Majed Haddad's research while affiliated with Université d´Avignon et des Pays du Vaucluse and other places

Wireless jamming attacks have recently been a subject of several researches, due to the exposed nature of the wireless medium. This paper studies the anti-jamming resistance in the presence of several attackers. Two kind of jammers are considered, smart jammers which have the ability to sense the legitimate signal power and regular jammers which don't have this ability. An Anti Multi-Jamming based Power Control problem modeled as a non-zero-sum Game is suggested to study how the transmitter can adjust its signal power against several jamming attacks. A closed-form expression of Nash Equilibrium is derived when players actions are taken simultaneously. In addition, a Stackelberg Equilibrium closed-form expression is derived when the hierarchical behavior between the transmitter and jammers is assumed. Simulation results show that the proposed scheme can enhance the anti-jamming-resistance against several attackers. Furthermore, this study proves that on the transmitter side, the most dangerous jammer is considered to have the highest ratio between channel gain and jamming cost. Finally, based on the Q-Learning technique, the transmitter can learn autonomously without knowing the patterns of attackers.

Due to the broadcast nature of the wireless medium, mechanisms are needed to deal with the problem of jamming attacks. This paper proposes a Large Anti-Jamming Cooperation scheme, in which, several anti-jammers are considered to help a secondary user sending signal to the receiver side in the presence of smart jamming attacks. A hierarchical behavior among players is considered to derive the Stackelberg Equilibrium (SE) closed form. At SE, we proved that on the transmitter side, the cumulative attacks are perceived as a single attack from the jammer that has the highest Jamming Efficiency Ratio, likewise, the cumulative anti-attacks are observed as a single reaction from the anti-jammer having the highest Cooperation Efficiency Ratio. On the other hand, anti-jammers that share the highest ratio are active and cooperate with each other while the remaining anti-jammers are inactive. Finally, by means of simulation results we have clearly showed that the transmitter can efficiently enhance its communication performance in the presence of several jamming attacks, especially when the inability of jammers to sense signal powers perfectly is considered.

Jamming mitigation as a means to countermeasure jamming attacks has recently been a subject to several research. Since the battery life is indeed important in any wireless system, and as it's directly related with the transmission activity, this paper proposes a Pricing Wireless Random Channel Access (P-WRCA) mechanism and compares it with the Wireless Random Channel Access (WRCA) mechanism during Random Reactive (RR) jamming attacks. The aim is to make it difficult for a jammer to exploit the aggressive behavior of mobile users. We model, analyze the selfish behavior of mobile users in the presence of a RR jammer so as to find the trade-off between selfish behavior and jamming-resistant. The results obtained from the proposed mechanism are presented to show the network resistance to RR attacks. Finally, we believe that P-WRCA may have wider usage in wireless networking than what has been explored in this paper.

Due to the broadcast nature of the shared medium, wireless communications become more vulnerable to malicious attacks. In this paper, we tackle the problem of jamming in wireless network when the transmission of the jammer and the transmitter occur with a non-zero cost. We focus on a jammer who keeps track of the re-transmission attempts of the packet until it is dropped. Firstly, we consider a power control problem following a Nash Game model, where all players take action simultaneously. Secondly, we consider a Stackelberg Game model, in which the transmitter is the leader and the jammer is the follower. As the jammer has the ability to sense the transmission power, the transmitter adjusts its transmission power accordingly, knowing that the jammer will do so. We provide the closed-form expressions of the equilibrium strategies where both the transmitter and the jammer have a complete information. Thereafter, we consider a worst case scenario where the transmitter has an incomplete information while the jammer has a complete information. We introduce a Reinforcement Learning method, thus, the transmitter can act autonomously in a dynamic environment without knowing the above Game model. It turns out that despite the jammer ability of sensing the active channel, the transmitter can enhance its efficiency by predicting the jammer reaction according to its own strategy

In this paper, we tackle the problem of a sequential routing game where multiple users coexist and competitively send their traffic to a destination over a line. The users arrive at time epoch with a given capacity. Then, they ship their demands over time on a shared resource. The state of players evolve according to whether they decide to transmit or not. The decision of each user is thus spatio-temporal control. We provide an explicit expression of the equilibrium of such systems and compare it to the global optimum case. In particular, we determine the expression of price of anarchy of such scheme and identify a Braess-type paradox in the context of sequential routing game.

In this paper, we consider a routing game in a network that contains lossy links. We consider a multi-objective problem where the players have each a weighted sum of a delay cost and a cost for losses. We compute the equilibrium and optimal solution (which are unique). We discover here in addition to the classical Kameda type paradox another paradoxical behavior in which higher loss rates have a positive impact on delay and therefore higher quality links may cause a worse performance even in the case of a single player.