Abstract-Wireless Sensors Network (WSN) security is a major concern and many new protocols are being designed. Most of these protocols rely on cryptography, and therefore, require a Cryptographic Pseudo-Random Number Generator (CPRNG). However, designing an efficient and secure CPRNG for wireless sensor There are typically two types of generators: hardware-based and software-based. The hardware-based generators exploit the randomness which occurs in some physical phenomena. They usually require some additional hardware and are therefore, excluded in wireless sensor networks. The softwarebased generators may be based on processes such as system clock, elapsed time between keystrokes, mouse movement, user input or operating system values such as system load and, network statistics [7] . A well-designed software random generator should utilize as many good sources of randomness as are available, since some of them can be easily observed or manipulated. Each source should be sampled, and the sampled sequences should be combined using a randomness extractor, often a cryptographic hash function. The purpose of the extractor is to distill the true random bits from the sampled, sequences. Unfortunately, most of the usual sources of entropy do not exist on a sensor (a sensor does not have a mouse, keyboard, user interface and so on). Furthermore, network timing can easily be monitored on wireless channels and the sensor clock being very slow, the timings are easy to predict. Values from the sensors of the node may be used, however, they are not always present and may provide insufficient level of randomness or low secrecy. The contributions of this paper are twofold: 1) We first show that transmission bit errors on wireless sensor network are a very good source of randomness. In fact, we demonstrate that these errors are randomly distributed and uncorrelated from one sensor to another. Furthermore, we show that these errors are difficult to observe and manipulate by an attacker. 2) \e design and implement a practial random generator,
In REF , Francillon and Castelluccia have shown that transmission bit errors on a wireless sensor network are a potentially good source of entropy.
TinyRNG: A Cryptographic Random Number Generator for Wireless Sensors Network Nodes
2007 5th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks and Workshops
2007 5th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks and Workshops
Computer Science