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Internet of Everything (IoE) and Internet of Nano Technology (IoNT) are the most prominently distributed knowledge over reviews on current trends. Nanoparticles communicating in the perceiving and propagating end cause AI and NLP usage in a better manner. IoNT is used as the medical smart watch calorimeter and pulse rate instrumentation. A sensor of IoE category is used in the mobile devices to accurately provide the alert on calorimeter results and pulse sensed. Voice-based results are gained with the help of AI and NLP. The fuzzy expert system is used to decide on the perceptions received by IoNT devices. Human intelligence is incorporated to further query on installation of food diet control mobile applications in the registry of the programmable devices. There is a strong interest to use social networking to enhance the communications among different IoT things. A new paradigm, named Social Internet of Things (SIoT), was recently proposed. Health-problem-specific solutions are extracted from the social networking blogs for solutions in the recent era. Solutions referred and improvement are recorded for recommendations as a social network post with the concerned proprietary owner permission and rights.

As big data hits the maximum number of companies in all domains, secured data transfer can be done by cryptography. With increasing threats to big data, the security must focus on to avoid the attackers from the formation of any pattern to gain access to the information. Big data deals with the linguistic data which consists of low secured data and high secured data as well. Hence, the system should focus on providing multi-fold security and should avoid high-security common to all data categories. This paper presents a hybrid model for big data that ensures data confidentiality, data integrity, access control and sequential freshness by combining three symmetric key algorithms AES, DES and blowfish for the encryption and decryption process in any desired order. Based on the level of security the combination of the algorithms can vary. This method of encryption and decryption process ensures safe data transformation between source and destination.

Many Internet-based applications authenticate the users before they are allowed to access the services provided by them. The traditional text-based password system is vulnerable to brute force attack, peeping attack, and reverse engineering attacks. The pitfalls of text-based passwords are addressed by employing graphical passwords. To create a password the graphical password systems make use of custom images, icons, or faces. Using images will decrease the tendency to choose insecure passwords. In this paper, we present a shoulder-surfing resistant pair based graphical password scheme to authenticate a user. Further enhancement of the proposed scheme is briefly discussed. Security analysis of the method is also evaluated.

Nowadays web pages are mostly XML based and most of this information does not have well-defined Document Type Definition (DTD) or Schema. They are relatively huge document and incomplete in nature. Therefore effective answering of the XML document is tedious as it leads to irrelevant and more generic results thereby failed to offer the specific user's needs. To avoid this problem, an approach based on Tree-based Association Rule (TAR) mining was proposed, using which for efficient answering the frequent paths and references of its occurrence will be extracted and it is stored in XML format for both ordered and unordered XML document. The constructed XML file is used for query answering; thereby it provides quick and approximate answers to user's query. The user's query is automatically transferred into a query format that retrieves information from the constructed XML file.