Generalized Colonel Blotto Game

Competitive resource allocation between adversarial decision makers arises in a wide spectrum of real-world applications such as in communication systems, cyber-physical systems security, as well as financial, political, and electoral competition. As such, developing analytical tools to model and analyze competitive resource allocation is crucial for devising optimal allocation strategies and anticipating the potential outcomes of the competition. To this end, the Colonel Blotto game is one of the most popular game-theoretic frameworks for modeling and analyzing such competitive resource allocation problems. However, in many real-world competitive situations, the Colonel Blotto game does not admit solutions in deterministic strategies and, hence, one must rely on analytically complex mixed-strategies with their associated tractability, applicability, and practicality challenges. In this paper, a generalization of the Colonel Blotto game which enables the derivation of deterministic, practical, and implementable equilibrium strategies is proposed while accounting for the heterogeneity of the battlefields. In addition, the proposed generalized game enables accounting for the consumed resources in each battlefield, a feature that is not considered in the classical Blotto game. For the generalized game, the existence of a Nash equilibrium in pure-strategies is shown. Then, closed-form analytical expressions of the equilibrium strategies, are derived and the outcome of the game is characterized; based on the number of resources of each player as well as the valuation of each battlefield. The generated results provide invaluable insights on the outcome of the competition. For example, the results show that, when both players are fully rational, the more resourceful player can achieve a better total payoff at the Nash equilibrium, a result that is not mimicked in the classical Blotto game.Comment: 8 pages, 5 figure

Resource Allocation for Interference Management in Wireless Networks

Interference in wireless networks is a major problem that impacts system performance quite substantially. Combined with the fact that the spectrum is limited and scarce, the performance and reliability of wireless systems significantly deteriorates and, hence, communication sessions are put at the risk of failure. In an attempt to make transmissions resilient to interference and, accordingly, design robust wireless systems, a diverse set of interference mitigation techniques are investigated in this dissertation. Depending on the rationale motivating the interfering node, interference can be divided into two categories, communication and jamming. For communication interference such as the interference created by legacy users(e.g., primary user transmitters in a cognitive radio network) at non-legacy or unlicensed users(e.g.,secondary user receivers), two mitigation techniques are presented in this dissertation. One exploits permutation trellis codes combined with M-ary frequency shift keying in order to make SU transmissions resilient to PUs’ interference, while the other utilizes frequency allocation as a mitigation technique against SU interference using Matching theory. For jamming interference, two mitigation techniques are also investigated here. One technique exploits time and structures a jammer mitigation framework through an automatic repeat request protocol. The other one utilizes power and, following a game-theoretic framework, employs a defense strategy against jamming based on a strategic power allocation. Superior performance of all of the proposed mitigation techniques is shown via numerical results

Security for 5G Mobile Wireless Networks

The advanced features of 5G mobile wireless network systems yield new security requirements and challenges. This paper presents a comprehensive survey on security of 5G wireless network systems compared to the traditional cellular networks. The paper starts with a review on 5G wireless networks particularities as well as on the new requirements and motivations of 5G wireless security. The potential attacks and security services with the consideration of new service requirements and new use cases in 5G wireless networks are then summarized. The recent development and the existing schemes for the 5G wireless security are presented based on the corresponding security services including authentication, availability, data confidentiality, key management and privacy. The paper further discusses the new security features involving different technologies applied to 5G such as heterogeneous networks, device-to-device communications, massive multiple-input multiple-output, software defined networks and Internet of Things. Motivated by these security research and development activities, we propose a new 5G wireless security architecture, based on which the analysis of identity management and flexible authentication is provided. As a case study, we explore a handover procedure as well as a signaling load scheme to show the advantage of the proposed security architecture. The challenges and future directions of 5G wireless security are finally summarized

Optimal decision making in cognitive radio networks

Cognitive Radio Networks are being researched upon heavily in the various layers of the communication structure. The task of bringing software in the physical layer of communication system led to the concept of a smart radio being able to learn, adapt and make intelligent decisions in an autonomous manner by use of a Software Defined Radio. This work provides novel concepts in the areas of spectrum sensing, learning of ongoing transmissions through Reinforcment learning, use of a game theoretic concept such as Zero-sum game for resilience of authorized users in cases of jamming, and decision making of user transmissions through Markov Decision processes. This is highly applicable in dynamic radio environments such as emergency communications required during natural disasters, large scale events and in mobile wireless communications. Such applications come under the "Internet of Things"

A Survey on the Communication Protocols and Security in Cognitive Radio Networks

A cognitive radio (CR) is a radio that can change its transmission parameters based on the perceived availability of the spectrum bands in its operating environment. CRs support dynamic spectrum access and can facilitate a secondary unlicensed user to efficiently utilize the available underutilized spectrum allocated to the primary licensed users. A cognitive radio network (CRN) is composed of both the secondary users with CR-enabled radios and the primary users whose radios need not be CR-enabled. Most of the active research conducted in the area of CRNs has been so far focused on spectrum sensing, allocation and sharing. There is no comprehensive review paper available on the strategies for medium access control (MAC), routing and transport layer protocols, and the appropriate representative solutions for CRNs. In this paper, we provide an exhaustive analysis of the various techniques/mechanisms that have been proposed in the literature for communication protocols (at the MAC, routing and transport layers), in the context of a CRN, as well as discuss in detail several security attacks that could be launched on CRNs and the countermeasure solutions that have been proposed to avoid or mitigate them. This paper would serve as a good comprehensive review and analysis of the strategies for MAC, routing and transport protocols and security issues for CRNs as well as would lay a strong foundation for someone to further delve onto any particular aspect in greater depth

Game-Theoretic Frameworks and Strategies for Defense Against Network Jamming and Collocation Attacks

Modern networks are becoming increasingly more complex, heterogeneous, and densely connected. While more diverse services are enabled to an ever-increasing number of users through ubiquitous networking and pervasive computing, several important challenges have emerged. For example, densely connected networks are prone to higher levels of interference, which makes them more vulnerable to jamming attacks. Also, the utilization of software-based protocols to perform routing, load balancing and power management functions in Software-Defined Networks gives rise to more vulnerabilities that could be exploited by malicious users and adversaries. Moreover, the increased reliance on cloud computing services due to a growing demand for communication and computation resources poses formidable security challenges due to the shared nature and virtualization of cloud computing. In this thesis, we study two types of attacks: jamming attacks on wireless networks and side-channel attacks on cloud computing servers. The former attacks disrupt the natural network operation by exploiting the static topology and dynamic channel assignment in wireless networks, while the latter attacks seek to gain access to unauthorized data by co-residing with target virtual machines (VMs) on the same physical node in a cloud server. In both attacks, the adversary faces a static attack surface and achieves her illegitimate goal by exploiting a stationary aspect of the network functionality. Hence, this dissertation proposes and develops counter approaches to both attacks using moving target defense strategies. We study the strategic interactions between the adversary and the network administrator within a game-theoretic framework. First, in the context of jamming attacks, we present and analyze a game-theoretic formulation between the adversary and the network defender. In this problem, the attack surface is the network connectivity (the static topology) as the adversary jams a subset of nodes to increase the level of interference in the network. On the other side, the defender makes judicious adjustments of the transmission footprint of the various nodes, thereby continuously adapting the underlying network topology to reduce the impact of the attack. The defender\u27s strategy is based on playing Nash equilibrium strategies securing a worst-case network utility. Moreover, scalable decomposition-based approaches are developed yielding a scalable defense strategy whose performance closely approaches that of the non-decomposed game for large-scale and dense networks. We study a class of games considering discrete as well as continuous power levels. In the second problem, we consider multi-tenant clouds, where a number of VMs are typically collocated on the same physical machine to optimize performance and power consumption and maximize profit. This increases the risk of a malicious virtual machine performing side-channel attacks and leaking sensitive information from neighboring VMs. The attack surface, in this case, is the static residency of VMs on a set of physical nodes, hence we develop a timed migration defense approach. Specifically, we analyze a timing game in which the cloud provider decides when to migrate a VM to a different physical machine to mitigate the risk of being compromised by a collocated malicious VM. The adversary decides the rate at which she launches new VMs to collocate with the victim VMs. Our formulation captures a data leakage model in which the cost incurred by the cloud provider depends on the duration of collocation with malicious VMs. It also captures costs incurred by the adversary in launching new VMs and by the defender in migrating VMs. We establish sufficient conditions for the existence of Nash equilibria for general cost functions, as well as for specific instantiations, and characterize the best response for both players. Furthermore, we extend our model to characterize its impact on the attacker\u27s payoff when the cloud utilizes intrusion detection systems that detect side-channel attacks. Our theoretical findings are corroborated with extensive numerical results in various settings as well as a proof-of-concept implementation in a realistic cloud setting

Strategic and Stochastic Approaches to Modeling the Structure of Multi-Layer and Interdependent Networks

Examples of complex networks abound in both the natural world (e.g., ecological, social and economic systems), and in engineered applications (e.g., the Internet, the power grid, etc.). The topological structure of such networks plays a fundamental role in their functioning, dictating properties such as the speed of information diffusion, the influence of powerful or vulnerable nodes, and the ability of the nodes to take collective actions. There are two main schools of thought for investigating the structure of complex networks. Early research on this topic primarily adopted a stochastic perspective, postulating that the links between nodes are formed randomly. In an alternative perspective, it has been argued that optimization (rather than pure randomness) plays a key role in network formation. In such settings, edges are formed strategically (either by a designer or by the nodes themselves) in order to maximize certain utility functions. The classical literature on the structure of networks has predominantly focused on single layer networks where there is a single set of edges between nodes. However, there is an increasing realization that many real-world networks have either multi-layer or interdependent structure. While the former considers multiple layers of relationships between the same set of nodes, the latter deals with networks-of-networks consisting of interdependencies between different subnetworks. This thesis focuses on the analysis of the structure of multi-layer and interdependent networks via strategic and stochastic approaches. In the strategic multi-layer network formation setting, each layer represents a different type of relationship between the nodes and is designed to maximize some utility that depends on its own topology and those of the other layers. By viewing the designer of each layer as a player in a multi-layer network formation game, we show that hub-and-spoke networks that are commonly observed in transportation systems arise as a Nash equilibrium. Extending this analysis to interdependent networks where there are different sets of nodes, we introduce a network design game where the objective of the players is to design the interconnections between the nodes of two different networks, G1 and G2. In this game, each player is associated with a node in G1 and has functional dependencies on certain nodes in G2. Besides showing that finding a best response of a player is NP-hard and characterizing some useful properties of the best response actions of the players, we prove existence of pure Nash equilibria in this game under certain conditions. In order to obtain further insights into the structure of interdependent networks with an arbitrary number of subnetworks, we consider a model for random interdependent networks where each edge between two different subnetworks is formed with probability p. We investigate certain spectral and structural properties of such networks, with corresponding implications for certain variants of consensus dynamics on those networks. In particular, we study a property known as r-robustness, which is a strong indicator of the ability of a network, including interdependent networks, to tolerate structural perturbations and dynamical attacks