Trust-based Security in Wireless Sensor Networks using Game Theory

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Trust-based Security in Wireless Sensor Networks using Game Theory

Kavitha B M

Department of computer science and Engg.

Akshya Institute of Technology Tumkur, India

Mr. Harish H K

Department of computer science and Engg.

Akshya Institute of Technology Tumkur, India

Abstract at current, Sensor Networks and the emerging Internet of Things standard are playing a key role in the industry and in academic research. Internet of Things (IoT) is an included part of Future Internet and could be distinct as a dynamic global network infrastructure with self configuring capabilities based on typical and interoperable communication protocols where physical and virtual things have identities, physical

attributes, and virtual personalities and employ intelligent interfaces, and are seamlessly integrated into the information network. In this paper we presented the overview of internet of thing, security and challenges for Internet of Things (IoT), we also proposed features of Intenet of thing in this paper.

Keywords-; Energy awareness, game theory, Internet of Things (IoT), security, trust evaluation,

  1. INTRODUCTION

    In the future Internet of Things (IoT), the everyday objects which contain us will become positive actors of the Internet, generating and consuming information. The elements of the IoT comprise not only those devices that are already deeply rooted in the technological world (such as cars or fridges), but also objects foreign to this environment (garments or perishable food), or even living beings (plantations, forest or livestock). By embedding computational capabilities in all kinds of objects and living beings, it will be possible to present a qualitative and quantitative leap in several sectors: healthcare, logistics, domotics, entertainment, and so on. In fact, one of the most important elements in the IoT paradigm is wireless sensor networks (WSN). The benefits of concerning both WSN and other IoT elements go beyond remote access, as heterogeneous information systems can be able to collaborate and present general services. This integration is not simple speculation, but a truth supported by several international

    companies. Noteworthy examples are A Smarter Planet

    [1], a strategy developed by IBM which deems sensors as basic pillars in intelligent water management

    systems and smart cities; and the CeNSE project by HP Labs, illustrated on the exploitation of a worldwide sensor network in order to create a central nervous system for the Earth. By

    the equivalent time the technologies that will allow the integration are being developed and tested. For example, the

    LowPAN standard, defined by IETF [2], allows the transmission of IPv6 packets during computationally confidential networks. Moreover, it is actually possible to link the data produced by the elements of a WSN (sensor nodes) with web services based on SOAP and REST, messaging mechanisms (such as emails and SMS) or social networks (e.g. Twitter) and blogs (e.g. WordPress) [3]. However, having IP connectivity does not mean that every sensor node should be directly connected to the Internet. Here, many challenges that must be carefully considered, and one of those disputes is security. While in this paper we will introduce some of the most important security integration challenges (integration of security mechanisms and services, data privacy) we will focus on one specific challenge: the concrete connectivity model between the WSN and the Internet.

  2. SECURITY INTEGRATION CHALLENGES

    In order to allocate wireless sensor network turn into an essential part of the IoT in a secure way, several security challenges must be considered. As aforementioned, in this paper we focus on the connectivity at the network level. Nevertheless, there are additional security challenges that, even if they are not studied in this paper, must be highlighted to guide future work. These challenges are tightly related to WSN, but also can be applicable to other relevant technologies of the IoT. Some of the most important challenges are the integration of security mechanisms and users acceptance. It is

    essential to consider the security of the IoT from a global

    perspective and not as a set of isolated issues related to

    specific technologies. Otherwise, we could reach a point

    where a technology (e.g. a WSN) satisfies a minimal set of

    security requirements, but its integration with other

    technologies (e.g. RFID) generates new requirements

    which

    had not been previously considered. Regarding the users perspective, the IoT must be able to satisfy their expectations without betraying their trust. Not only the IoT must be useful, but also users must perceive that they control any information that is related to them. If users feel that they are controlled by the system, or they have a false perception of security which is betrayed due to a violation of their rights, any advantage that the IoT can provide will be directly rejected. Data privacy must also be critically considered. The information obtainable concerning a exacting user will not only consist of his personal data, but also of any data generated by the objects (e.g. sensor nodes) surrounding the individual. In this situation, it is necessary to clarify who owns the data and how the user can be sure that the data is safe and will not be used without his consent. Moreover, there will be some scenarios where part of the data should be shared in order to provide a service. For example, in case of disaster, a person should present her health data (e.g. personal history and allergies) to the ambulance and medical staff in a transparent way. Beyond individual users, data privacy is also a matter of concern for business scenarios. Any company that makes use of the mechanisms provided by the IoT will generate a huge data flow (e.g. human resources

    interaction, production processes). Such data must remain

    private, illicit by the company and accessible only when

    required. Finally, another significant aspect that must be taken

    into account is the protection of the components of the IoT by

    means of adequate security mechanisms. This not only refers

    to the use of security protocols and mechanisms at the network

    level (which will be considered in the remainder of the paper),

    but also to the interactions between objects and services.

    As

    the IoT is a distributed, dynamic and heterogeneous

    infrastructure, it is essential to separate a number of

    technologies, protocols and access models in order to provide

    services in an appropriate way. From a security viewpoint, the

    primary objects and infrastructures must be able to handle

    several identification and security mechanisms in a transparent

    and scalable way. Although there will exist some isolated

    scenarios (e.g. a digital home, the headquarters of a company)

    where interactions between objects will be kept under-

    control,

    It will exist different services (such as logistics) which will

    make use of several elements geographically dispersed all over

    the world. Due to this, reaching an equilibrium point in the

    secure interactions between objects and services is one of the

    most interesting challenges in the IoT [6].

  3. COMMON ISSUES IN INTERNET OF THINGS (IOT)

    O Scalability: – The IoT has larger overall scope than communications with conventional hosts. There will be small (home environment) or large scale (factory, building) application area. Objects communicate with eachother and with people seamlessly. Each

    constituent might be offering different services. Basic functionalities such as communication, service discovery need to be functioning efficiently in both small and large scale environment. Scalability regarding addressing can be taken as an example. IPv4 address is finishing, object-to-object communication needs huge number of IP addresses in order to uniquely identify each objects. As a scalable solution, IPv6 can be used which can accommodate as many things as required to include in the IoT.

    o Interoperability: – World of physical objects is extremely diverse. They have different communication, information and processing capabilities. Each object would also be subjected to very different conditions such as power energy vailability and communication

    bandwidth requirement. In order to facilitate communication and cooperation common practices and standards are required. Interoperability issue includes device, services heterogeneities. Devices are small, large,

    with continuously powered, without power supply. Interoperability solution should be maintained to provide seamless interaction among them.

    Service

    description, publishing, and discovery mechanisms

    should be interoperable otherwise the IoT will be

    converted into islands of heterogeneous object network.

    o Discovery: – In dynamic environment of ubiquitous networking, suitable services for objects must

    be

    automatically identified. As users want to know

    product information and their availability all the time,

    it requires appropriate semantic means of describing their functionality.

    o Data Volumes: – Depending on application and use cases there is variance in data volume. In a

    sufficient energy source. Passive RFID does not

    scenario where there is brief collaboration among

    objects data volume will be less. However, in case

    where there are large number of objects and interact

    among very frequently there are large volume of data.

    How to handle big volume of data is one of the important challenges of ubiquitous networking.

    Volume can be considered either from device or as a

    whole network perspective. Each object has

    augmented memory, storage and processing

    capability. If there are a large number of peer objects

    communicating with each other, object runs out of

    processing, memory and storage. From network

    perspective it is also difficult to handle bulk amount

    of data if objects produce huge bytes of data

    regularly. Solution can be periodic communication between objects or some data compression and optimization techniques.

    o Power Supply: – Scope of object is broad in the IoT. It ranges from small to large. Moreover, things

    move around and difficult to connect to power supply

    all the time. So they need to operate with self-

    contain power supply, which requires reader in order to get information from it. Not all objects can be connected to continuous power supply also, providing battery for each small object may not be feasible. Therefore, energy efficient communication mechanisms are essential.

    • Fault-Tolerance: – The IoT consists of objects

      have less power. They are more dynamic and mobile compare to current state. However, users rely and believe that network will function properly. To maintain robust and trust worthy dynamic ubiquitous networking requires redundancy in several levels and ability to automatically adapt to changed conditions depending on the required quality of service.

    • Security and personal privacy: –

      Users are fighting

      with security and privacy issue of current

      in large extent. When it will be broaden in to ubiquitous networking, there is even more threat of security and personal privacy. Confidentiality, authenticity and

      trustworthiness communication partners need to be maintained. Users may want to give things limited service access not allowing them to communicate in uncontrolled manner.

    • Device adaptation: – Initially started with retail and

      logistic application, the IoT is covering very general applications scenario integrating things to the network. It allows objects to collaborate each other and with person. There are heterogeneous devices, application scenarios, data

      format, and communication network. Each connected objects should be able to adapt the situation where it is now. When a person with smart phone enters home, it should adapt communication mechanism, addressing and localized environment. When it reaches in office environment it should adapt with new situation where the mechanisms available in home can be different. Adaption in many senses should be maintained.

  4. EXISTING SYSTEM

    Zhang et al. [4] presented a suite of novel schemes that can ensure data confidentiality against master nodes and also enable the network owner to verify with very high probability the authenticity and completeness of any query result by inspecting the spatial and temporal relationships among the returned data. Detailed performance evaluations confirm the high efficacy and efficiency of the proposed schemes.

    Cordasco and Wetzel [5] demonstrated the results of implementation and evaluation of both protocols on real

    resource-limited hardware. The expected difference

    between

    the two protocols was shown to be consistent with this real

    world scenario. These experiments showed that there is

    significant room between the two protocols for a secure hybrid protocol to be developed which takes advantage of the

    strongest points of both. Future work needs to delve further into the extensive body of work on various trust metrics. This includes the testing of other trust metrics for use in ad-hoc routing as well as developing the aforementioned hybrid protocols and testing their performance against the results presented in this paper. In addition, it is necessary to test the quality of the routing decisions produced by all of these protocols in a malicious environment.

    InternYetu et al. [6] analyzed a novel yet important issue of fine- grained data access control for distributed storage in WSNs. To address the problem, they proposed a

    scheme called FDAC in which each sensor node is assiogfned a set of attributes, and each user is assigned an access structure which designates the access capability of the user. The sensor data is encrypted under the attributes such that only the

    users with the intended access structure are able to decrypt.

    Ning et al. [7] developed message specific puzzles, a weak authentication mechanism, to mitigate DoS attacks against

    signature-based and µTESLA-based broadcast authentication

    in wireless sensor networks. This approach has a number of

    nice properties: First, a weak authenticator can be efficiently

    verified by a regular sensor node, but takes a computationally

    powerful attacker a substantial amount of time to forge.

    Second, a weak authenticator cannot be pre- computed without

    a non-reusable (or short-lived) key disclosed only in a valid broadcast packet. Thus, an attacker cannot start the expensive

    computation to forge a weak authenticator without seeing a valid broadcast packet. Third, even if an attacker has sufficient

    computational resources to forge one or more weak

    authenticators, it is difficult to reuse these forged weak

    authenticators. Thus, this weak authentication mechanism

    substantially increases the difficulty of launching successful

    DoS attacks against signature based and

    µTESLA-based broadcast authentication.

    Zhang et al. [8] developed a formal framework and theory

    to investigate the correctness, optimality, inter- operatively of

    trust-based routing protocols for WANETs. Their results

    obtained here can be extended in two ways. (1) For indirect

    trust inference problems, they only consider the situation when

    all trusts in a WANET are transitive. When transitive and no transitive trust coexist in a WANET, a new

    and any cast are totally different from that for unicast, and the

    concept of path selection will be replaced by tree selection. Therefore, these topics should be further investigated.

    Marti et al. [9] have used a watchdog that identifies

    misbehaving nodes and a patl~rater that helps routing protocols avoids these nodes. Through simulation they evaluate watchdog and pathrater using packet throughput, percentage of overhead (routing) transmissions, and the

    accuracy of misbehaving node detection. When used together

    in a network with moderate mobility, the two techniques

    increase throughput by 17% in the presence of 40%

    misbehaving nodes, while increasing the percentage of

    overhead transmissions from the standard routing protocol's

    9% to 17%. During extreme mobility, watchdog and pathrater

    can increase network throughput by 27%, while increasing the

    overhead transmissions from the standard routing protocol's

    12% to 24%.

    Zakhary et al. [10] discussed how they integrate two kinds of centrality in their reputation-based protocol and propose a number of optimizations for more efficient node monitoring and trust resolution such as selective deviation test and adaptive expiration timer. Their early prototype

    implementation over AODV confirms and extends the results published. The results presented in this paper show that the throughput remains above 70% in the presence of the

    increasing number of black hole nodes while the jitter

    algebraic structure

    for a combined trust metric is needed and consequently new

    algorithm should be designed to infer indirect trust under no transitive trust constraints. (2) From routing s point of view, in their framework they only consider topology- based routing

    protocols. They can extend their study to location-based

    routing like geographic routing, which is popular for

    WANETs. Also in this paper they restrict ourselves to unicast

    routing. Obviously, the trust metrics for multicast, broadcast,

    and delay decrease and are below AODV. They also discuss the impact the distribution of centrality and reputation of their nodes has on the time needed to isolate malicious nodes. Their subsequent work will focus on studying the impact of centrality and configuration parameters on the protocol performance in relation to network throughput, network delay, network jitter and the protocol detection ratio.

    Szabo and Hauert [11] considered: the risk adverse loners

    who are unwilling to participate in the social enterprise and

    rather rely on small but fixed earnings. This results in a rock-

    scissors-paper type of cyclic dominance of the three strategies.

    In the prisoner s dilemma, the effects of voluntary

    participation crucially depend on the underlying population

    structure. While leading to homogeneous states of all loners in

    well-mixed populations, they demonstrate that cyclic

    dominance produces self-organizing patterns on square lattices

    but leads to different types of oscillatory behavior on random

    regular graphs: the temptation to defect determines whether

    damped, periodic, or increasing oscillations occur. These

    Monte Carlo simulations are complemented by predictions

    from pair approximation reproducing the results for random

    regular graphs particularly well.

    Szabo et al. [12] have exhibited a phase transition from a

    mixed state of cooperators and defectors to a homogeneous

    one where only the defectors remain alive. Using systematic

    Monte Carlo simulations and different levels of the generalized mean-field approximations they have determined the phase boundaries (critical points) separating the two phases on the plane of the temperature (noise) and temptation

    to choose defection. In the zero temperature limit this analysis

    suggests that the cooperation can be sustained only for those

    connectivity structures where three-site clique percolation

    occurs.

  5. FEATURES OF THE IOT

      • Overall aspects:- (Order(s) of magnitude bigger

        than the Internet, No computers or humans at endpoint, Inherently mobile, disconnected,

        unattended)

      • Applications/services aspects:- There are many use

        cases among various stakeholders in IoT environment. Each device/machine can be used for multiple applications/services with different

        characteristics.

      • Networking aspects:- It is required to provide a

        common communications technology that supports all applications/services as well as heterogeneous

      • Link/physical layer aspects:- There are various

        types of networking interfaces which have different coverage and data rates. These environments have

        the characteristics of low power and lossy

        networks like Bluetooth, IEEE

        802.

        15.4

        (6LoWPAN, ZigBee), NFC etc.

      • Smart/connected bjects aspects:-

        Smart/connected

        objects are heterogeneous with different sizes, mobility, power, connectivity and protocols. A physical object interacts with several entities, performs various functionalities and

        gener

        ates

        data that might be used by other entities. Usually resources of these objects are limited.

      • Smart environment aspects:- Smart environment

    which consists of networks of federated sensors

    and actuators can be extended from homes/offices to buildings/cities.From residential home, end-to-

    end large scale services such as smart cities can be considered.

  6. CONCLUSION

It is apparent that the potential of the wireless sensor networks (WSN) paradigm will be completely unleashed once it is connected to the Internet, fetching part of the Internet of Things (IoT). The Internet of Things (IoT) presented the

insurrection already below way that is seeing a growing

number of internet enabled devices which can network and

converse with each other and with other web-enabled gadgets.

IoT refers to a state where Things (e.g. objects, environments,

vehicles and clothing) will have more and more information

connected with them and may have the aptitude to sense,

communicate, network and produce new

information, flattering an integral part of the Internet." REFERENCES

[1]IBM: A Smarter Planet, http://www.ibm.com/smarterplanet/, Accessed on October 2010.

[2]G. Montenegro, N. Kushalnagar, J. Hui, D. Culler. RFC 4944:

Transmission of IPv6 Packets over IEEE 802.15.4 Networks. 2007 [3]Libelium: Interfacing the Sensor Networks with the Web 2.0,

http://www.libelium.com/, Accessed on October 2010

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