onset of social-norm-violating behaviors when social punishment is present. To this aim, a compartmental model is introduced to illustrate the flows among the three possible states: Honest, corrupt, and ostracism. With this simple model we attempt to capture some essential ingredients such as the contagion of corrupt behaviors to honest agents, the delation of corrupt individuals by honest ones, and the warning to wrongdoers (fear like that triggers the conversion of corrupt people into honesty). In nonequilibrium statistical physics terms, the former dynamics can be viewed as a non-Hamiltonian kinetic spin-1 Ising model. After developing in full detail its mean-field theory and comparing its predictions with simulations made on regular networks, we derive the conditions for the emergence of corrupt behaviors and, more importantly, illustrate the key role of the warning-to-wrongdoers mechanism in the latter