Hongbing Cheng

Identity-Based Key Agreement and Encryption For Wireless Sensor Networks

It is an important challenge to find out suitable cryptography for wireless sensor networks (WSN) because of the limitations of power, computation capability, and storage resources. Many schemes based on public or symmetric key cryptography are investigated. Recently, a practical identity-based encryption technique is proposed. In this article, we present an identity-based key agreement and encryption scheme for WSNs. This scheme is an elliptic curve cryptography type algorithm. First, we briefly review regarding identity-based encryption and decryption, particularly, the Boneh-Franklin algorithms. Then we describe a key agreement and encryption scheme on the basis of the Boneh-Franklin algorithms for WSNs. We discuss the efficiency and security of our scheme by comparing it with traditional public key technique and symmetric key technique.

Secure big data storage and sharing scheme for cloud tenants

The Cloud is increasingly being used to store and process big data for its tenants and classical security mechanisms using encryption are neither sufficiently efficient nor suited to the task of protecting big data in the Cloud. In this paper, we present an alternative approach which divides big data into sequenced parts and stores them among multiple Cloud storage service providers. Instead of protecting the big data itself, the proposed scheme protects the mapping of the various data elements to each provider using a trapdoor function. Analysis, comparison and simulation prove that the proposed scheme is efficient and secure for the big data of Cloud tenants.

A novel intrusion detection algorithm for wireless sensor networks

Wireless sensor network (WSN) is an emerging important research area. Because WSNs in general and in nature are unattended and physically reachable from the outside world, they could be vulnerable to physical attacks in the form of node capture or node destruction. These forms of attacks are hard to protect against and require intelligent prevention methods. It is necessary for WSNs to have security measures in place as to prevent an intruder from inserting compromised nodes in order to decimate or disturb the network performance. In this paper we present an intrusion detection algorithm for wireless sensor networks which does not require prior knowledge of network behavior or a learning period in order to establish this knowledge. We have taken a more practical approach and constructed this algorithm with small to middle-size networks in mind, like home or office networks. The proposed algorithm is also dynamic in nature as to cope with new and unknown attack types. This algorithm is intended to protect the network and ensure reliable and accurate aggregated sensor readings. Theoretical simulation results indicate that compromised nodes can be detected with high accuracy and low false alarm probability.

An Identity-Based Encryption Scheme for Broadcasting

It is a challenge to find out suitable cryptography for wireless sensor networks (WSN) due to limitations of power, computation capability and storage resources. Many schemes based on public or symmetric key cryptography are investigated. We propose an identity-based broadcast encryption scheme, which can be used for key distribution or directly broadcasting message. The scheme is also suitable for general kind of networks. We review first identity-based encryption (IBE) and decryption, particularly, the Boneh-Franklin (BF) algorithm. Then we describe a key agreement and encryption scheme based on the Boneh-Franklin algorithms. We discuss the efficiency and security of our scheme by comparing with traditional public key technique and symmetric key technique.

Securing big data in the Cloud by protected mapping over multiple providers

The Cloud is increasingly being used to store and process big data, and conventional security mechanisms using encryption are either not sufficiently efficient or not suited to the task of protecting big data in the Cloud. In this paper we present an alternative approach which divides big data among multiple Cloud providers, and instead of protecting the data itself, protects the mapping of the various data elements to each provider using a trapdoor function. Our initial analysis indicates that this is an efficient and secure approach for securing big data.