This paper proposes a system to analyze the sentiments of tweeters. It is to build an accurate model to detect different emotions in a tweet. The analysis takes place through several stages (i.e., pre-processing, feature extraction, and training more than one machine learning (ML)). Naïve Bayes, Multinomial Naïve Bayes and Bernoulli Naïve Bayes were selected as supervised machine learning for sentiment analysis using a dataset of 3,057 tweets with users ranging from fear to happiness, anger, and sadness because this method is suitable for solving a problem of this type. This system was also applied to another dataset of 10,000 Tweets (5,000 positive and 5,000 negatives). This approach, consisting of three Naïve Bayes classification models, was applied to two datasets to analyze the sentiment used in them and classify each category separately. The Multinomial Naïve Bayes model outperformed the other models Where it achieved an accuracy of (91.6%) when applied to the first dataset and accuracy (87.6%) when applied to the second dataset. The researchers aim to continue this research with larger data by using other methods of sentiment analysis to predict users' thoughts about COVID-19 or any other problem and to obtain higher accuracy for the models used.

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The study of cryptography applications in chaotic system have been exponentially increasing in the recent years. Depending on the sensitivity to initial conditions, chaotic systems are characterized, similarity to continuous broad-band power spectrum and random behavior. The chaotic system is high sensitive to the initial condition and is a high complex nonlinear dynamic system. The chaotic sequence is unpredictable and extreme sensitivity to initial conditions. There are many applications to the chaotic system in several methods, image compression, encryption, modulation and digital communication system. In this paper, an algorithm based on Discrete Cosine Transform (DCT) has been introduced by using Henon map to get the scheme of chaos image encryption. The level of security is very high and this algorithm can improve small key space.A new chaotic algorithm is presented to get rid of the problem of the weakness of security in one dimensional chaotic cryptosystems and small key space based on a new chaotic algorithm, which uses two dimension linear functions instead of one dimension.

The concept Web of Things (WoT) goes well beyond the emphasis on the Internet as a means of sharing data, instead of introducing all resources and connections involving computers, data, and people to the Web. It, therefore, focuses on a range of problems and opportunities, thus paving the way for several exciting industries applications.  In cryptography a range of main characteristics of chaotic systems such as non-linearity, initial condition sensitivity, and mixing properties are available. These characteristics provide an essential connection between cryptography and chaos. GOST block cipher is based on secret key secrecy. However, when the encryption process with the same key is used for plaintext, the same cipher text is created. Message replication can be easily detected by an adversary who is a bad link in every communication. In this paper, propose to use a 5d chaotic system combined with GOST block cipher to create a new secure Web of Things (WoT) cryptography system. The 5D chaotic system was used to generate chaotic random keys used in GOST algorithm to provide proper security with as high hardness randomly enhances the NIST fifteen statistical tests and modifies key schedule as security operations.

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