AN EFFICIENT POINT TO POINT COMMUNICATION PROTOCOL FOR MOBILE CLOUD COMPUTING

Transcription

1 AN EFFICIENT POINT TO POINT COMMUNICATION PROTOCOL FOR MOBILE CLOUD COMPUTING Lavanya P J 1, Suresh P 2 1 PG Student, Dept of CSE, Sri Venkateshwara College of Engineering, lavanyachetana@gmail.com 2 Assistant professor, Dept of CSE, Sri Venkateshwara College of Engineering, Suresh.rvce@gmail.com ABSTRACT Since mobile cloud computing is increasing, it became the paradigm in changing the infrastructure of traditional mobile computing. Now a day s smart phones rely on virtual clones in the cloud. These clones will increase the communication and computation capabilities of smart phones, these clones will make the limited batteries last longer. For this we have a new privacy risks, communicating users will distribute the personal information among several parties. So to overcome these risks, this paper implements an end to end anonymous communication protocol in the network between two users. This protocol will have the properties of social networks and adhoc wireless networks. We consider an adversary model where cloud user will observe the portion of the communication this will collides with others to uncover the identity of the communicating users. And we analyze the security of our protocol and anonymity preserved against the above adversaries. And we compare with the existing system i.e Tor (The second generation onion router).to assess the performance of our protocol tor is tested on relative clones and on real testbed of 36 smart phones and relative clones. Keywords: anonymity, mobile cloud computing, Smartphone clones etc 1. INTRODUCTION Advances in mobile technologies have turned our Smartphone s into small, powerful devices that use to play, check s, watch movies, songs, other than call and text wherev er and whenever we are. Current Smartphone s have built in 3G/WiFi and Bluetooth technologies, these technologies outperform like the desktop computers of ten years ago. Since we are increasing in spread of technologies and applications the current smart phones suffer from a major drawback i.e. battery limit. Since current batteries cannot cope up with increasing complexity of mobile applications, this becomes more and more energy hungry. To address the need of optimizing energy consumption[1],some of the solutions focus on offloading mobile computation to the software clones of the real devices is the cloud [2], [3], [4],[5],[6],[7],[8]. We have clone2clone, where clones are connected to each other clones in a peer to peer fashion in the cloud, which allows the computation and communication offloading. These scenarios involve many entities which include the clones, the devices, cloud provider, and the cellular network operator. The cellular network provider and the cloud provider will handle all the communication and monitor within the network. This can monitor who is communicating with whom, how often or how frequently they are communicating and what amount of data is being exchanged. If the clones collude the information can be easily inferred to the end to end communications, this will cause the privacy of all the users in the system. The mobile computing scenario is therefore in worse condition in the mobile privacy problem. So, for all these risks we focus on the privacy problem and we propose a communication protocol. Which allows the communicating users should anonymously communicate with each other by using clones as the intermediatory nodes in the cloud computing environment. Our solution has some major features of Tor and some features which are not available in Tor. Here tor is the second generation onion router. It firstly provides the resiliency against end to end attack. Resiliency is in the form of size and time correlations. Tor doesn t have goal but it is must and should in our solution.

2 2. RELATED WORK In wired and wireless systems anonymous is most important issue, so most of the applications are based on this issue. And they use the concept of mixing, where mixing is a method where messages are sent along a chain of proxy nodes there are also called mixes that accumulate and forward source encrypted messages in batches. In wired systems tor is most popularly deployed in mix network. Tor achieves mixing by layer encrypting a message at the source selected chain each hop at the source selected chain called tor nodes it will decrypt the message, to the destination selected by the client the tor i.e. the last node of the tor sends the unencrypted message. Our solution leverages for some communication steps one approach is similar to the tor network where in tor uses the mix zones and for some steps originator is unpredictable because of the hidden terminal property of the networks. In our solution we use the most popularity of social networks platform this will give raise to the cloud computing and the anonymity schemes which will rely on the friendship nodes among the users while communication. This will use same as in the tor network, by assuming the friend nodes trust each other which communicating and they are based on the social trust. To build a onion routing they rely in trust relationships in social network for this reason the early methods proposing the anonymous schema are mostly inspired by tor. The social cloud in the paper [20] have nodes that trust the relationships are bounded b y the social ties. Our solution also uses trust among the friend nodes for the anonymous communication. Recently in the paper[27] presents an anonymous communication protocol which is aimed for anony mity of (α,β)in mobile hybrid networks. This also involve the cellular network and Wi-Fi communication links. In the paper [4] we assume that each clone in the cloud is associated with the Smartphone, clones of friend users these are interconnected by peer to peer links between them. 3. PROPOSED MODELS 3.1 System Model Write our system includes four different parties I. The Smartphone will manage the clone of their Smartphones and carry mobile devices for communication. II. The cellular network operator This will manage the cellular infrastructure and allowing smartphone users to access its service. III. A set of proxies It acts as a mediator between the smartphone user and the cloud infrastructure. IV. The cloud provider This will manage the infrastructure of the cloud and their computing resource. D C d i c i s di s ci S R O Set of mobile devices Set of device clones i-th mobile device i-th clone Friend-set of d i (including d i itself) Friend-set of c i (including c i itself) Sender of a communication Receiver of a communication Cellular network operator

3 Cp pr Adv SK cloud provider Proxy Adversory attacking users anonymity Symmetric key (K p,k s ) A public/private key pair [m]k Message m encrypted with key K TABLE : Notation FIGURE 1 : System model The smartphone users will communicate with each other through both the cellular network which is the middle layer in the network and wide range of wifi adhoc communication links which is bottom layer in the figure D is denoted as set of mobile devices and C is denoted as set of clones. Each mobile device d i D associated with a software clone c i C in the cloud platform, for backup, offloading computations and communication purposes. O and cp denoted as cellular network operator and cloud provider respectively. This cellular network operator will receive all the cellular communication, and it acts as a gateway between mobile peers and the cloud infrastructure. And cloud provider will manage all the cloud communications. Our system architecture also includes set of n proxies pr 1,.,pr 2, which acts as a mediator between all communication channels the devices and the clones in cloud. The proxies will keeps track of cloneid and clone public IP address. Proxies by using the cellular and cloud identites, make our anonymous protocol successful. Proxies hav private and pubilc key (K p pri,k s pri) and this is used when the device is communicating with the users device and the clone. Each communication among devices is bidirectional as a exchange af a set of messages between the communicating sender and receiver. 3.2 Anonymity Model Here we extend the concept of k-anonymity, this aims to hide the sender and receiver of the communication among the α and β possible devices respectively.user of the communication can travel on ad hoc wireless, cellular,

4 or cloud network channels, and they are exposed to attacks in each of the communication.the adversaries in our model are honest but curious, they can neither tamper the messages nor read the encrypted messages. Such messages are grouped as follows, Mallicious devices: The mallicious devies are the adversories of adhoc networks which intensionally attack the anonymity of the communication. Cellular network operator: This will measure the position of the device by observing the cellular antena. Cloud provider: This will eaves drop incomming and outgoing traffic of every clone. Malicious clone: Malicious clones are the clones which are under the control of malicious devices which are intentionally attacked by the anonymity of the communication protocol. 4. OUR SOLUTION To achive (α,β)- anonymity is the main goal of our protocol in the communication involving sender s,receiver r,and clones. In our protocol s and r communicate as follows: Firstly, sender s sends message anonymously to its clone cs this is send through the multi hop wifi netwo rk which will forword the message to the physical proximity of the devices. Secondly, After reaching message to cs, the message anonymously forward to the clone cr of r. the clone ci is associated with the cs and clone cj is associated with the cr are in the same social network. Thirdly, after reaching cr, via proxy,the cellular operator, and the device in the proximity of r, the message is distributed to the mobile devices r. finally, the receiver r can reply to the sender s by reusing the same path or by building the new path. 4.1 Sender communication In sender communication the user s will check in the friendship database and it will select randomly one of the friend clone in the friendship database which has the social network of at least α members. Then, by using a probabilistic multi hop wifi, the sender s sends the message to the proxy pr. After that pr forwards the message to the ci. After reaching ci, this will delivers the message to α of its friends including cs, this is the only one to decrypt the message. 4.2 Clone communication All the α devices after receiving the message will reply after the timestamp T. for the sender clone cs,m will be the response and it will forward to the destination clone cr. responses of the clones are randomly generated which will be having variable lengths. 4.3 Receiver communication In receiver communication the push approach is used to deliver the payload m to receive r. similar to the last communication after a time stamp T the β clone is received a message from cj. responses to cj I is bundle of M 4.4 Response commnication The communication between the sender s and receiver r is bidirectional, we have two approaches are used, I) the protocol is repeated as one way communication switching s with r. II) the messages from r to s follows the same path as s to r. 5. SYSTEM ARCHITECTURE Our system implements devices, clones and proxy components in the cellular infrastructure, 5.1 Device In device component by using the android app we achieve the anonymity of our protocol bythrough wifi we connect the devices in the proximity range We should handle the device clone communication.

5 FIGURE 2 : Architecture of device 5.2 Clone The clone side implementation is done through the software clones of the real devices. In this we have neighbor notification server which handles the notification of the devices which are send by the associate devices for any changes. In our system peer to peer networking is used. FIGURE 3 : Architecture of Clone 5.3 Proxy This is implemented in java. And this will handle the communication between the devices and the clones in the cloud. This is consists of java threads, the mainpersistentconnection will have the record of new device entering into the system. Receiver task will receive the messages coming from the clones or devices. Packethandler will receives the message and access the destination. And this will decrypt the message using the private key of proxy. Sender task will handle the messages which are directed to the clone.

6 CONCLUSION FIGURE 4: Architecture of Proxy In our solution we have the anonymity, where the end to end communication is used in Smartphones and clone are created where the clones are the copies of real devices which will handle the part of the communication in the network by having the properties of social networks and adhoc wireless networks. Where the social networks are used for the friend clones in the friendship database. And adhoc networks are used to transfer the data. we have good communication computations and backup of the data and the communication is honest and curious, it will collide with each other to uncover the identity of the communication. Finally we calculate the performance by comparing our protocol by tor for mobile android devices on two real testbeds. REFERENCES [1] M. V. Barbera, S. Kosta, A. Mei, V. C. Perta, and J. Stefa, CDroid: Towards a Cloud-Integrated Mobile Operating System, in Proc. Of IEEE INFOCOM 13, [2] R. Dingledine, N. Mathewson, and P. Syverson, Tor: The Second Generation Onion Router, in Proc. of the 13th USENIX Security Symposium, [3] C. Ardagna, M. Conti, M. Leone, and J. Stefa, Preserving smartphone users anonymity in cloudy days, in Proc. of MobiPST 13, [4] P. Mittal, M. Wright, and N. Borisov, Pisces: Anonymous communication using social networks, in arxiv: , [5] S. Seys and B. Preneel, ARM: anonymous routing protocol for mobile ad hoc networks, Int. J. Wire. Mob. Comput., vol. 3, pp , [6] Y. Zhang, W. Liu, W. Lou, and Y. Fang, MASK: Anonymous ondemand routing in mo bile ad hoc networks, IEEE TWC, vol. 21, pp , [7] B. G. Chun, S. Ihm, P. Maniatis, M. Naik, and A. Patti, Clonecloud: elastic execution between mobile device and cloud, in Proc. of EuroSys 11, [8] B. Levine, M. Reiter, C. Wang, and M. Wright, Timing attacks in lowlatency mix systems (extended abstract), in Proc. of FC 04, [9] N. Thiagarajan, G. Aggarwal, A. Nicoara, D. Boneh, and J. Singh, Who killed my battery?: analyzing mobile browser energy consumption, in Proc. of WWW 12, [10] S. Kosta, V. C. Perta, J. Stefa, P. Hui, and A. Mei, CloneDoc: Exploiting the Cloud to Leverage Secure Group Collaboration Mechanisms for Smartphones, in Proc. of IEEE INFOCOM 13, [11] C. Ardagna, S. Jajodia, P. Samarati, and A. Stavrou, Privacy pres ervation over untrusted mobile networks, in Privacy in Location Based Applications: Research Issues and Emerging Trends, C. Bettini, S. Jajodia, P. Samarati, and S. Wang, Eds. Springer, 2009.