Game Theory Based Research On Several Key Problems Of Wireless Sensor Networks Security

Wireless Sensor Networks (WSNs) are composed of a large number of micro and low-priced sensor nodes deployed in sensing fields, whose aim is, cooperatively and instantly, to monitor, sense, and collect varieties of data information on monitoring objects, such as temperature, humidity, and air pressure and so on. By the method of wireless communications, these sensor nodes form a self-organized, self-adapted, and multi-hoped network system that is intelligent and transmits information sensed to administrators through the Base Station. It has been known that WSNs can be applied in a broad of fields, such as industry, agriculture, city control, medical treatment, environmental monitoring, and military and so forth.As task networks, WSNs not only transfer data sensed by sensor nodes, but also perform the fusion of these data and control coordinately different missions. During the process of these works, secure problems of how to guarantee confidentiality of performing tasks, reliability of producing data, and security of transmitting data, have been concerned by researchers. These problems have been a key factor to determine the development of WSNs.Game theory is a sort of mathematical tools to study decision problems between two players or among multiple ones, which can be a novel way for researching secure problems in WSNs. There are characteristics such as self-organization, lacking control center, dynamic topology, and limited sources in the typical WSNs. These characteristics will influence the behavior decision of sensor nodes during their communications. Then, the problem that will arise is:which strategy is optimal during the decision of sensor nodes? Sensor nodes maybe behave selfishly to seek their decisions only beneficial to their own profits, or even act maliciously and thus select their decisions to break the performance of the whole WSNs. These cases above can be solved by different non-cooperative games including signaling game, stochastic game, differential game, and so on. In addition, evolutionary game can be employed to explore the dynamic evolution of sensor nodes’behaviors. Therefore, applying game theory provides practical new thoughts to study several key secure problems in WSNs, which has become an important research direction full of future prospects.This dissertation is to target important research fields in WSNs security involving intrusion detection, trust, malware propagation, and survivability. Correspondingly, with game theory, some key problems including when to launch intrusion detection system (IDS), how to evolve trust decisions, how to propagate and control malwares, and how to predict attacked behaviors in survivability evaluation, are solved, respectively.(1) Signaling game based strategies optimal to IDS in WSNsAs an important shield to WSNs security, IDS is able to defend actively inside and outside attacks. IDS in WSNs can isolate those malicious sensor nodes to make following routings not pass them, and thus the loss resulted by malicious sensor nodes will be alleviated. However, plenty of computation resources must be required to make use of the IDS in WSNs. Due to limited resources of sensor nodes, it is not an optimal strategy that renders the IDS be in work state over time. Therefore, the strategy of when to launch IDS in WSNs has become a key factor to apply IDS effectively.The main results in this part lie as follows. 1) An Intrusion Detection Game based on the signaling game is formulated to study strategies of malicious sensor nodes and IDS agents, which satisfies such a situation that the IDS agent is uncertain about the type of its opponent;2) The theorems of equilibriums of the Intrusion Detection Game are set up and proven, which provide the optimal strategy for the IDS agent to decide whether to take Defend or Idle. That is, the IDS agents are not always on Defend and thus their energy are saved;3) Based on the Perfect Bayesian equilibrium, the IDS agent and the corresponding algorithm are designed;4) Simulation experiments to support the efficiency of the WSNs Intrusion Detection Game are constructed.(2) Evolutionary game based trust evolution dynamics of sensor nodes in WSNsRecently, the security mechanism based on trust, one of security technology, has been applied in WSNs. Contrast to cryptographic measures, trust among sensor nodes in WSNs will help other sensor nodes construct their confidence, promote their cooperation, and depress their risks to cooperate with others. Generally, trust proofs must be collected and stored in a trust management system. The trust level values of sensor nodes are considered to be computed and actions between sensor nodes are recorded. These processes satisfying the characteristic of dynamics are repeatedly performed and evolved. Based on a trust management system, a sensor node can determine whether to cooperate with others by making a trust decision. Moreover, disclosing principles of trust evolving is able to provide supports to quantify trust level values. Therefore, the trust decision of sensor nodes and its dynamics that will be studied constitute building blocks to secure and stabilize the whole WSNs.The main results in this part lie as follows.1) A WSNs trust game among sensor nodes is formulated, which is able to reflect properly the utilities of sensor nodes when they are making their decisions;2) It has been found that the incentive mechanism bound with the trust level of a sensor node is able to reduce greatly the rate of sensor nodes selecting the strategy Distrust and thus improve effectively WSNs in their security as well as stability;3) The theorems of evolutionarily stable strategies related to the trust game are attained, which provide various conditions to achieve these strategies and can be used to set up the theoretical foundation to guide the design of a trust management system for WSNs.(3) Differentia! game based optimal strategies against malware propagation in WSNsSimilar to other network environments, malware propagation in WSNs has become one of severe security problems. Recent studies have shown that malwares are prone to propagate in WSNs. Once these malwares have spread broadly due to software and hardware bugs of sensor nodes, they are able to listen in data sensed by sensor nodes, or even render sensor nodes dysfunctional by exhausting their energy reserves. These malicious behaviors will affect seriously confidentiality of data in WSNs as well as stability of the whole WSNs. In order to be able to devise the corresponding control strategies, modeling the propagation of the malware in WSNs should be considered firstly. Exactly, the malware propagation model is fully able to reflect the actual propagation process made by malwares in WSNs, to disclose malware propagation laws, and to predict possible threats. It thus provides a theoretical basis for controlling the malware spread in WSNs. Therefore, solving the problem of how to explore the malware propagation and make optimal strategies to control malwares effectively is important to guarantee the security of the whole WSNs.The main results in this part lie as follows.1) A malware propagation model by developing the epidemic theory is constructed, which is able to reflect the facts that sensor nodes are required to make themselves into the scheduled sleep mode for saving their energy, and that any sensor nodes will be dead after exhausting their power;2) A two-player zero-sum malware-defense differential game is formulated, which is able to reflect the interactions between the system and the malware, and the overall cost inflicted by the system and the malware;3) The interesting optimal strategies for the system and the malware are attained, respectively, which are able to suppress the propagation of the malware evidently and, due to their convenience to implement, are very suitable for sensor nodes.(4) Stochastic game based survivability evaluation towards attacked WSNsWSNs survivability is to reflect the ability to finish timely key missions when some sensor nodes have emerged hardware faults or suffered from malicious attacks. Satisfying high survivability has become an eventual aim for WSNs researchers. Currently, general survival technologies for WSNs consist of fault-tolerance, intrusion-tolerance, and self-regeneration and so on. In order to employ these survival technologies, the network survivability evaluation to realize quantity analysis must be performed firstly. The specific evaluation values attained can describe accurately the survival status of WSNs, and provide the decision basis for launching timely corresponding technologies to improve the survivability of WSNs. Therefore, solving the problem of how to measure the survivability is important to design a highly survival WSNs.The main results in this part lie as follows.1) A two-player zero-sum attack-prediction stochastic game between the attacker and the system is formulated, which is able to attain the attack probabilities adopted by the attacker in different states and set up the relation between the intention of attack behaviors and the randomness of continuous-time Markov chain (CTMC);2) The lifetime model of an attacked sensor node with CTMC is set up, which is able to depict the different states. Thus, the Mean Time to Failure (MTTF) of an attacked sensor node can be computed;3) A mechanism of survivability evaluation for attacked WSNs is constructed, which is composed of the reliability, survival lifetime, and availability in the steady state. These survivability evaluation metrics will be used to set up the theoretical foundation to guide the design of highly survival WSNs.In summary, game theory has provided a novel way for exploring problems of WSNs security. Results obtained above will give supports to construct intelligent cities and are significant to improve WSNs fundamental theory and methods in fields of intrusion detection, trust, malware propagation, and survivability.