Biblio

The randomness, ambiguity and some other uncertainties of trust relationships in Wireless Sensor Networks (WSNs) make existing trust management methods often unsatisfactory in terms of accuracy. This paper proposes a trust evaluation method based on cloud model for malicious node detection. The conversion between qualitative and quantitative sensor node trust degree is achieved. Firstly, nodes cooperate with each other to establish a standard cloud template for malicious nodes and a standard cloud template for normal nodes, so that malicious nodes have a qualitative description to be either malicious or normal. Secondly, the trust cloud template obtained during the interactions is matched against the previous standard templates to achieve the detection of malicious nodes. Simulation results demonstrate that the proposed method greatly improves the accuracy of malicious nodes detection.

Damgard et al. proposed a new primitive called access control encryption (ACE) [6] which not only protects the privacy of the message, but also controls the ability of the sender to send the message. We will give a new construction based on the Learning with Error (LWE) assumption [12], which is one of the two open problems in [6]. Although there are many public key encryption schemes based on LWE and supporting homomorphic operations. We find that not every scheme can be used to build ACE. In order to keep the security and correctness of ACE, the random constant chosen by the sanitizer should satisfy stricter condition. We also give a different security proof of ACE based on LWE from it based on DDH. We will see that although the modulus of LWE should be super-polynomial, the ACE scheme is still as secure as the general public key encryption scheme based on the lattice [5].