Abstract: A tax authority wants to take actions it knows will foster
the greatest degree of voluntary taxpayer compliance to reduce the
“tax gap.” This paper suggests that even if a tax authority could attain
a state of complete knowledge, there are constraints on whether and
to what extent such actions would result in reducing the macro-level
tax gap. These limits are not merely a consequence of finite agency
resources. They are inherent in the system itself. To show that this is
one possible interpretation of the tax gap data, the paper formulates
known results in a different way by analyzing tax compliance as a
population with a single covariate. This leads to a standard use of the
logistic map to analyze the dynamics of non-compliance growth or
decay over a sequence of periods. This formulation gives the same
results as the tax gap studies performed over the past fifty years
in the U.S. given the published margins of error. Limitations and
recommendations for future work are discussed, along with some
implications for tax policy.
Abstract: This paper presented a video watermarking algorithm based on wavelet chaotic neural network. First, to enhance binary image’s security, the algorithm encrypted it with double chaotic based on Arnold and Logistic map, Then, the host video was divided into some equal frames and distilled the key frame through chaotic sequence which generated by Logistic. Meanwhile, we distilled the low frequency coefficients of luminance component and self-adaptively embedded the processed image watermark into the low frequency coefficients of the wavelet transformed luminance component with the wavelet neural network. The experimental result suggested that the presented algorithm has better invisibility and robustness against noise, Gaussian filter, rotation, frame loss and other attacks.
Abstract: A modified two dimensional (2D) logistic map based on cross feedback control is proposed. This 2D map exhibits more random chaotic dynamical properties than the classic one dimensional (1D) logistic map in the statistical characteristics analysis. So it is utilized as the pseudo-random (PN) sequence generator, where the obtained real-valued PN sequence is quantized at first, then applied to radio frequency identification (RFID) communication system in this paper. This system is experimentally validated on a cortex-M0 development board, which shows the effectiveness in key generation, the size of key space and security. At last, further cryptanalysis is studied through the test suite in the National Institute of Standards and Technology (NIST).
Abstract: Generating random numbers are mainly used to create
secret keys or random sequences. It can be carried out by various
techniques. In this paper we present a very simple and efficient
pseudo random number generator (PRNG) based on chaotic maps
and S-Box tables. This technique adopted two main operations one to
generate chaotic values using two logistic maps and the second to
transform them into binary words using random S-Box tables.
The simulation analysis indicates that our PRNG possessing
excellent statistical and cryptographic properties.
Abstract: In this study, a system of encryption based on chaotic
sequences is described. The system is used for encrypting digital
image data for the purpose of secure image transmission. An image
secure communication scheme based on Logistic map chaotic
sequences with a nonlinear function is proposed in this paper.
Encryption and decryption keys are obtained by one-dimensional
Logistic map that generates secret key for the input of the nonlinear
function. Receiver can recover the information using the received
signal and identical key sequences through the inverse system
technique. The results of computer simulations indicate that the
transmitted source image can be correctly and reliably recovered by
using proposed scheme even under the noisy channel. The
performance of the system will be discussed through evaluating the
quality of recovered image with and without channel noise.