自Benninghoven。A 提出静态二次离子质谱(Static Secondary Ion Mass Spectrometry或SSIMS)方法以来,它就成为一种极灵敏的表面分析技术。近年来,SSIMS技术在多相催化研究中的应用日益广泛。我们曾成功地用SSIMS表征过MoO_3-NiO-P_2O_5...自Benninghoven。A 提出静态二次离子质谱(Static Secondary Ion Mass Spectrometry或SSIMS)方法以来,它就成为一种极灵敏的表面分析技术。近年来,SSIMS技术在多相催化研究中的应用日益广泛。我们曾成功地用SSIMS表征过MoO_3-NiO-P_2O_5/γ-Al_2O_3催化剂的表面结构层次.本工作中,我们应用SSIMS,并结合XPS对新型催化剂MoO_-CoO/TiO_2-Al_2O_3的表面结构层次和表面状态作了研究.展开更多
Ensuring the secure transmission of secret messages,particularly through video—one of the most widely used media formats—is a critical challenge in the field of information security.Relying on a single-layered secur...Ensuring the secure transmission of secret messages,particularly through video—one of the most widely used media formats—is a critical challenge in the field of information security.Relying on a single-layered security approach is often insufficient for safeguarding sensitive data.This study proposes a triple-lightweight cryptographic and steganographic model that integrates the Hill Cipher Technique(HCT),Rotation Left Digits(RLD),and Discrete Wavelet Transform(DWT)to embed secret messages within video frames securely.The approach begins with encrypting the secret text using a private key matrix(PK^(1))of size 2×2 up to 6×6 via HCT.A second encryption layer is applied using a dynamic private key(PK2)derived from the RGB pixel values of the video frame,resulting in a rotated cipher.The doubly encrypted message is then embedded into the video frames using the DWT method.Upon transmission,the concealed message is extracted using inverse DWT and decrypted in two steps—first with PK2 and then with the inverse of PK^(1).Experiments conducted using MPEG video sequences and message lengths ranging from 10 to 300 bytes demonstrate strong performance in terms of Mean Square Error(MSE),Peak Signal-to-Noise Ratio(PSNR),and Correlation Coefficient(CC)between original and encrypted messages.The similarity between original and stego frames is further validated using Structural Similarity Index(SSIM),Mean Absolute Error(MAE),Number of Pixel Change Rate(NPCR),and Unified Average Changing Intensity(UACI).Results confirm that utilizing video frames to generate PK2 offers superior security compared to static key images.Moreover,the indistinguishability between original and stego frames highlights the method’s robustness against visual and statistical attacks.展开更多
In this paper, we study edge detection or segmentation, which is recognized as a rudiment innovation as it can evaluate sharpness and analyze object boundaries. That’s the reason it has been an influential figure in ...In this paper, we study edge detection or segmentation, which is recognized as a rudiment innovation as it can evaluate sharpness and analyze object boundaries. That’s the reason it has been an influential figure in the image-processing era. Because of this, it has a significant influence in the age of image processing. On the other hand, edge detection is the process of dividing an image into discontinuous regions. It specifies the intensity shift connected to the image’s edge. There are several methods for detecting edges. Four edge identification methods on satellite images and satellite images affected by Gaussian noise were examined. Known edge detection technologies such as Canny, Prewitt, Scharr, and Robert operators are included in this study. Additionally, the key feature of an image for evaluating its quality is the Image Quality Assessment (IQA) measure. We primarily take into account SSIM, MSE, PSNR, and RMSE when assessing image quality. Experimental validation has been obtained for the application of the Canny and Prewitt algorithms to the satellite dataset. However, when the Gaussian Noise effect is added to the same dataset, clever edge detection performs better.展开更多
Biometric template protection is essential for finger-based authentication systems,as template tampering and adversarial attacks threaten the security.This paper proposes a DCT-based fragile watermarking scheme incorp...Biometric template protection is essential for finger-based authentication systems,as template tampering and adversarial attacks threaten the security.This paper proposes a DCT-based fragile watermarking scheme incorporating AI-based tamper detection to improve the integrity and robustness of finger authentication.The system was tested against NIST SD4 and Anguli fingerprint datasets,wherein 10,000 watermarked fingerprints were employed for training.The designed approach recorded a tamper detection rate of 98.3%,performing 3–6%better than current DCT,SVD,and DWT-based watermarking approaches.The false positive rate(≤1.2%)and false negative rate(≤1.5%)were much lower compared to previous research,which maintained high reliability for template change detection.The system showed real-time performance,averaging 12–18 ms processing time per template,and is thus suitable for real-world biometric authentication scenarios.Quality analysis of fingerprints indicated that NFIQ scores were enhanced from 2.07 to 1.81,reflecting improved minutiae clarity and ridge structure preservation.The approach also exhibited strong resistance to compression and noise distortions,with the improvements in PSNR being 2 dB(JPEG compression Q=80)and the SSIM values rising by 3%–5%under noise attacks.Comparative assessment demonstrated that training with NIST SD4 data greatly improved the ridge continuity and quality of fingerprints,resulting in better match scores(260–295)when tested against Bozorth3.Smaller batch sizes(batch=2)also resulted in improved ridge clarity,whereas larger batch sizes(batch=8)resulted in distortions.The DCNN-based tamper detection model supported real-time classification,which greatly minimized template exposure to adversarial attacks and synthetic fingerprint forgeries.Results demonstrate that fragile watermarking with AI indeed greatly enhances fingerprint security,providing privacy-preserving biometric authentication with high robustness,accuracy,and computational efficiency.展开更多
文摘自Benninghoven。A 提出静态二次离子质谱(Static Secondary Ion Mass Spectrometry或SSIMS)方法以来,它就成为一种极灵敏的表面分析技术。近年来,SSIMS技术在多相催化研究中的应用日益广泛。我们曾成功地用SSIMS表征过MoO_3-NiO-P_2O_5/γ-Al_2O_3催化剂的表面结构层次.本工作中,我们应用SSIMS,并结合XPS对新型催化剂MoO_-CoO/TiO_2-Al_2O_3的表面结构层次和表面状态作了研究.
文摘Ensuring the secure transmission of secret messages,particularly through video—one of the most widely used media formats—is a critical challenge in the field of information security.Relying on a single-layered security approach is often insufficient for safeguarding sensitive data.This study proposes a triple-lightweight cryptographic and steganographic model that integrates the Hill Cipher Technique(HCT),Rotation Left Digits(RLD),and Discrete Wavelet Transform(DWT)to embed secret messages within video frames securely.The approach begins with encrypting the secret text using a private key matrix(PK^(1))of size 2×2 up to 6×6 via HCT.A second encryption layer is applied using a dynamic private key(PK2)derived from the RGB pixel values of the video frame,resulting in a rotated cipher.The doubly encrypted message is then embedded into the video frames using the DWT method.Upon transmission,the concealed message is extracted using inverse DWT and decrypted in two steps—first with PK2 and then with the inverse of PK^(1).Experiments conducted using MPEG video sequences and message lengths ranging from 10 to 300 bytes demonstrate strong performance in terms of Mean Square Error(MSE),Peak Signal-to-Noise Ratio(PSNR),and Correlation Coefficient(CC)between original and encrypted messages.The similarity between original and stego frames is further validated using Structural Similarity Index(SSIM),Mean Absolute Error(MAE),Number of Pixel Change Rate(NPCR),and Unified Average Changing Intensity(UACI).Results confirm that utilizing video frames to generate PK2 offers superior security compared to static key images.Moreover,the indistinguishability between original and stego frames highlights the method’s robustness against visual and statistical attacks.
文摘In this paper, we study edge detection or segmentation, which is recognized as a rudiment innovation as it can evaluate sharpness and analyze object boundaries. That’s the reason it has been an influential figure in the image-processing era. Because of this, it has a significant influence in the age of image processing. On the other hand, edge detection is the process of dividing an image into discontinuous regions. It specifies the intensity shift connected to the image’s edge. There are several methods for detecting edges. Four edge identification methods on satellite images and satellite images affected by Gaussian noise were examined. Known edge detection technologies such as Canny, Prewitt, Scharr, and Robert operators are included in this study. Additionally, the key feature of an image for evaluating its quality is the Image Quality Assessment (IQA) measure. We primarily take into account SSIM, MSE, PSNR, and RMSE when assessing image quality. Experimental validation has been obtained for the application of the Canny and Prewitt algorithms to the satellite dataset. However, when the Gaussian Noise effect is added to the same dataset, clever edge detection performs better.
文摘Biometric template protection is essential for finger-based authentication systems,as template tampering and adversarial attacks threaten the security.This paper proposes a DCT-based fragile watermarking scheme incorporating AI-based tamper detection to improve the integrity and robustness of finger authentication.The system was tested against NIST SD4 and Anguli fingerprint datasets,wherein 10,000 watermarked fingerprints were employed for training.The designed approach recorded a tamper detection rate of 98.3%,performing 3–6%better than current DCT,SVD,and DWT-based watermarking approaches.The false positive rate(≤1.2%)and false negative rate(≤1.5%)were much lower compared to previous research,which maintained high reliability for template change detection.The system showed real-time performance,averaging 12–18 ms processing time per template,and is thus suitable for real-world biometric authentication scenarios.Quality analysis of fingerprints indicated that NFIQ scores were enhanced from 2.07 to 1.81,reflecting improved minutiae clarity and ridge structure preservation.The approach also exhibited strong resistance to compression and noise distortions,with the improvements in PSNR being 2 dB(JPEG compression Q=80)and the SSIM values rising by 3%–5%under noise attacks.Comparative assessment demonstrated that training with NIST SD4 data greatly improved the ridge continuity and quality of fingerprints,resulting in better match scores(260–295)when tested against Bozorth3.Smaller batch sizes(batch=2)also resulted in improved ridge clarity,whereas larger batch sizes(batch=8)resulted in distortions.The DCNN-based tamper detection model supported real-time classification,which greatly minimized template exposure to adversarial attacks and synthetic fingerprint forgeries.Results demonstrate that fragile watermarking with AI indeed greatly enhances fingerprint security,providing privacy-preserving biometric authentication with high robustness,accuracy,and computational efficiency.
