Pub Date : 2017-03-01DOI: 10.1109/JSAC.2017.2659478
Han Hu, Yonggang Wen, D. Niyato
Mobile social video sharing enables mobile users to create ultra-short video clips and instantly share them with social friends, which poses significant pressure to the content distribution infrastructure. In this paper, we propose a public cloud-assisted architecture to tackle this problem. In particular, by motivating mobile users to upload videos to the local public cloud to serve requests, and, therefore, having a permission to access friends’ videos stored in the cloud, our method can alleviate the traffic burden to the social service providers, while reducing the service latency of mobile users. First, we present a general framework to model the information diffusion and utility function of each user on the proposed architecture, and formulate the problem as a decentralized social utility maximization game. Second, we show that this problem is a supermodular game and there exists at least one socially aware Nash equilibrium (SNE). We then develop two decentralized algorithms to solve this problem. The first algorithm can find an SNE with less computation complexity, and the second algorithm can find the Pareto-optimal SNE with better performance. Finally, through extensive experiments, we demonstrate that the overall system performance can be significantly improved by exploiting the selflessness among social friends.
{"title":"Public Cloud Storage-Assisted Mobile Social Video Sharing: A Supermodular Game Approach","authors":"Han Hu, Yonggang Wen, D. Niyato","doi":"10.1109/JSAC.2017.2659478","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2659478","url":null,"abstract":"Mobile social video sharing enables mobile users to create ultra-short video clips and instantly share them with social friends, which poses significant pressure to the content distribution infrastructure. In this paper, we propose a public cloud-assisted architecture to tackle this problem. In particular, by motivating mobile users to upload videos to the local public cloud to serve requests, and, therefore, having a permission to access friends’ videos stored in the cloud, our method can alleviate the traffic burden to the social service providers, while reducing the service latency of mobile users. First, we present a general framework to model the information diffusion and utility function of each user on the proposed architecture, and formulate the problem as a decentralized social utility maximization game. Second, we show that this problem is a supermodular game and there exists at least one socially aware Nash equilibrium (SNE). We then develop two decentralized algorithms to solve this problem. The first algorithm can find an SNE with less computation complexity, and the second algorithm can find the Pareto-optimal SNE with better performance. Finally, through extensive experiments, we demonstrate that the overall system performance can be significantly improved by exploiting the selflessness among social friends.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"545-556"},"PeriodicalIF":16.4,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2659478","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49235900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/JSAC.2017.2672239
L. Guijarro, V. Pla, J. Vidal, M. Naldi
The advent of the Internet of Things (IoT) is expected to bring major benefits to a wide range of areas. However, the successful deployment of the IoT calls for the existence of sustainable and well-understood business models. In this paper, we propose and analyze a business model for a likely scenario in the IoT, which is made up of WSNs, service providers and users. The service providers compete against each other in the intermediation between the virtualized WSNs and the users that benefit from enhanced services built on the sensed data. The service providers pay to the WSNs for the data and charge the users for the service. The model is analyzed by applying oligopoly theory and game theory, the conditions for the existence and uniqueness of the Nash equilibrium are established, and the equilibrium and the social optimum are obtained. Our results show that the business model is sustainable, provided that the users’ sensitivity to the value-to-price ratio is not negligible and, in this situation, the number of active service providers is upper bounded by a value that depends on the sensitivity and the market size. Furthermore, the operation of such a market is shown to efficiently use the information provided by the WSNs, and, when compared to the social optimum, to produce an increase in users’ and service providers’ surpluses, but a reduction in WSNs’ surplus.
{"title":"Game Theoretical Analysis of Service Provision for the Internet of Things Based on Sensor Virtualization","authors":"L. Guijarro, V. Pla, J. Vidal, M. Naldi","doi":"10.1109/JSAC.2017.2672239","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2672239","url":null,"abstract":"The advent of the Internet of Things (IoT) is expected to bring major benefits to a wide range of areas. However, the successful deployment of the IoT calls for the existence of sustainable and well-understood business models. In this paper, we propose and analyze a business model for a likely scenario in the IoT, which is made up of WSNs, service providers and users. The service providers compete against each other in the intermediation between the virtualized WSNs and the users that benefit from enhanced services built on the sensed data. The service providers pay to the WSNs for the data and charge the users for the service. The model is analyzed by applying oligopoly theory and game theory, the conditions for the existence and uniqueness of the Nash equilibrium are established, and the equilibrium and the social optimum are obtained. Our results show that the business model is sustainable, provided that the users’ sensitivity to the value-to-price ratio is not negligible and, in this situation, the number of active service providers is upper bounded by a value that depends on the sensitivity and the market size. Furthermore, the operation of such a market is shown to efficiently use the information provided by the WSNs, and, when compared to the social optimum, to produce an increase in users’ and service providers’ surpluses, but a reduction in WSNs’ surplus.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"691-706"},"PeriodicalIF":16.4,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2672239","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48180661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/JSAC.2017.2672258
M. Touati, R. El-Azouzi, M. Coupechoux, E. Altman, J. Kélif
In multi-rate IEEE 802.11 WLANs, the traditional user association based on the strongest received signal and the well-known anomaly of the MAC protocol can lead to overloaded access points (APs), and poor or heterogeneous performance. Our goal is to propose an alternative game-theoretic approach for association. We model the joint resource allocation and user association as a matching game with complementarities and peer effects consisting of selfish players solely interested in their individual throughputs. Using recent game-theoretic results, we first show that various resource sharing protocols actually fall in the scope of the set of stability-inducing resource allocation schemes. The game makes an extensive use of the Nash bargaining and some of its related properties that allow controlling the incentives of the players. We show that the proposed mechanism can greatly improve the efficiency of 802.11 with heterogeneous nodes and reduce the negative impact of peer effects such as its MAC anomaly. The mechanism can be implemented as a virtual connectivity management layer to achieve efficient APs-user associations without modification of the MAC layer.
{"title":"A Controlled Matching Game for WLANs","authors":"M. Touati, R. El-Azouzi, M. Coupechoux, E. Altman, J. Kélif","doi":"10.1109/JSAC.2017.2672258","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2672258","url":null,"abstract":"In multi-rate IEEE 802.11 WLANs, the traditional user association based on the strongest received signal and the well-known anomaly of the MAC protocol can lead to overloaded access points (APs), and poor or heterogeneous performance. Our goal is to propose an alternative game-theoretic approach for association. We model the joint resource allocation and user association as a matching game with complementarities and peer effects consisting of selfish players solely interested in their individual throughputs. Using recent game-theoretic results, we first show that various resource sharing protocols actually fall in the scope of the set of stability-inducing resource allocation schemes. The game makes an extensive use of the Nash bargaining and some of its related properties that allow controlling the incentives of the players. We show that the proposed mechanism can greatly improve the efficiency of 802.11 with heterogeneous nodes and reduce the negative impact of peer effects such as its MAC anomaly. The mechanism can be implemented as a virtual connectivity management layer to achieve efficient APs-user associations without modification of the MAC layer.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"707-720"},"PeriodicalIF":16.4,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2672258","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47680522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/JSAC.2017.2672278
Salvatore D’oro, L. Galluccio, S. Palazzo, G. Schembra
Softwarization of networks allows simplifying deployment, configuration, and management of network functions. The driving force toward this evolution is represented by software defined networking that allows more flexible and dynamic network resource allocation and management. The efficient allocation and orchestration of network resources is of extreme importance for this softwarization process, and many centralized solutions have been proposed. However, they are complex and exhibit scalability issues. So, distributed solutions are to be preferred but, in order to be effective, should quickly converge towards equilibrium solutions. In this paper, we focus on making distributed resource allocation and orchestration a viable approach, and prove convergence of the relevant mechanisms. Specifically, we exploit game theory to model interactions between users requesting network functions and servers providing these functions. Accordingly, a two-stage Stackelberg game is presented, where servers act as leaders of the game and users as followers. Servers have conflicting interests and try to maximize their utility; users, on the other hand, use a replicator behavior and try to imitate other user’s decisions to improve their benefit. The framework proves the existence and uniqueness of an equilibrium, and a learning mechanism to converge to such equilibrium is proposed. Numerical results show the effectiveness of the approach.
{"title":"A Game Theoretic Approach for Distributed Resource Allocation and Orchestration of Softwarized Networks","authors":"Salvatore D’oro, L. Galluccio, S. Palazzo, G. Schembra","doi":"10.1109/JSAC.2017.2672278","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2672278","url":null,"abstract":"Softwarization of networks allows simplifying deployment, configuration, and management of network functions. The driving force toward this evolution is represented by software defined networking that allows more flexible and dynamic network resource allocation and management. The efficient allocation and orchestration of network resources is of extreme importance for this softwarization process, and many centralized solutions have been proposed. However, they are complex and exhibit scalability issues. So, distributed solutions are to be preferred but, in order to be effective, should quickly converge towards equilibrium solutions. In this paper, we focus on making distributed resource allocation and orchestration a viable approach, and prove convergence of the relevant mechanisms. Specifically, we exploit game theory to model interactions between users requesting network functions and servers providing these functions. Accordingly, a two-stage Stackelberg game is presented, where servers act as leaders of the game and users as followers. Servers have conflicting interests and try to maximize their utility; users, on the other hand, use a replicator behavior and try to imitate other user’s decisions to improve their benefit. The framework proves the existence and uniqueness of an equilibrium, and a learning mechanism to converge to such equilibrium is proposed. Numerical results show the effectiveness of the approach.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"721-735"},"PeriodicalIF":16.4,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2672278","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48454376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/JSAC.2017.2659581
Xiaofan He, H. Dai, P. Ning, R. Dutta
In various resource sharing networks, opportunistic resources with dynamic quality are often present for the users to exploit. As many user tasks are delay-tolerant, this favorably allows the network users to wait for and access the opportunistic resource at the time of its best quality. For such delay-tolerant and opportunistic resource sharing networks, the resource accessing strategies developed in the literature suffer from three limitations. First, they mainly focused on single-user scenarios, whereas the competition from other users is ignored. Second, the influence from the resource seller who may take actions to manipulate the resource sharing procedure is not considered. Third, the impact of the actions from both the network users and the resource seller on the resource quality dynamics is not considered either. To overcome these limitations, a leader–follower controlled Markov stopping game (LF-C-MSG) is developed in this paper. The derived Stackelberg equilibrium strategy of the LF-C-MSG can be used to guide the behaviors of both the network users and the resource seller for better performance and resource utilization efficiency. Two exemplary applications of the proposed LF-C-MSG are presented, along with corresponding numerical results to verify the effectiveness of the proposed framework.
{"title":"A Leader–Follower Controlled Markov Stopping Game for Delay Tolerant and Opportunistic Resource Sharing Networks","authors":"Xiaofan He, H. Dai, P. Ning, R. Dutta","doi":"10.1109/JSAC.2017.2659581","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2659581","url":null,"abstract":"In various resource sharing networks, opportunistic resources with dynamic quality are often present for the users to exploit. As many user tasks are delay-tolerant, this favorably allows the network users to wait for and access the opportunistic resource at the time of its best quality. For such delay-tolerant and opportunistic resource sharing networks, the resource accessing strategies developed in the literature suffer from three limitations. First, they mainly focused on single-user scenarios, whereas the competition from other users is ignored. Second, the influence from the resource seller who may take actions to manipulate the resource sharing procedure is not considered. Third, the impact of the actions from both the network users and the resource seller on the resource quality dynamics is not considered either. To overcome these limitations, a leader–follower controlled Markov stopping game (LF-C-MSG) is developed in this paper. The derived Stackelberg equilibrium strategy of the LF-C-MSG can be used to guide the behaviors of both the network users and the resource seller for better performance and resource utilization efficiency. Two exemplary applications of the proposed LF-C-MSG are presented, along with corresponding numerical results to verify the effectiveness of the proposed framework.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"615-627"},"PeriodicalIF":16.4,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2659581","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44032377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/JSAC.2017.2672378
Rui Zhang, Quanyan Zhu, Y. Hayel
Cyber insurance is a valuable approach to mitigate further the cyber risk and its loss in addition to the deployment of technological cyber defense solutions, such as intrusion detection systems and firewalls. An effective cyber insurance policy can reduce the number of successful cyber attacks by incentivizing the adoption of preventative measures and the implementation of best practices of the users. To study cyber insurance in a holistic manner, we first establish a bi-level game-theoretic model that nests a zero-sum game in a moral-hazard type of principal-agent game to capture complex interactions between a user, an attacker, and the insurer. The game framework provides an integrative view of the cyber insurance and enables a systematic design of incentive compatible and attack-aware insurance policy. The framework is further extended to study a network of users and their risk interdependencies. We completely characterize the equilibrium solutions of the bi-level game. Our analytical results provide a fundamental limit on insurability, predict the Peltzman effect, and reveal the principles of zero operating profit and the linear insurance policy of the insurer. We provide analytical results and numerical experiments to corroborate the analytical results and demonstrate the network effects as a result of the strategic interactions among the three types of players.
{"title":"A Bi-Level Game Approach to Attack-Aware Cyber Insurance of Computer Networks","authors":"Rui Zhang, Quanyan Zhu, Y. Hayel","doi":"10.1109/JSAC.2017.2672378","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2672378","url":null,"abstract":"Cyber insurance is a valuable approach to mitigate further the cyber risk and its loss in addition to the deployment of technological cyber defense solutions, such as intrusion detection systems and firewalls. An effective cyber insurance policy can reduce the number of successful cyber attacks by incentivizing the adoption of preventative measures and the implementation of best practices of the users. To study cyber insurance in a holistic manner, we first establish a bi-level game-theoretic model that nests a zero-sum game in a moral-hazard type of principal-agent game to capture complex interactions between a user, an attacker, and the insurer. The game framework provides an integrative view of the cyber insurance and enables a systematic design of incentive compatible and attack-aware insurance policy. The framework is further extended to study a network of users and their risk interdependencies. We completely characterize the equilibrium solutions of the bi-level game. Our analytical results provide a fundamental limit on insurability, predict the Peltzman effect, and reveal the principles of zero operating profit and the linear insurance policy of the insurer. We provide analytical results and numerical experiments to corroborate the analytical results and demonstrate the network effects as a result of the strategic interactions among the three types of players.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"779-794"},"PeriodicalIF":16.4,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2672378","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43166520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/JSAC.2017.2659580
Peyman Siyari, M. Krunz, Diep N. Nguyen
We consider joint optimization of artificial noise (AN) and information signals in a MIMO wiretap interference network, wherein the transmission of each link may be overheard by several MIMO-capable eavesdroppers. Each information signal is accompanied with AN, generated by the same user to confuse nearby eavesdroppers. Using a noncooperative game, a distributed optimization mechanism is proposed to maximize the secrecy rate of each link. The decision variables here are the covariance matrices for the information signals and ANs. However, the nonconvexity of each link’s optimization problem (i.e., best response) makes conventional convex games inapplicable, even to find whether a Nash equilibrium (NE) exists. To tackle this issue, we analyze the proposed game using a relaxed equilibrium concept, called quasi-NE (QNE). Under a constraint qualification condition for each player’s problem, the set of QNEs includes the NE of the proposed game. We also derive the conditions for the existence and uniqueness of the resulting QNE. It turns out that the uniqueness conditions are too restrictive, and do not always hold in typical network scenarios. Thus, the proposed game often has multiple QNEs, and convergence to a QNE is not always guaranteed. To overcome these issues, we modify the utility functions of the players by adding several specific terms to each utility function. The modified game converges to a QNE even when multiple QNEs exist. Furthermore, players have the ability to select a desired QNE that optimizes a given social objective (e.g., sum rate or secrecy sum rate). Depending on the chosen objective, the amount of signaling overhead as well as the performance of resulting QNE can be controlled. Simulations show that not only can we guarantee the convergence to a QNE, but also due to the QNE selection mechanism, we can achieve a significant improvement in terms of secrecy sum rate and power efficiency, especially in dense networks.
{"title":"Friendly Jamming in a MIMO Wiretap Interference Network: A Nonconvex Game Approach","authors":"Peyman Siyari, M. Krunz, Diep N. Nguyen","doi":"10.1109/JSAC.2017.2659580","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2659580","url":null,"abstract":"We consider joint optimization of artificial noise (AN) and information signals in a MIMO wiretap interference network, wherein the transmission of each link may be overheard by several MIMO-capable eavesdroppers. Each information signal is accompanied with AN, generated by the same user to confuse nearby eavesdroppers. Using a noncooperative game, a distributed optimization mechanism is proposed to maximize the secrecy rate of each link. The decision variables here are the covariance matrices for the information signals and ANs. However, the nonconvexity of each link’s optimization problem (i.e., best response) makes conventional convex games inapplicable, even to find whether a Nash equilibrium (NE) exists. To tackle this issue, we analyze the proposed game using a relaxed equilibrium concept, called quasi-NE (QNE). Under a constraint qualification condition for each player’s problem, the set of QNEs includes the NE of the proposed game. We also derive the conditions for the existence and uniqueness of the resulting QNE. It turns out that the uniqueness conditions are too restrictive, and do not always hold in typical network scenarios. Thus, the proposed game often has multiple QNEs, and convergence to a QNE is not always guaranteed. To overcome these issues, we modify the utility functions of the players by adding several specific terms to each utility function. The modified game converges to a QNE even when multiple QNEs exist. Furthermore, players have the ability to select a desired QNE that optimizes a given social objective (e.g., sum rate or secrecy sum rate). Depending on the chosen objective, the amount of signaling overhead as well as the performance of resulting QNE can be controlled. Simulations show that not only can we guarantee the convergence to a QNE, but also due to the QNE selection mechanism, we can achieve a significant improvement in terms of secrecy sum rate and power efficiency, especially in dense networks.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"601-614"},"PeriodicalIF":16.4,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2659580","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46230395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/JSAC.2017.2659418
Liang Xiao, Dongjin Xu, Caixia Xie, N. Mandayam, H. Poor
Cloud storage is vulnerable to advanced persistent threats (APTs), in which an attacker launches stealthy, continuous, and targeted attacks on storage devices. In this paper, prospect theory (PT) is applied to formulate the interaction between the defender of a cloud storage system and an APT attacker who makes subjective decisions that sometimes deviate from the results of expected utility theory, which is a basis of traditional game theory. In the PT-based cloud storage defense game with pure strategy, the defender chooses a scan interval for each storage device and the subjective APT attacker chooses his or her interval of attack against each device. A mixed-strategy subjective storage defense game is also investigated, in which each subjective defender and APT attacker acts under uncertainty about the action of its opponent. The Nash equilibria (NEs) of both games are derived, showing that the subjective view of an APT attacker can improve the utility of the defender. A Q-learning-based APT defense scheme that the storage defender can apply without being aware of the APT attack model or the subjectivity model of the attacker in the dynamic APT defense game is also proposed. Simulation results show that the proposed defense scheme suppresses the attack motivation of subjective APT attackers and improves the utility of the defender, compared with the benchmark greedy defense strategy.
{"title":"Cloud Storage Defense Against Advanced Persistent Threats: A Prospect Theoretic Study","authors":"Liang Xiao, Dongjin Xu, Caixia Xie, N. Mandayam, H. Poor","doi":"10.1109/JSAC.2017.2659418","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2659418","url":null,"abstract":"Cloud storage is vulnerable to advanced persistent threats (APTs), in which an attacker launches stealthy, continuous, and targeted attacks on storage devices. In this paper, prospect theory (PT) is applied to formulate the interaction between the defender of a cloud storage system and an APT attacker who makes subjective decisions that sometimes deviate from the results of expected utility theory, which is a basis of traditional game theory. In the PT-based cloud storage defense game with pure strategy, the defender chooses a scan interval for each storage device and the subjective APT attacker chooses his or her interval of attack against each device. A mixed-strategy subjective storage defense game is also investigated, in which each subjective defender and APT attacker acts under uncertainty about the action of its opponent. The Nash equilibria (NEs) of both games are derived, showing that the subjective view of an APT attacker can improve the utility of the defender. A Q-learning-based APT defense scheme that the storage defender can apply without being aware of the APT attack model or the subjectivity model of the attacker in the dynamic APT defense game is also proposed. Simulation results show that the proposed defense scheme suppresses the attack motivation of subjective APT attackers and improves the utility of the defender, compared with the benchmark greedy defense strategy.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"534-544"},"PeriodicalIF":16.4,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2659418","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48723559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/JSAC.2017.2659498
Haipeng Chen, Bo An, D. Niyato, Y. Soh, C. Miao
In cloud computing, a private (secondary) cloud can: 1) outsource workload to public (primary) clouds via vertical federation or 2) share resources with other secondary clouds through horizontal federation to enhance its service quality. While there have been attempts to establish a joint vertical and horizontal cloud federation (VHCF), little is known regarding the economic aspects (e.g., what stable cooperation pattern will form, will it improve efficiency) of such a complex cloud network, where secondary clouds are self-interested. To fill the gap, we analyze the interrelated workload factoring and federation formation among secondary clouds, while providing scalable algorithms to assist them to optimally select partners and outsource workload. We use a game theoretic approach to model the federation formation of clouds as a coalition game with externalities. We adopt a pessimistic core to characterize the cooperation stability and formulate its computation as a bilevel optimization problem. The properties of the problem are explored and efficient algorithms are developed to solve it. Experimental results show that the two common practices (no-cooperation and all-in-one federation) are not always stable. The results also show that compared with the two common practices, secondary clouds can decrease service delay penalty by around 11% with the proposed VHCF network.
{"title":"Workload Factoring and Resource Sharing via Joint Vertical and Horizontal Cloud Federation Networks","authors":"Haipeng Chen, Bo An, D. Niyato, Y. Soh, C. Miao","doi":"10.1109/JSAC.2017.2659498","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2659498","url":null,"abstract":"In cloud computing, a private (secondary) cloud can: 1) outsource workload to public (primary) clouds via vertical federation or 2) share resources with other secondary clouds through horizontal federation to enhance its service quality. While there have been attempts to establish a joint vertical and horizontal cloud federation (VHCF), little is known regarding the economic aspects (e.g., what stable cooperation pattern will form, will it improve efficiency) of such a complex cloud network, where secondary clouds are self-interested. To fill the gap, we analyze the interrelated workload factoring and federation formation among secondary clouds, while providing scalable algorithms to assist them to optimally select partners and outsource workload. We use a game theoretic approach to model the federation formation of clouds as a coalition game with externalities. We adopt a pessimistic core to characterize the cooperation stability and formulate its computation as a bilevel optimization problem. The properties of the problem are explored and efficient algorithms are developed to solve it. Experimental results show that the two common practices (no-cooperation and all-in-one federation) are not always stable. The results also show that compared with the two common practices, secondary clouds can decrease service delay penalty by around 11% with the proposed VHCF network.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"557-570"},"PeriodicalIF":16.4,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2659498","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47531432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-03-01DOI: 10.1109/JSAC.2017.2659582
E. Ciftcioglu, Siddharth Pal, K. Chan, D. Cansever, A. Swami, Ambuj K. Singh, P. Basu
We study the problem of network topology design within a set of policy-compliant topologies as a game between a designer and an adversary. At any time instant, the designer aims to operate the network in an optimal topology within the set of policy compliant topologies with respect to a desired network property. Simultaneously, the adversary counters the designer trying to force operation in a suboptimal topology. Specifically, if the designer and the attacker choose the same link in the current topology to defend/grow and attack, respectively, then the latter is thwarted. However, if the defender does not correctly guess where the attacker is going to attack, and, hence, acts elsewhere, the topology reverts to the best policy-compliant configuration after a successful attack. We show the existence of various mixed strategy equilibria in this game and systematically study its structural properties. We study the effect of parameters, such as probability of a successful attack, and characterize the steady state behavior of the underlying Markov chain. While the intuitive adversarial strategy here is to attack the most important links, the Nash equilibrium strategy is for the designer to defend the most crucial links and for the adversary to focus attack on the lesser crucial links. We validate these properties through two use cases with example sets of network topologies. Next, we consider a multi-stage framework where the designer is not only interested in the instantaneous network property costs but a discounted sum of costs over many time instances. We establish structural properties of the equilibrium strategies in the multi-stage setting, and also demonstrate that applying algorithms based on the Q-Learning and Rollout methods can result in significant benefits for the designer compared with strategies resulting from a one-shot based game.
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