In this paper we review some statistical tests included in the NIST SP 800-22 suite, which is a collection of tests for the evaluation of both true-random (physical) and pseudorandom (algorithmic) number generators for cryptographic applications. The output of these tests is the so-called p-value which is a random variable whose distribution converges to the uniform distribution in the interval [0,1] when testing an increasing number of samples from an ideal generator. Here, we compute the exact non-asymptotic distribution of p-values produced by few of the tests in the suite, and propose some computation-friendly approximations. This allows us to explain why intensive testing produces false-positives with a probability much higher than the expected one when considering asymptotic distribution instead of the true one. We also propose a new approximation for the Spectral Test reference distribution, which is more coherent with experimental results.

Spread spectrum is a technique introduced for mitigating electromagnetic interference (EMI) problems in many class of circuits. In this paper, with particular emphasis on switching DC/DC converters, we consider the most common and most efficient known spreading techniques, looking for spreading parameters that ensure the highest EMI reduction and the lowest performance reduction in the circuit where the spreading is applied. The result is an interesting tradeoff not only between EMI reduction and performance drop, but also on the EMI reduction itself when considering different EMI victim models. The proposed analysis is supported by measurements on two switching DC/DC converters: 1) based on pulse-width modulation and 2) based on the resonant converter class.

We present the design and the validation by means of suitably improved randomness tests of two different implementations of high-performance true-random number generators which use a discrete-time chaotic circuit as their entropy source. The proposed system has been developed from a standard pipeline Analog-to-Digital converter (ADC) design, modified to operate as a set of piecewise-linear chaotic maps. The evolution of each map is observed and quantized to obtain a random bit stream. With this approach it is possible to obtain, on current CMOS technology, a data rate in the order of tens of megabit per second. Furthermore, we can also prove that the design is tamper resistant in the sense that a power analysis cannot leak information regarding the generated bits. This makes the proposed circuit perfectly suitable for embedding in cryptographic systems like smarts cards, even more so if one consider that it could be easily obtained by reconfiguring an existing pipeline ADC. The two prototypes have been designed in a 0.35-μm and 0.18-μm CMOS technology, and have a throughput of, respectively, 40 Mbit/s and 100 Mbit/s. A comparison between measured results and other high-end commercial solutions shows a comparable quality with a operating speed that is one order of magnitude faster.

The idea that compressed sensing may be used to encrypt information from unauthorized receivers has already been envisioned but never explored in depth since its security may seem compromised by the linearity of its encoding process. In this paper, we apply this simple encoding to define a general private-key encryption scheme in which a transmitter distributes the same encoded measurements to receivers of different classes, which are provided partially corrupted encoding matrices and are thus allowed to decode the acquired signal at provably different levels of recovery quality. The security properties of this scheme are thoroughly analyzed: first, the properties of our multiclass encryption are theoretically investigated by deriving performance bounds on the recovery quality attained by lower-class receivers with respect to high-class ones. Then, we perform a statistical analysis of the measurements to show that, although not perfectly secure, compressed sensing grants some level of security that comes at almost-zero cost and thus may benefit resource-limited applications. In addition to this, we report some exemplary applications of multiclass encryption by compressed sensing of speech signals, electrocardiographic tracks and images, in which quality degradation is quantified as the impossibility of some feature extraction algorithms to obtain sensitive information from suitably degraded signal recoveries.

The need for fast and strong image cryptosystems motivates researchers to develop new techniques to apply traditional cryptographic primitives in order to exploit the intrinsic features of digital images. One of the most popular and mature technique is the use of complex dynamic phenomena, including chaotic orbits and quantum walks, to generate the required key stream. In this paper, under the assumption of plaintext attacks we investigate the security of a classic diffusion mechanism (and of its variants) used as the core cryptographic primitive in some image cryptosystems based on the aforementioned complex dynamic phenomena. We have theoretically found that regardless of the key schedule process, the data complexity for recovering each element of the equivalent secret key from these diffusion mechanisms is only O(1). The proposed analysis is validated by means of numerical examples. Some additional cryptographic applications of this paper are also discussed.

We report the design and implementation of an Analog-to-Information Converter (AIC) based on Compressed Sensing (CS). The system is realized in a CMOS 180 nm technology and targets the acquisition of bio-signals with Nyquist frequency up to 100 kHz. To maximize performance and reduce hardware complexity, we co-design hardware together with acquisition and reconstruction algorithms. The resulting AIC outperforms previously proposed solutions mainly thanks to two key features. First, we adopt a novel method to deal with saturations in the computation of CS measurements. This allows no loss in performance even when 60% of measurements saturate. Second, the system is able to adapt itself to the energy distribution of the input by exploiting the so-called rakeness to maximize the amount of information contained in the measurements.