250 Int'l Conf. Security and Management SAM'15

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1 250 Int'l Conf. Security and Management SAM'15 Key Management for Secure Multicast Communication in Sensor Cloud Shoroq Odah Al Beladi, Firdous Kausar Department of Computer Science, Al Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia Abstract - Recently, data size has been largely increased and there is no enough storage and computation resources to handle these data. Sensor-Cloud scheme represents the best solution to solve this problem. In this paper, secure-multicast group key management protocol has been has been proposed in order to provide secure group communication within a dynamic Sensor-Cloud. The analysis of proposed protocol shows that it provides the properties of forward secrecy, backward secrecy, self-healing and periodic rekeying. We implement the proposed protocol on Tosssim simulator by using programming language nesc and TinyOS operating system. Simulation results are measured in term of throughput and packet loss and it has been found that it has high throughput and low packet loss. Keywords: Sensor-Cloud, Secure Multicast, Group Key Management Protocol, Wireless Sensor Networks, TinyOS 1 Introduction In the few last years, the Wireless Sensor Network (WSN) earns high attention from a large number of people, because it provides many effective solutions for many fields, like; monitoring of air pollution, forecasting of weather, traffic monitoring for citywide roads, and e-healthcare. On the other hand, expanding WSNs to large networks can lead to many problems and limitations [1]. Many designs of the vendor show that there is no ability to connect various sensor networks with others and it is impossible to sharing the data of sensor between various user groups. In addition, there are no enough resources of storage and computation to overcome the applications of large-size. The sensor network with large-size is a very important issue, so the Sensor-Cloud is used to handle this issue. This model can be described by combining the cloud with WSNs and it is a very efficient solution for this type of networks. This combination provides the data processing with high swift through the available Cloud structure with larger routing and through the massive processing power to support the user with fast response. The management of secure multicasting is a very important issue, so it is discussed here. The figure 1 below shows the structure of Sensor-Cloud [1]. Figure 1: Sensor-Cloud Structure [1] The security of sensor network can be improved by many services of security like; key management. The protocol of key management for WSNs must be light and simple because the communication bandwidth, processing power, memory space and battery life of the distributed nodes are limited. The scheme of random-key pre-distribution is very suitable for widely WSNs, where this scheme enables the communication between neighbor nodes only. In this scheme, the nodes selected a specified number of used key randomly before being scattered. Secure links are constructed between these nodes and their neighbors that possessing shared keys after the deployment. Furthermore, a path-key is constructed between every two neighbors that have not shared keys [2]. The techniques of encryption are the best solution to achieve secure group communication. All keys should be managed in a secure manner to distribute, update and create these keys in an efficient way in order to provide a secure communication for the group. Furthermore, the protocols of key establishment should be used to allocate group key among the group of entities in an effective and secured way. There are two main kinds of these protocols which are; Key Agreement Protocol (KAP) and Key Transfer Protocol (KTP). KTPs based on Key Generation Center (KGC) in order to provide the contacting information with appropriate group key. However, in KAPs, group key can be identified via interchanges the public keys that refer into two parties of communication and this can be achieved by communication bodies presence [3]. The schemes of Self-Healing Key Distribution aim to propagate useful information into the trusted users. By integrating the propagated information with the predistributed secrets, the trusted users became able to rebuild shared keys. However, useful information cannot be reached

2 Int'l Conf. Security and Management SAM' by the revoked users. Self-healing enables users to recover any lost key and this only requires the user to be a member in the key group. So, the off-line group member can immediately recover the lost keys of the session after the return to the online state [4,8]. In this work, a secure and efficient multicast key management protocol has been suggested to provide secure group communication in dynamic Sensor-Cloud with self-healing and periodic rekeying properties. Furthermore, the Backward Secrecy (BS) and the Forward Secrecy (FS) have been used in this design to protect the keys of the group. A securemulticast has been used to securely transmit the data between WSNs and the Cloud. TinyOS has been used to construct and simulate the suggested scheme architecture. This paper consists of other four sections: many related studies that related to this work have been discussed in section 2. The proposed scheme has been illustrated in section 3, where the results obtained have been discussed in section 4. A summary of the entire work has been provided in section 5. 2 Related Work Please A. Herrera et.al [5] proposed a Key distribution Protocol (KDP) using prevailing primitives of security to confirm interoperability and security for WSN. This suggested protocol was able to support the distributed nodes within WSN with a key of symmetric cryptography. The Trusted Platform Module (TPM) has been applied rather than ECC or RSA primitives of encryption. The obtained results showed that this suggested protocol was able to provide a strong level of interoperability and security. Also, it was able to preserve the efficiency of energy and the scaling ability. D. M. Mani [6] presented the wireless Sensor Networks (WSNs) secure multicasting protocol. Many nodes of sensors and base stations were included in Wireless Sensor Networks (WSNs), where the external events provide simulated to those nodes. One of the most important services of security in WSN is the transmission of the message, which is susceptible to many attacks kinds. In the proposed research, there were many schemes that proposed to get services to WSNs, like multilevel μ TESLA and μ TESLA. But, the problem of message authentication delay led to suffer these schemes from many attacks of Denial of Service (DoS). In wireless devices, the Elliptic Curve Cryptography (ECC) is largely deployed because its features over RSA, also ECC is used in the devices that their battery life, memory life, and computing power are bounded. In addition, there is another scheme is largely used in authentication of multicast, which is Public Key Cryptography (PKC). But using PKC in a dense way for authentication process is very expensive to supply restricted sensor nodes. The most important parameter in WSN is the lifetime of sensor nodes. The scheme of Low Energy Adaptive Clustering Hierarchy (LEACH) has motivated several researchers that focus on the extension of node lifetime. A short survey has been proposed in [7] to propose various strategies to select the cluster-head and to compare the cost that demanded to select the cluster-head based on transmission method, cluster creation, rounds, information of cluster and cluster-heads distribution. K. Ramesh et.al [7] compared many schemes such as; deterministic schemes, schemes of cluster-head selecting, using a hybrid type of clustering, probabilistic schemes of constant parameters and probabilistic schemes of adaptive resources. The obtained results show that the distance between middle cluster-head and sending cluster-head in multi-hope sending of data should be equal through various rounds of data collecting. The purpose of this set was to make the amount of consumed energy equal among the transmitted data from or to the base-station. Furthermore, the results confirm that these schemes were not the best, so more stable, energy efficient and scalable schemes of clustering should be found. A distribution scheme of self-healing distribution has been evolved in [8] to achieve the secure multicast communication of groups in the environment of WSN. Many techniques to leave and combine the groups and a strategy to scatter the rekeying messages securely have been also applied. According to this suggested scheme, the nodes have been separated into many collections, where the Group Controller (GC) has been used to manage all these collections. But, the dynamicity of these collections leads to perform the regrouping process after a certain duration of time. The obtained results confirmed that the proposed scheme met the requirements of security for backward and forward secrecy. Furthermore, applying the Message Digest 5 (MD5) and Secure Hash Algorithm-1 (SHA-1) algorithms; which are one-way segmentation algorithms, confirms that the suggested scheme feasibility is suitable for the present technology of WSN. Also, the results of this scheme are attractive and scalable for the huge and dynamic collections. A novel scheme of randomized-key pre-distribution has been implemented in [9] through TinyOS mot Simulator (TOSSIM) in order to provide WSN with high secure simulation. The TinyViz, has been used to transfer messages among nods and to visualize this proposed scheme. Through this scheme, the nodes have been randomly scattered over a specific area. The pseudo generator of random number was used to construct a pool of key with their IDs. During the discovery shared of shared key, the IDs of key have not broadcasting into all nodes but these IDs only sent to the desired nodes for communication in order to improve the efficiency of communication and to save resources loads. In this study, this proposed model has been analyzed depending on Cryptography and Erdos-Renyi (ER) model. The obtained results show that the model of Cryptography was more appropriate than an ER model for safe WSNs.

3 252 Int'l Conf. Security and Management SAM'15 3 Proposed Scheme This section describes the scheme architecture and the main protocols that applied within this scheme. 3.1 Sensor-Cloud Architecture The architecture of Sensor-Cloud consists of two main sides; WSN Side and Sensor-Cloud Side. This architecture links the WSNs with three distinct network elements. These are defined below: 1) Sensor Nodes (SN) these are the leaf nodes (end-nodes) in the sensor-network which do the actual sampling. Each sensor-node has a unique sensor node id. 2) Group-Coordinators (GC) the large amount of leaf nodes are harder to manage, therefore, they are grouped. These groups consists of the Group-Coordinator which manages various administrative task such as renewing session keys/ revoking node permission, etc. They also act as the data aggregation point for the all the nodes assigned to its particular group. 3) Cloud-Gateway (CG) all the Group-Coordinators are connected to the Cloud-Gateway via the Internet. Also the Cloud-Gateway handles all the data-aggregation from each of the sensor-node groups connected to it. This architecture is shown in the Figure 2. Figure 2: Sensor-Cloud Architecture 3.2 Protocol Features The protocol is optimized for the following features: 1. Optimized for Data Aggregation: We take advantage of the fact that many of these sensor-networks operates in particular manner, where their main operation is to aggregate the sensor data into the back-end infrastructure. The leaf-nodes rarely have to communicate among themselves. Therefore the protocol-suit can optimized for that particular operation. 2. Low Cost Session re-keying: The symmetric keys used for communication sessions between the leaf-nodes and the group-coordinator need to be updated periodically to avoid security vulnerabilities. Given the low-cost and simple hardware capabilities of the leaf-nodes, it is not possible to store large number of session keys at the node installation as that would costly in-terms of storage. Therefore we propose a mechanism that allows the session keys to be derived from a simple sequence of random seeds installed at the node set-up stage. 3. Key revoking: When a node is suspected of being compromised the node permission required to be revoked as the data it provides will potentially corrupt the aggregated data from the entire set of nodes. This is often achieved through the revoking the session-key for that particular node. But often in multi-cast group communication protocols this operation requires the participation of all the nodes in the group and is costly. In the protocol proposed below, the revoking permission for a particular leaf-node only require simple operation at the Group-Coordinator. 3.3 Protocol Steps The protocol execution is divided into two stages 1) The initiation and set-up stage 2) Operational stage These two stages are described in the following section: Initiation and Setup Stage 1. Node Ids assignment: Each of the Leaf-Nodes are assigned a unique id, also the group-coordinators are assigned a unique Id. 2. The Topology: we assume for simplicity that the leaf-nodes arranged in a star-topology, where each leaf-node can reach the Group-Coordinator in one hop. 3. Administrative Key Assignment: Each leaf-node is installed with a random and unique administrative-key. The corresponding group-coordinator is also installed with the set of administrative keys for all the leaf-nodes within its group. 4. Assignment of random sequence of seeds: Each leaf-node is installed with a random sequence of seeds (random numbers). The corresponding group-coordinator is installed with all the seed sequences belong to all the node-ids within its group. This is depicted in the table below. 5. The second stage of the data-transfer: the data that is sent from the leaf-nodes to the Group-Coordinators need to be sent to the back-end Cloud Infrastructure for final storage and analysis. This is node using the asymmetric cryptographic

4 Int'l Conf. Security and Management SAM' methods. To this end, the all the GC nodes are installed with a public key of the Cloud Gateway. Leaf Node Node id Node id N Sequence of Seeds S_1, S_2, S_3. S_N S_1, S_2, S_3. S_N Operational Stage 1. Join Message: Leaf Node wishing to initiate a session with GC will send join message to the GC SN GC : {node_id}, {join:message_type, seed_id} node_admin_key This message request the GC to initiate the session with the Leaf-Node. The message contain the node_id of the leaf node, the message type and the random seed id. The random seed id is randomly picked from the sequence of seeds contained within the leaf-node. The latter two elements are encrypted with the admin_key installed at the initiation. 2. When GC receives the join message from the Leaf-Node, it look up the admin key for the node id in the admin key table and decrypts the message. Then it retrieves the seed_id and looks up the seed_id in the seed sequence table using: lookup (node id, seed id) => seed. Then it uses the seed to produce the session key as described below. 3. The session key is produced using the admin key material and the random seed as follows: MD5_Hash (admin_key XOR seed) =>Session key material 4. Now since both the Leaf-Node and GC is able to create the session key, a session can now be initiated. This is done by GC sending a session acknowledgement message to notify the leaf-node that a session was successfully initiated. GC SN: {node_id}, {session_ack:message_type } session-key 5. Data Transfer Mode: this is the standard mode of operation for the system, where the sensor data are transferred for the cloud infrastructure. SN GC: node_id {data: message_type, data_byte1, data_byte_2,, data_byte_n} session-key When the Group-Coordinator receive the data, it looks-up the current session-key table where all the keys for active sessions are stored using the node_id. Then uses that key to decrypts the message. See below how the next stage of the protocol where the data is sent to the cloud gateway is handled. 6. Transfer to Cloud: The Group-Coordinator then encrypts all the messages it receives from the Leaf- Nodes using the public key of the Cloud Gateway (CG) as flows: GC CG : {node id, Group_Coordinator id, data } Cloud_Gateway_public_key If there a need for communicating between leaf-node with a group or nodes between groups. This can be achieved by addition another two message types (intra-group, inter-group). These messages need to send via the GC. If the message is of type Intra-Group the message will be routed to the node within the group. Else, if the message type is Inter-Group, then the message need to contain the Group id in addition to the node id, which can be sent to the appropriate GC via the Cloud-Gateway. 4 Performance Analysis 4.1 Scheme Framework The suggested system has been constructed by the TOSSIM Simulator, where it aims to provide the applications of TinyOS with a simulation with high validity. Due to this, this simulator concentrates on simulating the execution of the proposed protocol on TinyOS. By this simulator, the users can analyze, test and debug the algorithms within the repeatable and controlled environment. Also, this simulator operates on the PC, so the TinyOS code can be examined by the tools of developments and the debuggers. The architecture of TinyOS allows the rapid implementation and innovation while reducing the size of code as demanded by the memory of server limits the network of inherent sensor. In addition, TinyOS has three main features that impact on the design of nesc, these features are; operations of split-phase, the simple concurrency model that based on the events and componentbased construction. In this work, WSNs that consist of sensor nodes have been constructed. The wireless BSs provide the communication channels between the WSNs and the Cloud. The required code to define the WSNs and the BS has been written by nesc, where the code of applying the protocol of key management, symmetric key, Backward Secrecy and Forward Secrecy have been included within this code. The flowchart of the designed system is shown in Figure 3.

5 254 Int'l Conf. Security and Management SAM'15 the key reasons for this loss. Within the WSNs, packets are lost due to the packet dropping or malicious non-forwarding that caused by the compromised nodes or the adversary. Within this work, the number of pack lost has been measured for the total data that transmitted from WSNs to the Cloud. 5 Obtained Results The results of the simulation and simulation scenario have been shown and discussed in this section. 5.1 Simulation Setup The initial simulation set up consists of two groups each consisting of 10 nodes, node id 1 connected to nodes 2-10, and node id 11 connected to nodes The network topology for each group is a star- topology where each of the leaf-nodes are connected to the group-coordinator with a single hop. In this setup nodes 1 and 11 are the group-coordinators. The leaf nodes will be sending packets of data periodically to the group-coordinators (at 5Hz frequency). Since we do not have actual sensor data values to send in the packets, we use a counter that is incremented at 5Hz (that is every 200 miliseconds). This counter value is used as the data that is sent over the network. This setup simulate a typical dataaggregation sensor network. Figure 3: Scheme Flowchart. 4.2 Measurements By this work, many parameters can be measured to evaluate the performance of the suggested scheme. These measurements are; The throughput This concept can be described by the amount of the data transmitted from the source node to the node of the destination. Furthermore, it can be defined as the amount of data processed within a certain time amount. Also, it defines as the average bits number that successfully transmitted per second. Within this work, the throughput has been measured for the data transmitted from the WSNs to the Cloud. This term ensures the reliability of this proposed system Packet Loss By this term, the number of packet losses can be measured. The heavy traffic, delay, collisions and buffer overflows, are Figure 4: Packet loss vs number of nodes. As shown in Figure 4 above the value of packet loss is increased with the number of nodes that existed within the cluster. This figure represent the behavior of packet loss in general. However within this design, applying GKMP helps to minimize the number of lost packet through the self-healing property.

6 Int'l Conf. Security and Management SAM' [3] R. V. Rao, K. Selvamani and R. Elakkiya, A Secure Key Transfer Protocol for Group Communication, Advanced Computing: An International Journal (ACIJ), 3 (6), pp , [4] B. Tian, S. Han, D.S. Tharam, S. Das, A self-healing key distribution scheme based on vector space secret sharing and one way hash chains, IEEE international symposium on a world of wireless, mobile and multimedia networks, WoWMoM 2008, pp.1,6, June [5] A. Herrera and W. Hu, A Key Distribution Protocol for Wireless Sensor Networks, 37th IEEE Conference on Local Computer Networks (LCN), pp.140,143, Oct Figure 5: Packet delivery vs packet transmission frequency. The Figure 5 illustrates the number of packet delivery with respect to the packet sent frequency. The data show the packet delivery reaches the equilibrium at around 85% between the 1-10 Hz packet injection rates from each individual node. The effective data throughput as opposed to the overall datathroughput depends on the efficient and effective design of the aggregation protocol. 6 CONCLUSION This paper presents a secure multicast group key management protocol for Sensor-Cloud in order to solve the problem of secure transfer of large size of data between WSN and cloud network. The suggested system architecture consists of two main sides; WSNs side and Cloud s side. The secure-multicast method has been used as a way to transmit the data. Furthermore, proposed secure multicast group key management protocol have been analyzed and provide the features of secure transmission of data, prevent data loss and to enhance the number of updated keys. We measure the throughput and packet loss to assess the performance level of the proposed protocol and determine, it achieve the desired results and performance. The obtained results confirm the stability of this protocol, where it has high throughput and low packet loss. 7 References [1] T. Nguyen and E. Huh, An efficient key management for secure multicast in Sensor-Cloud, ACIS/JNU International Conference on Computers, Networks, Systems, and Industrial Engineering, pp 1-7, [2] P.J. Chuang, T. H. Chao and B.Y. Li, Scalable Grouping Random Key Predistribution in Large Scale Wireless Sensor Networks, Tamkang Journal of Science and Engineering, 12(2), pp , [6] D. M. Mani, Secure Multicasting for Wireless Sensor Networks, IJREAT International Journal of Research in Engineering & Advanced Technology, 1(5), pp 1-8, [7] K. Ramesh and K. Somasundaram, A Comparative Study of Cluster-head Selection Algorithms in Wireless Sensor Networks, International Journal of Computer Science & Engineering Survey (IJCSES), 2(4), pp , [8] F. Kausar, S. Hussain, J. H.Park and A. Masood, Secure Group Communication with Self-healing and Rekeying in Wireless Sensor Networks, Third International Conference on Mobile Ad-Hoc and Sensor Networks, MSN 2007, Lecture Notes in Computer Science, pp , Beijing, China, December 12-14, [9] S. Verma and Prachi, Analysis of a New Random Key Pre-distribution Scheme for WSN Based on Random Graph Theory and Cryptography, Journal of Information and Data Management, 1(1), pp , [10] M. H. Ullah, J. No, G. H. Kim and S.Park, A Collaboration Mechanism Between Wireless Sensor Network and a Cloud through a Pub/Sub-based Middleware Service, The Fifth International Conference on Evolving Internet, pp.38-42, [11] K. Sun, P.Peng, P. Ning and C. Wang, Secure Distributed Cluster Formation in Wireless Sensor Networks, Computer Security Applications Conference, ACSAC '06. pp , Dec [12] O. Gaddour, A. Koubˆaa and M. Abid, SeGCom: A Secure Group Communication Mechanism in Cluster-Tree Wireless Sensor Networks, Communications and Networking, ComNet 2009, pp. 1-7, Nov [13] A. Diop, Y. Qi and Q. Wang, Efficient Group Key Management using Symmetric Key and Threshold Cryptography for Cluster based Wireless Sensor Networks, I.J. Computer Network and Information Security, pp. 9-18, 2014.