Extracting embedded messages using adaptive steganography based on optimal syndrome-trellis decoding paths

Privacy protection is the key to maintaining the Internet of Things(IoT)communication strategy.Steganography is an important way to achieve covert communication that protects user data privacy.Steganalysis technology is the key to checking steganography security,and its ultimate goal is to extract embedded messages.Existing methods cannot extract under known cover images.To this end,this paper proposes a method of extracting embedded messages under known cover images.First,the syndrome-trellis encoding process is analyzed.Second,a decoding path in the syndrome trellis is obtained by using the stego sequence and a certain parity-check matrix,while the embedding process is simulated using the cover sequence and parity-check matrix.Since the decoding path obtained by the stego sequence and the correct parity-check matrix is optimal and has the least distortion,comparing the path consistency can quickly filter the coding parameters to determine the correct matrices,and embedded messages can be extracted correctly.The proposed method does not need to embed all possible messages for the second time,improving coding parameter recognition significantly.The experimental results show that the proposed method can identify syndrome-trellis coding parameters in stego images embedded by adaptive steganography quickly to realize embedded message extraction.

Online Pattern Recognition and Data Correction of PMU Data Under GPS Spoofing Attack

Smart grids are increasingly dependent on data with the rapid development of communication and measurement.As one of the important data sources of smart grids,phasor measurement unit(PMU)is facing the high risk from attacks.Compared with cyber attacks,global position system(GPS)spoofing attacks(GSAs)are easier to implement because they can be exploited by portable devices,without the need to access the physical system.Therefore,this paper proposes a novel method for pattern recognition of GSA and an additional function of the proposed method is the data correction to the phase angle difference(PAD)deviation.Specifically,this paper analyzes the effect of GSA on PMU measurement and gives two common patterns of GSA,i.e.,the step attack and the ramp attack.Then,the method of estimating the PAD deviation across a transmission line introduced by GSA is proposed,which does not require the line parameters.After obtaining the estimated PAD deviations,the pattern of GSA can be recognized by hypothesis tests and correlation coefficients according to the statistical characteristics of the estimated PAD deviations.Finally,with the case studies,the effectiveness of the proposed method is demonstrated,and the success rate of the pattern recognition and the online performance of the proposed method are analyzed.