Security in cognitive radio network becomes a challenging issue, since more chances are given to attackers by cognitive radio technology compared to general ...
2012 International Conference on Advances in Mobile Network, Communication and Its Applications
GAME THEORY FOR SECURITY IN COGNITIVE RADIO NETWORKS Saed Alrabaee, Anjali Agarwal, Devesh Anand, and Mahmoud Khasawneh School of Electrical and Computer Engineering Concordia University, Montreal, Canada {s_alraba, aagarwal,d_anand,m_khasaw}@encs.concordia.ca Abstract— Cognitive Radio Networks (CRNs) appear as a probable solution for the shortage of spectrum. However, the Security in cognitive radio network becomes a challenging issue, since more chances are given to attackers by cognitive radio technology compared to general wireless network. These chances may cause degradation the network quality of service but currently there are no specific secure protocols for cognitive radio networks. By this motivation, we present the state of art in security of cognitive radio network. In addition, we present the existing game theory models and non-game theory model for security issues in CRN. The attacks in different protocols layers were also investigated.
TABLE I.
NETWORKING GAME
Elements of a game Players Actions Payoff
INTRODUCTION
The idea of cognitive radio network (CRN) was introduced to increase the frequency spectrum utilization in wireless networks [1]. A CRN comprises of two types of users in wireless networks: the Licensed or Primary users (PU) and the Unlicensed or Secondary users (SU). Most of the previous work on CRN does not consider security issues, which however is very important in a CRN. Security problems faced by a CRN are unique as compared to the ones in conventional Wireless Networks [2]. Some of the security attacks in a CRN, such as the jamming attack at physical layer, are capable to damage the whole network, which are therefore required to be counteracted immediately. Game theory is a mathematical tool that helps us to understand the interaction among rational entities, which can be applied to analyze single or group behavior of users in a multiple access in wireless networks. It also offers resource allocation with the help of Nash equilibrium concept where secondary users compete against each other to maximize their performance, under the restriction on the maximum interference made to primary users [1]. Recently, game theory has also been applied to cognitive radio networks, but not in the context of security. Table I shows the correspondence between each element in a cognitive radio network with each element in game theory. In this paper we identify, analyze and explain security attacks and solutions in cognitive networks with the usage of game theory concepts. This paper describes the different security models for the cognitive spectrum paradigm and the explanation of attacks at each layer with game theory as a solution approach.
978-0-7695-4720-6/12 $26.00 © 2012 IEEE DOI 10.1109/MNCApps.2012.17
Element of a CRN Nodes (Secondary and Primary users) Change parameters Throughput, Delay, Bandwidth, Interference, etc.
The rest of this paper is organized as follows: In Section 2, we discuss the security issues and the general attacks in a CRN. In Section 3, we describe the role of game theory in a CRN. In Section 4, we describe the solution models for security issues in a CRN with or without using game theory. Finally, Sections 5 and 6 provide some future challenges and conclusion of the paper respectively.
Keywords-component; Cognitive Radio Network (CRN); Security attacS; Security properties; Game theory
I.
COGNITIVE RADIO NETWORK BASED ON WIRELESS
II.
SECURITY ISSUES IN CRN
The security is considered as a vital area that has received little attention to date in the cognitive radio network. A. Behavior of users in a CRN In this section, we describe the behaviors that indicate the existence of some or more attacks. The following represents the most important behaviors [2]: •
Misbehaving: A SU does not follow anything; it is a type of dictatorship.
•
Selfish: A SU always tries to fulfill its desire for more spectrum bands or bigger time frames.
•
Cheat: A SU cheats with other users purposely to increase its own functions.
•
Malicious: A SU simply interferes in the service with a specific purpose without considering the outcomes.
B. Security properties in a CRN In this section, we describe the most important security properties which clearly impact network performance. • •
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Availability: the link should be returned to the primary user when he is active. The selfish behavior can affect this property. Reliability: it is the reliability of transmitting sensing results for SU. The cheat behavior can affect this property.
•
• •
Non-Repudiation: it is related to the agreement between two parties and this property prevents either the primary user or the secondary user break this agreement. The malicious behavior as well as the selfish behavior can affect this property. Authentication: it is the key property to assure the truthiness of the CR users. The cheat behavior can affect this property. Stability: coming back to equilibrium state after being hindered by a physical disturbance. The sudden physical circumstances can affect this property.
•
Key Depletion Attack: In this attack, the intruder breaks the cipher system with the help of probability of session key repetitions [2].
•
Lion Attack: It basically targets frequency handoff causing decrease in throughput. It is launched by an external entity [3].
•
Jellyfish Attack: It uses closed loop flows to reduce the throughput of TCP and it interferes with the endto-end protocols to infer network status so that it can disrupt the traffic flows [3].
We summarize the above mentioned attacks in Table II according to the layers and we indicate the affected service for each attack.
C. General Attacks on Different Layers of a CRN The attacks generally follow a layered approach. The attacks in a CRN are described in this section, which are later classified in Table II according to each layer. •
•
TABLE II.
TABLE 2: SUMMARY OF ATTACKS IN EACH LAYER WITH THE AFFECTED SERVICE
Jamming Attack: This attack acts by sending arbitrary messages to network. It is further classified into three types. In Intentional Jamming user transmits high power signals so that he can use licensed bands continuously. In an Overlapping Unlicensed user, some random malicious transmission in a CR network affects the other networks. Lastly, Asynchronous sensing deals with the violations of spectrum sensing rules by a selfish user [2].
Layer Physical Data Link Network Transport
Primary User Emulation (PUE) Attack: If a primary user is using a band then secondary users should avoid using that band. To launch this attack a user basically emulates the characteristics of Primary user and the aim is to resist the band from other foreign users. This attack is also classified in two types: the selfish PUE and the malicious PUE [3].
•
Attack on Routing and Disruption: Routing table is made in network layer that provides the path through which messages are delivered to its receiver. This path is like a cake walk for an attacker due to the long distance between source and destination. Once the attack is launched on this layer, it disrupts the whole network [2].
•
Biased Utility Attack: It occurs when a selfish SU alters its function parameters to get more bandwidth while decreasing the bandwidth of unlicensed user [3].
•
False Feedback Attack: When a malicious user hides the presence of licensed user and network nodes are unable to sense information due to signal fading [3].
•
Common Control Channel (CCC) Attack: In such kind of attacks, the attacker can take over the control channel and interfere in the channel negotiation and allocation process, causing denial of service (DoS).
Attack Jamming PUE Biased Utility False Feedback CCC Routing Attack Key Depletion Lion Jellyfish
References [2,15] [3] [2] [2,3] [2,3,15]
Table II does not include application layer, which is the highest layer in CR networks, and its working totally depends upon lower layer. Any attack in lower layers will directly interfere with the quality and service of application. III.
THE ROLE OF GAME THEORY IN CRN
Game theory has been used mostly in economics, in order to model competition between firms. It has also been applied to networking, generally to solve routing and resource allocation problems in a competitive environment [4]. Recently, game theory was also applied to wireless communication: the decision makers in the game are rational users who control their communication devices [4]. Due to the nature of cognitive radio network whereas if any change in environment will trigger the network to re-allocate the spectrum resources; the game theory was used as an important tool to analyze, model, and study the interactions. By using game theory we can get an efficient model as well as self-enforcing and scalable schemes. Furthermore, the secondary users who compete for spectrum may or may not cooperate with other users. The latter will lead to the selfish behavior of users. Therefore, this nature specifically requires using a game theory model. There are various kinds of games such as cooperative, non-cooperative, static, dynamic, repeated, and stackelberg. •
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Non-cooperative game: The users act to maximize their own payoff individually.
•
Cooperative game: The users have mutual actions to gain shared benefits.
•
Static game: It is deterministic, time independent, and is good for one period.
•
Issue in CRN Power Control
Dynamic game: It is good for more periods and any change in the parameters of the system will affect the game.
Interference
• •
TABLE III.
Spectrum Sharing Power Allocation Spectrum access Security
Repeated game: A group of agents engage in a strategic interaction over and over. Stackelberg game: It consists of a leader and a follower. Leader announces a policy and the follower chooses its policy based on leader action.
In cognitive radio network, some of the game theoretic models were presented in [4], which has identified potential game models for power control, call admission control, and interference avoidance in cognitive radio networks. Several methods have been proposed for dynamic spectrum access including game theory [5].
Spectrum Trading
In [5], the channel allocation problem is modeled as a repeated game. In this, the players are secondary users and their strategies (actions) are choosing channel. In [5] two classes of payoff were presented according to which cognitive radios adapt their transmissions.
IV.
SUMMARY OF GAME MODELS FOR ISSUES IN CRN
Game Model
Solution
Noncooperative Potential game, Stackelberg game Cooperative
Nash equilibrium Nash equilibrium
[4]
Nash equilibrium Nash equilibrium Nash equilibrium Nash equilibrium Market equilibrium
[7]
Potential game Noncooperative Stackelberg Supply Demand functions
and
Reference
[6]
[8] [11] [14] [15]
MODELS FOR SECURITY ISSUES IN CRN
Most game approaches on spectrum and power do not consider security issue. Moreover most of the available approaches make some assumptions related to security, such as all users are not malicious users, all users are trusted, all users are authorized as well as authenticated, and the primary user is a trusted party. However, in some environment these assumptions are not valid, which require changes to the existing model to prevent any kinds of attacks or denial of services. Following is a discussion about some existing models for security issue in CRN.
The first class corresponds to selfish behavior. The second class corresponds to cooperative behavior. The benefit of a game theory model in CRN is summarized as follows: the network users’ behavior and actions can be analyzed; game theory provides us the equilibrium (solution), and the non-cooperative game theory gives us the ability to derive efficient distributed approaches.
A. Models as solution for security issues in CRN without using game theory
Basically, it is clearly shown in Table III that the solution for most game models is Nash equilibrium, which means each player has no chance to increase its utility by unilaterally deviating from this equilibrium. Table 3 shows the different issues in CRN that have been modeled by game theory. This modeling gives us the ability to understand the issue deeply and based on that we can change the parameters of models according to our requirements.
New authentication mechanism based on third-party Certification Authority (CA) is proposed in [9]. The author of [10] proposed hard punishment mechanism based on a puzzle model. In [10] the selfish behavior in cognitive radio networks is studied and an improved security mechanism is presented. The authors of [12] proposed a good puzzle model when they studied the denial of service attack. When the service device makes an agreement or starts to deal with resource functions of a request it will ask the node to solve a puzzle. The authors in [13] describe the attacks in physical layer and proposed solutions for these attacks. Sensory manipulation attacks were discussed in [13], where an adversary understands how a radio’s statistics are calculated, and manipulates them. Belief manipulation attacks occurs when an attacker can introduce a jamming signal as long as a policy radio switches to a faster modulation rate, forcing it to always operate at lower modulation rates, resulting in lower link speeds. Some solutions for the previous attacks are: improving sensor input can significantly help reduce the
Most game theoretic models were modeled for issues related to power and spectrum such as spectrum allocation, spectrum sharing, spectrum access, spectrum trading, power allocation, power control, and interference avoidance. There are very few game theoretic models for security issues in CRN because the difficulty of this area according to the nature of node’s mobility, variety in architectures, and this nature could contains multi types of users such as mobiles, computers, base stations, and other electronic devices. In the next section we describe the existing game models and non-game models for security issues.
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chance to other user and game theory plays a vital role to prevent such action by giving a way to monitor the behaviors of users in the network.
gullibility of cognitive radios, radio policies should be carefully evaluated to protect against malicious sensor input. B. Game theoretic models as solutions for security issues in CRN
REFERENCES
The authors of [14] proposed a secure game theory approach (Stackelberg approach) to prevent the malicious users. It gives the primary user ability to supervise the secondary user whether cooperate or not and to detect the compromised actions. The main idea in [14] is based on contract where the primary user monitors the secondary user and in case of malicious behavior, the primary user can break the contract and issue a punishment for the malicious user. The drawbacks of [14] are: it is only worthy for primary user and it consumes more resources for primary user. However, market-equilibrium based spectrum trading approach between primary user and secondary user is studied where both primary user and secondary user payoff could be satisfied. This way the selfish behavior is halted.
[1]
[2]
[3]
[4]
[5]
FUTURE TRENDS The emerging trend of achieving energy efficiency in CRN is motivating the standardization authorities and network operators to continuously explore future technologies in order to bring improvements in the entire network infrastructure. Cognitive radio is an undisputed future technology in this regard, the need is to overcome its security concerns and game theory is showing an optimistic prospective to deal with these security issues. We believe CRN is that milestone which will help in making next generation’s wireless systems “green”.
[6]
CONCLUSION
[10]
[7]
[8]
[9]
In this paper we presented the state-of-the-art of CR research for security issues with and without game theory framework. These vigilant future networks (CRN) have enormous potential in it .Wireless security in cognitive radio networks has received little attention to date, even though security will likely play a key role in commercial feasibility of the technology. This paper investigates on security issues of cognitive radio networks. The paper first analyzes user’s behavior in network, security properties in CRN, the security attacks in cognitive radio networks, and then describes current solutions. In the latter, we describe the models with and without the game theory framework. Finally, the security issue is very important issue to be handling according to the effect on the network performance because the malicious user could uses the network resources without giving any
[11]
[12]
[13]
[14]
[15]
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