Security analysis of linearly filtered NLFSRs

Non-linear feedback shift register (NLFSR) ciphers are cryptographic tools of choice of the industry especially for mobile communication. Their attractive feature is a high efficiency when implemented in hardware or software. However, the main problem of NLFSR ciphers is that their security is still not well investigated. The paper makes a progress in the study of the security of NLFSR ciphers. In particular, we show a distinguishing attack on linearly filtered NLFSR (or LF-NLFSR) ciphers. We extend the attack to a linear combination of LF-NLFSRs. We investigate the security of a modified version of the Grain stream cipher and show its vulnerability to both key recovery and distinguishing attacks.

Intimate relationship status variations in violence against women : urban, suburban, and rural differences

Woman abuse varies across intimate relationship categories (e.g., marriage, divorce, separation). However, it is unclear whether relationship status variations in violence against women differ across urban, suburban, and rural areas. We test the hypothesis that rural females, regardless of their intimate partner relationship status, are at higher risk of intimate violence than their urban and suburban counterparts. Results indicate that marital status is an important aspect of the relationship between intimate victimization and geographic area and that rural divorced and separated females are victimized at rates exceeding their urban counterparts.

Signal Processing Diagnostic Tool for Rolling Element Bearings Using EMD and MED

The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

Diagnostic of Rolling Element Bearings with Envelope Analysis in Non-Stationary Conditions

In the field of rolling element bearing diagnostics, envelope analysis has gained in the last years a leading role among the different digital signal processing techniques. The original constraint of constant operating speed has been relaxed thanks to the combination of this technique with the computed order tracking, able to resample signals at constant angular increments. In this way, the field of application of this technique has been extended to cases in which small speed fluctuations occur, maintaining high effectiveness and efficiency. In order to make this algorithm suitable to all industrial applications, the constraint on speed has to be removed completely. In fact, in many applications, the coincidence of high bearing loads, and therefore high diagnostic capability, with acceleration-deceleration phases represents a further incentive in this direction. This chapter presents a procedure for the application of envelope analysis to speed transients. The effect of load variation on the proposed technique will be also qualitatively addressed.