This letter proposes a novel malicious user prediction model based on quantum machine learning that estimates the vicious entity present in the communication system precedently before allocating the data in the distributed environments. The proposed model scrutinizes the behavior of each user and estimates probable data breaches using a developed malicious user predictor unit. The model computes essential scores associated with each user request for the learning process of the prediction unit by generating training samples. The predictor unit exploits the computational and behavioral properties of Qubits and Quantum gates for the accurate prediction of the malicious user with high precision to grant access to non-malicious data requests only. The experimental evaluation and comparison of the proposed model with state-of-the-art methods reveal that it significantly improves the security of the system up to 33.28%.

This article comprehensively studies data security in cloud computing environments and presents ideas for solving everyday computing issues. Cloud Computing (CC) is a shared pool of resources that allocates those computing resources to cloud clients over the internet. CC provides a set of controls that act as controls between cloud users and storage. Storage has played a crucial role in the cloud and has become ubiquitous among organizations and clients. Nevertheless, various issues such as security, information protection, interoperability, and consistent quality should be defined appropriately. However, the underlying problem is data security and how cloud providers ensure it. Safe and secure protection technology is indispensable for exchanging information between clouds. Encryption technology is used to provide data security in cloud environments. Numerous cryptography algorithms exist to transform plain text to cipher text before placing the data in the cloud to ensure security.

This paper is about preserving the Cloud data whose idea is to cure everyday problems with computing. Cloud computing is fundamentally pooling the resources virtually and the resources like storage are provided to the end-users through the web. Information preservation, security, uniform quality, and interoperability are some issues related to cloud computing. However, the most essential issue is Security and how it is ensured by a cloud supplier. Security of data can be offered by means of cryptography. This paper presents an improved composite data protection mechanism to protect data on the cloud from illegitimate access.

A novel scheme is proposed to process the real-time images according to requirements, captured in a computer web camera. By making use of open source computer vision library (OpenCV) and applying its in-built functions, we can easily detect human faces and then match them against the training sets (face images stored in the database) to recognize a human’s identity. Image handling and processing are done using basic library methods. These library functions are able to capture images from a webcam, create windows to hold the images at run time, save them in the database and process them to check exact likeness. CascadeClassifier is used for face detection, and HaarCascade is used for this purpose. FaceRecognizer class is used for face recognition. EigenFaces, FisherFaces and Local Binary Patterns are the basic methods that can be used for this. Images are stored in form of a CSV database.

he main problem that we face today is not about getting services, but how efficiently we manage them. We are living in an era where we cannot neglect the fact that we are now depending on various electronic devices which we use daily in our life. These devices have become an inseparable part of our life, in the present scenario technology is evolving so rapidly that it’s a fact if we do not accept any upcoming trend then we lag behind in the eye of others. Managing all these devices and remembering to tune them is quite a hectic task, as we have to do other main tasks too. Using every device efficiently at the same time is not possible. Hence, we came up with a solution, with a system that will manage all these devices according to predefined rules or instructions. Current smart home systems work in a way, to establish a connection between nodes and a hub and are controlled by smartphones, computers, remote, etc. In this research paper, we have proposed a model that will not only establish a connection but will work smartly according to instructions and algorithms saved earlier. This Auxiliary Informatics System (AuxIS) will serve the requirement of managing all the devices in a parallel fashion with very little human intervention and hence, will make a smarter home environment.