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In this paper, we propose a novel pricing mechanism to enhance the performance of the Slotted ALOHA mechanism combined with ZigZag Decoding (SA-ZD). We model the system using a stochastic game approach where the game state is given as a Markov process. We assume a cooperative game framework where users seek to optimize the same utility function. In our previous pricing mechanism [1], we associated a cost C ∊ [0; 1] for every transmission and retransmission attempt. Thus, if the transmission succeeds, the user receives a reward equal to 1°C. Otherwise, in the case of collision, he pays a penalty equal to C. Following this approach, users prefer to not take the risk of paying the penalty cost, which means they choose to wait rather than transmitting, especially in heavy traffic conditions. Even though it seems optimal to not transmit in such conditions, our results show that this behavior yields a dramatic decrease in the system performance. Besides, it leads to an inherent tradeoff between the backlogged and newly arrived traffic. Toward this end, we propose in this paper a novel pricing strategy where we associate a cost not only to transmission attempts but also to the idle event (i.e when no one is transmitting). Moreover, we address the tradeoff problem by associating different costs Cb and Cs, respectively, to backlogged and newly arrived packets. Therefore, when a successful transmission is going through the channel, users pay a cost denoted by Cs or Cb. If a collision occurs, they pay a cost Cc, and when no one is transmitting, they pay the idling cost Cidle. Compared to the old pricing mechanism, our results show that the proposed approach achieves the best performance and maintains a fairness level between backlogged and newly arrived packets. [ABSTRACT FROM AUTHOR]

In a complex network as a cloud computing environment, security is becoming increasingly based on deception techniques. To date, the static nature of cyber networks offers to adversaries good opportunities to systematically study the network environment, launch a cyber-attack effortlessly and wide-spread and finally defeat the target system. In order to resolve the limitations of the traditional security measures as intrusion prevention or detection systems, firewall, access list, etc., which did not change the attack surface and cannot avoid zero-days attacks, technics that provide dynamic defense, such virtual machine migration and honeypot should be deployed. Despite this, with a virtual machine migration technique, not all virtual machines' migration between servers enhances security considerably. In this paper, we propose an integrated defense system combining virtual machine migration and honeypot. The effectiveness of the proposed system is discussed in terms of security policies. In addition, our proposed model determines the potential attack paths quantitatively then classifies them into two sub-sets: attack paths explored only and attack paths explored and exploited based on the black box intrusion steps. Thus, to model the interaction attacker–defender, the attack graph combined with the stochastic game theory is used. Finally, we carry out some numerical results to demonstrate the effectiveness of the proposed security game model. [ABSTRACT FROM AUTHOR]

In Slotted ALOHA (SA), mobile nodes tend to be more aggressive when they compete to get access to the common channel, which leads to a dramatic decreases of the Quality of Service (QoS). In this paper, we analyze the Slotted ALOHA and Slotted ALOHA combined with ZigZag Decoding (SA-ZD) within a stochastic game framework. First, we start with the cooperative model of the proposed mechanism in which we propose several approach to optimize the system. Then, we model the system by a non-cooperative game using a bi-dimensional Markov chain that integrates the effect of ZigZag Decoding (ZD). We then propose an adjustable transmission cost to compromise between throughput and the delay of backlogged packets. All found results show that our approach improves significantly the QoS of the system. [ABSTRACT FROM AUTHOR]

In Cloud Computing environment, the allocation of virtual machines (VMs) to clients without taking into consideration the programs that they execute in their VMs could be a great threat to the entire cloud environment. Indeed the hypervisor cannot isolate the VMs totally and these machines have a lot of vulnerabilities that could be exploited then spread the attack in the other servers even if there is such an intrusion prevention or detection system. For this reason the process of monitoring the file that should be executed in an allocated VM is an important strategy to mitigate such a threat. The sandbox security mechanism is one of the solutions that are used in complex environment to isolate malicious or unknown files for execution than allow it thereafter to be used in a real context. In this paper, a Bayesian game theoretic approach is used in order to take into consideration the type of the client based on his previous activities to predict his actions and to determine in which case the monitoring process should be used. For this reason, we model the system as a Bayesian non-cooperative game firstly, then we resolve the game and finally we provide some numerical results to predict user's action and show the appropriate actions that should be taken by the administrator. [ABSTRACT FROM AUTHOR]

In wireless communication networks, when the workload increases, sources become more aggressive at the equilibrium in the game setting in comparison with the team problem by using slotted Aloha mechanism. Consequently, more packets are in collision and are lost. To reduce these phenomena and to enhance the performance of the networks, we propose to combine ZigZag decoding approach with non cooperative slotted Aloha mechanism. This approach was introduced in our previous work based on the cooperative slotted Aloha mechanism. The obtained results showed that this approach has significantly improved the cooperative slotted Aloha mechanism and gave best results for the throughput and delay. In this paper, we analyze the impact of combining non cooperative slotted Aloha and ZigZag Decoding. We model the system by a two dimensional Markov chain that integrates the effect of ZigZag decoding. The states of the Markov chain describe the number of backlogged packets among the users. We use a stochastic game to achieve our objective; we evaluate and compare the performances parameters of the proposed approach with those of a simple slotted Aloha mechanism. All found results show that our approach improves the performance parameters of the system. [ABSTRACT FROM AUTHOR]