Efficient Key Generation by Exploiting Randomness from Channel Responses of Individual OFDM Subcarriers

Key generation from the randomness of wireless channels is a promising technique to establish a secret cryptographic key securely between legitimate users. This paper proposes a new approach to extract keys efficiently from channel responses of individual orthogonal frequency-division multiplexing (OFDM) subcarriers. The efficiency is achieved by (i) fully exploiting randomness from time and frequency domains and (ii) improving the cross-correlation of the channel measurements. Through the theoretical modelling of the time and frequency autocorrelation relationship of the OFDM subcarrier's channel responses, we can obtain the optimal probing rate and use multiple uncorrelated subcarriers as random sources. We also study the effects of non-simultaneous measurements and noise on the cross-correlation of the channel measurements. We find the cross-correlation is mainly impacted by noise effects in a slow fading channel and use a low pass filter (LPF) to reduce the key disagreement rate and extend the system's working signal-to-noise ratio range. The system is evaluated in terms of randomness, key generation rate, and key disagreement rate, verifying that it is feasible to extract randomness from both time and frequency domains of the OFDM subcarrier's channel responses.

Quantum-information processing with noisy cluster states

We provide an analysis of basic quantum-information processing protocols under the effect of intrinsic nonidealities in cluster states. These nonidealities are based on the introduction of randomness in the entangling steps that create the cluster state and are motivated by the unavoidable imperfections faced in creating entanglement using condensed-matter systems. Aided by the use of an alternative and very efficient method to construct cluster-state configurations, which relies on the concatenation of fundamental cluster structures, we address quantum-state transfer and various fundamental gate simulations through noisy cluster states. We find that a winning strategy to limit the effects of noise is the management of small clusters processed via just a few measurements. Our study also reinforces recent ideas related to the optical implementation of a one-way quantum computer.

Systematic random sampling of the comet assay

The comet assay is a technique used to quantify DNA damage and repair at a cellular level. In the assay, cells are embedded in agarose and the cellular content is stripped away leaving only the DNA trapped in an agarose cavity which can then be electrophoresed. The damaged DNA can enter the agarose and migrate while the undamaged DNA cannot and is retained. DNA damage is measured as the proportion of the migratory ‘tail’ DNA compared to the total DNA in the cell. The fundamental basis of these arbitrary values is obtained in the comet acquisition phase using fluorescence microscopy with a stoichiometric stain in tandem with image analysis software. Current methods deployed in such an acquisition are expected to be both objectively and randomly obtained. In this paper we examine the ‘randomness’ of the acquisition phase and suggest an alternative method that offers both objective and unbiased comet selection. In order to achieve this, we have adopted a survey sampling approach widely used in stereology, which offers a method of systematic random sampling (SRS). This is desirable as it offers an impartial and reproducible method of comet analysis that can be used both manually or automated. By making use of an unbiased sampling frame and using microscope verniers, we are able to increase the precision of estimates of DNA damage. Results obtained from a multiple-user pooled variation experiment showed that the SRS technique attained a lower variability than that of the traditional approach. The analysis of a single user with repetition experiment showed greater individual variances while not being detrimental to overall averages. This would suggest that the SRS method offers a better reflection of DNA damage for a given slide and also offers better user reproducibility.

Field-programmable true random number generator

True random number generation is crucial in hardware security applications. Proposed is a voltage-controlled true random number generator that is inherently field-programmable. This facilitates increased entropy as a randomness source because there is more than one configuration state which lends itself to more compact and low-power architectures. It is evaluated through electrical characterisation and statistically through industry-standard randomness tests. To the best of the author's knowledge, it is one of the most efficient designs to date with respect to hardware design metrics.

Reliability Assessment of 3-D Space Frame Structures Applying Stochastic Finite Element Analysis

Throughout design development of satellite structure, stress engineer is usually challenged with randomness in applied loads and material properties. To overcome such problem, a risk-based design is applied which estimates satellite structure probability of failure under static and thermal loads. Determining probability of failure can help to update initially applied factors of safety that were used during structure preliminary design phase. These factors of safety are related to the satellite mission objective. Sensitivity-based analysis is to be implemented in the context of finite element analysis (probabilistic finite element method or stochastic finite element method (SFEM)) to determine the probability of failure for satellite structure or one of its components.

How do grazers achieve their distribution? A continuum of models from random diffusion to the ideal free distribution using biased random walks

A conceptual model is described for generating distributions of grazing animals, according to their searching behavior, to investigate the mechanisms animals may use to achieve their distributions. The model simulates behaviors ranging from random diffusion, through taxis and cognitively aided navigation (i.e., using memory), to the optimization extreme of the Ideal Free Distribution. These behaviors are generated from simulation of biased diffusion that operates at multiple scales simultaneously, formalizing ideas of multiple-scale foraging behavior. It uses probabilistic bias to represent decisions, allowing multiple search goals to be combined (e.g., foraging and social goals) and the representation of suboptimal behavior. By allowing bias to arise at multiple scales within the environment, each weighted relative to the others, the model can represent different scales of simultaneous decision-making and scale-dependent behavior. The model also allows different constraints to be applied to the animal's ability (e.g., applying food-patch accessibility and information limits). Simulations show that foraging-decision randomness and spatial scale of decision bias have potentially profound effects on both animal intake rate and the distribution of resources in the environment. Spatial variograms show that foraging strategies can differentially change the spatial pattern of resource abundance in the environment to one characteristic of the foraging strategy.</

Ordering effects and choice set awareness in repeat-response stated preference studies

We present an experiment designed to investigate the presence and nature of ordering effects within repeat-response stated preference (SP) studies. Our experiment takes the form of a large sample, full-factorial, discrete choice SP exercise investigating preferences for tap water quality improvements. Our study simultaneously investigates a variety of different forms of position-dependent and precedent-dependent ordering effect in preferences for attributes and options and in response randomness. We also examine whether advanced disclosure of the choice tasks impacts on the probability of exhibiting ordering effects of those different types. We analyze our data both non-parametrically and parametrically and find robust evidence for ordering effects. We also find that the patterns of order effect in respondents' preferences are significantly changed but not eradicated by the advanced disclosure of choice tasks a finding that offers insights into the choice behaviors underpinning order effects. © 2011 Elsevier Inc.

Making heads or tails of probability:an experiment with random generators

The equiprobability bias is a tendency for individuals to think of probabilistic events as 'equiprobable' by nature, and to judge outcomes that occur with different probabilities as equally likely. The equiprobability bias has been repeatedly found to be related to formal education in statistics, and it is claimed to be based on a misunderstanding of the concept of randomness.

Secure Key Generation from OFDM Subcarriers’ Channel Response

The ability to exchange keys between users is vital in any wireless based security system. A key generation technique exploits the randomness of the wireless channel is a promising alternative to existing key distribution techniques, e.g., public key cryptography. In this paper a secure key generation scheme based on the subcarriers’ channel responses in orthogonal frequencydivision multiplexing (OFDM) systems is proposed. We first implement a time-variant multipath channel with its channel impulse response modelled as a wide sense stationary (WSS) uncorrelated scattering random process and demonstrate that each subcarrier’s channel response is also a WSS random process. We then define the X% coherence time as the time required to produce an X% correlation coefficient in the autocorrelation function (ACF) of each channel tap, and find that when all the channel taps have the same Doppler power spectrum, all subcarriers’ channel responses has the same ACF as the channel taps. The subcarrier’s channel response is then sampled every X% coherence time and quantized into key bits. All the key sequences’ randomness is tested using National Institute of Standards and Technology (NIST) statistical test suite and the results indicate that the commonly used sampling interval as 50% coherence time cannot guarantee the randomness of the key sequence.

The Equiprobability Bias from a Mathematical and Psychological Perspective

The equiprobability bias (EB) is a tendency to believe that every process in which randomness is involved corresponds to a fair distribution, with equal probabilities for any possible outcome. The EB is known to affect both children and adults, and to increase with probability education. Because it results in probability errors resistant to pedagogical interventions, it has been described as a deep misconception about randomness: the erroneous belief that randomness implies uniformity. In the present paper, we show that the EB is actually not the result of a conceptual error about the definition of randomness. On the contrary, the mathematical theory of randomness does imply uniformity. However, the EB is still a bias, because people tend to assume uniformity even in the case of events that are not random. The pervasiveness of the EB reveals a paradox: The combination of random processes is not necessarily random. The link between the EB and this paradox is discussed, and suggestions are made regarding educational design to overcome difficulties encountered by students as a consequence of the EB.

Simultaneous Measurements of the Channel Response for Multiple Eavesdroppers Operating in the Vicinity of a Body Area Network at 2.45 GHz

Channel randomness can be exploited to generate secret keys. However, to ensure secrecy, it is necessary that the channel response of any eavesdropping party remain sufficiently de-correlated with that of the legitimate users'. In this paper, we investigate whether such de-correlation occurs for a body area network (BAN) operating in an indoor environment at 2.45 GHz. The hypothetical BAN configuration consisted of two legitimate transceivers, one situated on the user's left wrist and the other on the user's waist. The eavesdroppers were positioned in either a co-located or distributed manner in the area surrounding the BAN user. Using the simultaneous channel response measured at the legitimate BAN nodes and the eavesdropper positions for stationary and mobile scenarios, we analyze the localized correlation coefficient. This allows us to determine if it is possible to generate secret keys in the presence of multiple eavesdroppers in an indoor environment. Our experimental results show that although channel reciprocity was observed for both the stationary and the mobile scenarios, a higher de-correlation between the legitimate users' channels was observed for the stationary case. This indicates that mobile scenarios are better suited for secret key generation.

Secure key generation from OFDM subcarriers' channel responses

The ability to exchange keys between users is vital in any wireless based security system. A key generation technique which exploits the randomness of the wireless channel is a promising alternative to existing key distribution techniques, e.g., public key cryptography. In this paper, a secure key generation scheme based on the subcarriers' channel responses in orthogonal frequency-division multiplexing (OFDM) systems is proposed. We first implement a time-variant multipath channel with its channel impulse response modelled as a wide sense stationary (WSS) uncorrelated scattering random process and demonstrate that each subcarrier's channel response is also a WSS random process. We then define the X% coherence time as the time required to produce an X% correlation coefficient in the autocorrelation function (ACF) of each channel tap, and find that when all the channel taps have the same Doppler power spectrum, all subcarriers' channel responses has the same ACF as the channel taps. The subcarrier's channel response is then sampled every X% coherence time and quantized into key bits. All the key sequences' randomness is tested using National Institute of Standards and Technology (NIST) statistical test suite and the results indicate that the commonly used sampling interval as 50% coherence time cannot guarantee the randomness of the key sequence.

Key Generation from Wireless Channels: A Review

Key generation from the randomness of wireless channels is a promising alternative to public key cryptography for the establishment of cryptographic keys between any two users. This paper reviews the current techniques for wireless key generation. The principles, performance metrics and key generation procedure are comprehensively surveyed. Methods for optimizing the performance of key generation are also discussed. Key generation applications in various environments are then introduced along with the challenges of applying the approach in each scenario. The paper concludes with some suggestions for future studies.

Verification of Key Generation from Individual OFDM Subcarrier's Channel Response

This paper presents a key generation system derived from the channel response of individual subcarrier in orthogonal frequency-division multiplexing (OFDM) systems. Practical aspects of the security were investigated by implementing our key generation scheme on a wireless open-access research platform (WARP), which enables us to obtain channel estimation of individual OFDM subcarriers, a feature not currently available in most commercial wireless interface cards. Channel response of individual OFDM subcarrier is usually a wide sense stationary random process, which allows us to find the optimal probing period and maximize the key generation rate. The implementation requires cross layer design as it involves interaction between physical and MAC layer. We have experimentally verified the feasibility and principles of key generation, and also evaluated the performance of our system in terms of randomness, key generation rate and key disagreement rate, which proves that OFDM subcarrier's channel responses are valid for key generation.

Time series wind power forecasting based on variant Gaussian process and TLBO

Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.