With the recent development in digital currency, the number of online transactions done every day is increasing exponentially. Along with the growing need for online transactions various attacks are developed to mimic...
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This paper proposed a multi-level image steganography model that integrates with image and plaintext encryption schemes. The model starts by partitioning the cover-image pixel positions into two regions of respective ...
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This paper proposed a multi-level image steganography model that integrates with image and plaintext encryption schemes. The model starts by partitioning the cover-image pixel positions into two regions of respective purposes, one is reserved to hold the data, and through the implementation of the dynamic difference expansion principle, the other sloughs some parts to the reserved region in responsive to the size of the data to embed. Continuously reseeding and initializing the parameter values of a Linear Congruential Generator (LCG), generate a set of random pixel positions as members of the reserved region. Before data embedding, the region reserved to hold the data as well as the data bits to embed, are then encrypted using AES with respective keys. Encryption keys are randomly generated using a Cryptographically Secure Pseudo-Random Number Generator (CSPRNG), the Fortuna algorithm. Multiplex security nature of using a randomization generator to reserve image region for encryption and encrypting plaintext data before performing steganography still ensures stability in computational complexities better than a logarithmic O(n log n). A visual inspection by evaluators who made 3000 choices to correctly differentiate stego images from its cover-images shows that only 47 choices were correct, 1884 choices were wrong, while 1069 choices were uncertain. An experiment shows an average Embedding Rates (ERs) of 0.00109 bpp and an average PSNR of 72. This concludes, as our integrated steganography and image encryption which implements the dynamic difference expansion principle, outputs encrypted stego mages that can deceive the naked human eyes into identifying them as rather cover-images, its embedding rate is faster (i.e. ER < 0.1), suitably good, and ensures better imperceptibility of cover-image alterations. When comparing these experimental results with existing methods, our proposed model shows significant competitiveness. We even show real-life scenarios on how this
Body fitness monitoring applications are using mobile sensors to identify human activities. Human activity identification is a challenging task because of the wide availability of human activities. This paper proposes...
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Detecting fake news is currently one of the critical challenges facing modern societies. The problem is particularly relevant, as disinformation is readily used for political warfare but can also cause significant har...
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The neuron doctrine defines the neuron as the basic unit of the nervous system, which drives the dynamic behavior of our organs. This has led to neurons becoming the focus of modern neuroscience research and to the ri...
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Water Quality Sensors (WQSs) are becoming a promised tool in water quality data assessment and scientific value of aquatic structure. Such sensors are broadly used to produce live results by evaluating major water qua...
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The leading challenge for most businesses is customer churn;it is very hard for every business organization to maintain their customers. If customers are not satisfied with the service provided by an organization, the...
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The amount of written text on the internet has grown exponentially. When pairing that with the difficulties in sourcing the author of a text, a need emerges to be able to verify claimed author of text and attribute an...
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At present,the prevalence of diabetes is increasing because the human body cannot metabolize the glucose *** prediction of diabetes patients is an important research *** researchers have proposed techniques to predict...
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At present,the prevalence of diabetes is increasing because the human body cannot metabolize the glucose *** prediction of diabetes patients is an important research *** researchers have proposed techniques to predict this disease through data mining and machine learning *** prediction,feature selection is a key concept in ***,the features that are relevant to the disease are used for *** condition improves the prediction *** the right features in the whole feature set is a complicated process,and many researchers are concentrating on it to produce a predictive model with high *** this work,a wrapper-based feature selection method called recursive feature elimination is combined with ridge regression(L2)to form a hybrid L2 regulated feature selection algorithm for overcoming the overfitting problem of data *** is a major problem in feature selection,where the new data are unfit to the model because the training data are *** regression is mainly used to overcome the overfitting *** features are selected by using the proposed feature selection method,and random forest classifier is used to classify the data on the basis of the selected *** work uses the Pima Indians Diabetes data set,and the evaluated results are compared with the existing algorithms to prove the accuracy of the proposed *** accuracy of the proposed algorithm in predicting diabetes is 100%,and its area under the curve is 97%.The proposed algorithm outperforms existing algorithms.
Continuous-variable quantum key distribution(CVQKD)allows legitimate parties to extract and exchange secret ***,the tradeoff between the secret key rate and the accuracy of parameter estimation still around the presen...
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Continuous-variable quantum key distribution(CVQKD)allows legitimate parties to extract and exchange secret ***,the tradeoff between the secret key rate and the accuracy of parameter estimation still around the present CVQKD *** this paper,we suggest an approach for parameter estimation of the CVQKD system via artificial neural networks(ANN),which can be merged in post-processing with less additional *** ANN-based training scheme,enables key prediction without exposing any raw *** results show that the error between the predicted values and the true ones is in a reasonable *** CVQKD system can be improved in terms of the secret key rate and the parameter estimation,which involves less additional devices than the traditional CVQKD system.
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