Position based key exchange:definitions and implementations

Chandran,et al.introduce the direction of position based cryptography at CRYPTO 2009.In position based cryptography,the position of a party is used to be its unique“credential”in order to realize the cryptographic tasks,such as position based encryption,position based signature,position based key exchange and so on.Position based key exchange,as a basic primitive in position based cryptography,can be used to establish a shared key based on the position of the participant.To begin with,this paper presents the notions of the prover-to-verifier mode and the prover-to-prover mode for position based key exchange.In the prover-to-verifier mode,a secret key can be shared between a prover and the verifiers according to the position of the prover.While in the prover-to-prover mode,two provers located at the valid positions can negotiate a shared key with the help of the verifiers and any other party whose position is illegal cannot obtain the shared key.At the same time,this paper formalizes two security definitions against colluding adversaries:position based prover-to-verifier key exchange and position based prover-to-prover key exchange.Then,this paper introduces the bounded retrieval model and the implementations of position based key exchange in two modes based on the bounded retrieval model.Finally,this paper discusses the position based key exchange protocols in two modes from both security and performance perspectives.

Context-Aware Adaptive Routing for Opportunistic Network

Opportunistic networking-forwarding messages in a disconnected mobile ad hoc network via any encountered nodes offers a new mechanism for exploiting the mobile devices that many users already carry. However, forwarding messages in such a network is trapped by many particular challenges, and some protocols have contributed to solve them partly. In this paper, we propose a Context-Aware Adaptive opportunistic Routing algorithm（CAAR）. The algorithm firstly predicts the approximate location and orientation of the destination node by using its movement key positions and historical communication records, and then calculates the best neighbor for the next hop by using location and velocity of neighbors. In the unpredictable cases, forwarding messages will be delivered to the more capable forwarding nodes or wait for another transmission while the capable node does not exist in the neighborhood. The proposed algorithm takes the movement pattern into consideration and can adapt different network topologies and movements. The experiment results show that the proposed routing algorithm outperforms the epidemic forwarding（EF） and the prophet forwarding（PF） in packet delivery ratio while ensuring low bandwidth overhead.