A Secure Device Management Scheme with Audio-Based Location Distinction in IoT

Identifying a device and detecting a change in its position is critical for secure devices management in the Internet of Things(IoT).In this paper,a device management system is proposed to track the devices by using audio-based location distinction techniques.In the proposed scheme,traditional cryptographic techniques,such as symmetric encryption algorithm,RSA-based signcryption scheme,and audio-based secure transmission,are utilized to provide authentication,non-repudiation,and confidentiality in the information interaction of the management system.Moreover,an audio-based location distinction method is designed to detect the position change of the devices.Specifically,the audio frequency response(AFR)of several frequency points is utilized as a device signature.The device signature has the features as follows.(1)Hardware Signature:different pairs of speaker and microphone have different signatures;(2)Distance Signature:in the same direction,the signatures are different at different distances;and(3)Direction Signature:at the same distance,the signatures are different in different directions.Based on the features above,amovement detection algorithmfor device identification and location distinction is designed.Moreover,a secure communication protocol is also proposed by using traditional cryptographic techniques to provide integrity,authentication,and non-repudiation in the process of information interaction between devices,Access Points(APs),and Severs.Extensive experiments are conducted to evaluate the performance of the proposed method.The experimental results show that the proposedmethod has a good performance in accuracy and energy consumption.

Effects of dynamic recrystallization and strain-induced dynamic precipitation on the corrosion behavior of partially recrystallized Mg-9Al-lZn alloys

The corrosion susceptibility of recrystallized and un-recrystallized grains in equal channel angular pressed(ECAPed)Mg-9Al-lZn(AZ91)alloys immersed in chloride containing media was investigated through immersion testing and an electrochemical microcell technique coupledwith high resolution techniques such as scanning Kelvin probe force microscopy(SKPFM),transmission electron microscopy(TEM),andelectron backscatter diffraction(EBSD).During ECAP,dynamic recrystallization(DRX)and strain-induced dynamic precipitation(SIDP)simultaneously occurred,resulting in a bimodal grain structure of original elongated coarse grains and newly formed equiaxed fine grainswith a large volume fraction ofβ-Mg17Al12 precipitates.Corrosion preferentially initiates and propagates in the DRXed grains,owing tothe greater microchemistry difference between theβ-Mg17Al12 precipitates formed at the DRXed grain boundaries and the adjacentα-Mgmatrix,which induces a strong microgalvanic coupling between these phases.Additionally,the weaker basal texture of the DRXed grainsalso makes these grains more susceptible to electrochemical reactions than the highly textured un-DRXed grains.The influence of dynamicrecrystallization and dynamic precipitation was also studied in ECAPed alloys with differenl levels of deformation strain through corrosion andelectrochemical techniques.Increasing the strain level led to a more uniform corrosion with a shallow penetration depth,lower corrosion ratevalues,and higher protective ability of the oxide film.Furthermore,higher levels of strain resulted in greater hardness values of the ECAPedalloys.The superior corrosion resistance and strength of the ECAPed alloys with increasing strain level was attributed to the combination ofsmaller DRXed grain size,higher DRX ratio,and higher volume fraction of uniformly distributed fineβ-Mg17Al12 precipitates.c 2020 Published by Elsevier B.V.on behalf of Chongqing University.

Shallow water source localization using a mobile short horizontal array

This paper presents an approach to the challenging is- sue of passive source localization in shallow water using a mobile short horizontal linear array with length less than ten meters. The short array can be conveniently placed on autonomous underwa- ter vehicles and deployed for adaptive spatial sampling. However, the use of such small aperture passive sonar systems makes it difficult to acquire sufficient spatial gain for localizing long-range sources. To meet the requirement, a localization approach that employs matched-field based techniques that enable the short ho- rizontal linear array is used to passively localize acoustic sources in shallow water. Furthermore, the broadband processing and inter-position processing provide robustness against ocean en- vironmental mismatch and enhance the stability of the estimation process. The proposed approach＇s ability to localize acoustic sources in shallow water at different signal-to-noise ratios is examined through the synthetic test cases where the sources are located at the endfire and some other bearing of the mobile short horizontal linear array. The presented results demonstrate that the positional parameters of the estimated source build up over time as the array moves at a low speed along a straight line at a constant depth.

Enhancement Channel Estimation Using Outer-Product Decomposition Algorithm Based on Frequency Transformation

The outer-product decomposition algorithm(OPDA)performs well at blindly identifying system function.However,the direct use of the OPDA in systems using bandpass source will lead to errors.This study proposes an approach to enhance the channel estimation quality of a bandpass source that uses OPDA.This approach performs frequency domain transformation on the received signal and obtains the optimal transformation parameter by minimizing the p-norm of an error matrix.Moreover,the proposed approach extends the application of OPDA from a white source to a bandpass white source or chirp signal.Theoretical formulas and simulation results show that the proposed approach not only reduces the estimation error but also accelerates the algorithm in a bandpass system,thus being highly feasible in practical blind system identification applications.