Enhancing Privacy in Big Data through an Asymmetric Secure Storage Protocol with Data Sharing

Cloud computing has become integral to handling large-scale data in the era of big data. Storing such vast amounts of data locally is cost-prohibitive, necessitating the use of cloud storage services. However, reliance on a single cloud storage provider (CSP) raises concerns such as service interruptions and security vulnerabilities, including insider threats. To address these issues, this research proposes a novel approach where big data files are distributed across multiple CSPs using an asymmetric security framework. Metadata encryption and decentralized file access management are facilitated through a dew computing intermediary, enhancing security and ensuring privacy. Unlike previous approaches, this protocol employs group key encryption and secret sharing schemes within SSGK for efficient data protection and access control. Extensive security and performance evaluations demonstrate significant reductions in security risks and privacy breaches while optimizing storage efficiency

Novel Proposed Work for Empirical Word Searching in Cloud Environment

People's lives have become much more convenient as a result of the development of cloud storage. The third-party server has received a lot of data from many people and businesses for storage. Therefore, it is necessary to ensure that the user's data is protected from prying eyes. In the cloud environment, searchable encryption technology is used to protect user information when retrieving data. The versatility of the scheme is, however, constrained by the fact that the majority of them only offer single-keyword searches and do not permit file changes.A novel empirical multi-keyword search in the cloud environment technique is offered as a solution to these issues. Additionally, it prevents the involvement of a third party in the transaction between data holder and user and guarantees integrity. Our system achieves authenticity at the data storage stage by numbering the files, verifying that the user receives a complete ciphertext. Our technique outperforms previous analogous schemes in terms of security and performance and is resistant to inside keyword guessing attacks.The server cannot detect if the same set of keywords is being looked for by several queries because our system generates randomized search queries. Both the number of keywords in a search query and the number of keywords in an encrypted document can be hidden. Our searchable encryption method is effective and protected from the adaptive chosen keywords threat at the same time

Adaptation and application of the IEEE 2413-2019 standard security mechanisms to IoMT systems

Healthcare information systems are evolving from traditional centralised architectures towards highly-mobile distributed environments within the connected health context. The IoMT paradigm is at the forefront of this technological revolution underlying the development of communication infrastructures connecting smart medical devices, healthcare information systems and services. The IEEE 2413 standard, a promising general architectural framework for the design and implementation of IoT systems, has recently been announced. This standard proposes a general description for different types of domains, including healthcare, but it does not contain an extension developed for the IoMT systems domain. This paper presents a first approach to adapt the IEEE 2413 standard to the design of IoMT systems from a security perspective, considering the most relevant aspects of the standard for the construction of this type of systems. The application to an IoMT system for monitoring patients with chronic obstructive pulmonary disease is presented as a use case.Fundación Mutua MadrileñaSociedad Española de Diabete

Intelligent recognition of colorectal cancer combining application of computer-assisted diagnosis with deep learning approaches

The malignancy of the colorectal testing methods has been exposed triumph to decrease the occurrence and death rate; this cancer is the relatively sluggish rising and has an extremely peculiar to develop the premalignant lesions. Now, many patients are not going to colorectal cancer screening, and people who do, are able to diagnose existing tests and screening methods. The most important concept of this motivation for this research idea is to evaluate the recognized data from the immediately available colorectal cancer screening methods. The data provided to laboratory technologists is important in the formulation of appropriate recommendations that will reduce colorectal cancer. With all standard colon cancer tests can be recognized agitatedly, the treatment of colorectal cancer is more efficient. The intelligent computer assisted diagnosis (CAD) is the most powerful technique for recognition of colorectal cancer in recent advances. It is a lot to reduce the level of interference nature has contributed considerably to the advancement of the quality of cancer treatment. To enhance diagnostic accuracy intelligent CAD has a research always active, ongoing with the deep learning and machine learning approaches with the associated convolutional neural network (CNN) scheme

Security and Privacy Enhancing Multi-Cloud Architectures

Security challenges are still among the biggest obstacles when considering the adoption of cloud services. This triggered a lot of research activities, resulting in a quantity of proposals targeting the various cloud security threats. Alongside with these security issues, the cloud paradigm comes with a new set of unique features, which open the path toward novel security approaches, techniques, and architectures. This paper provides a survey on the achievable security merits by making use of multiple distinct clouds simultaneously. Various distinct architectures are introduced and discussed according to their security and privacy capabilities and prospects

Internet of Things Based Smart Vending Machine using Digital Payment System

The advent of the Internet envisions a cashless society by enabling financial transactions through digital payments. Significantly, the emergence of coronavirus (COVID-19) disrupted our traditional cash handling means and triggered an inflection point for switching towards contactless digital payments from physical cash payments. Furthermore, Internet of Things (IoT) technology escalates digital payments to the next level by enabling devices to render goods and services without requiring any human interaction. This research proposed an IoT-enabled cashless vending machine that incorporates both cloud computing and payment gateway for ordering and purchasing items through digital payment systems by using a mobile application. The system enables a pre-installed mobile application to scan the Quick Response (QR) code attached to the body of a vending machine, opens the portal of a web-based virtual machine through the code, allows user to choose and order items from the virtual vending, initiates and authorizes a digital payment through an IoT gateway installed inside the physical vending machine by establishing a connection between user's and vendor's financial entities, and finally, dispenses the ordered items by unlocking the shelves of the vending machine after the successful payment transaction. It operates in the Arduino platform with an ATmega 2560 Microcontroller and Esp8266 Wi-fi module as hardware components, mobile application software, and payment gateway API. The system performed an average response time of 14500 milliseconds to pick a product after running 150 consecutive API test calls. This result shows a satisfying time for enhancing customers' buying experiences with digital payment systems and a customizable and cost-effective IoT-based intelligent vending machine to introduce for mass production

BIoMT-ISeg: Blockchain internet of medical things for intelligent segmentation

In the quest of training complicated medical data for Internet of Medical Things (IoMT) scenarios, this study develops an end-to-end intelligent framework that incorporates ensemble learning, genetic algorithms, blockchain technology, and various U-Net based architectures. Genetic algorithms are used to optimize the hyper-parameters of the used architectures. The training process was also protected with the help of blockchain technology. Finally, an ensemble learning system based on voting mechanism was developed to combine local outputs of various segmentation models into a global output. Our method shows that strong performance in a condensed number of epochs may be achieved with a high learning rate and a small batch size. As a result, we are able to perform better than standard solutions for well-known medical databases. In fact, the proposed solution reaches 95% of intersection over the union, compared to the baseline solutions where they are below 80%. Moreover, with the proposed blockchain strategy, the detected attacks reached 76%.publishedVersio

Still Wrong Use of Pairings in Cryptography

Several pairing-based cryptographic protocols are recently proposed with a wide variety of new novel applications including the ones in emerging technologies like cloud computing, internet of things (IoT), e-health systems and wearable technologies. There have been however a wide range of incorrect use of these primitives. The paper of Galbraith, Paterson, and Smart (2006) pointed out most of the issues related to the incorrect use of pairing-based cryptography. However, we noticed that some recently proposed applications still do not use these primitives correctly. This leads to unrealizable, insecure or too inefficient designs of pairing-based protocols. We observed that one reason is not being aware of the recent advancements on solving the discrete logarithm problems in some groups. The main purpose of this article is to give an understandable, informative, and the most up-to-date criteria for the correct use of pairing-based cryptography. We thereby deliberately avoid most of the technical details and rather give special emphasis on the importance of the correct use of bilinear maps by realizing secure cryptographic protocols. We list a collection of some recent papers having wrong security assumptions or realizability/efficiency issues. Finally, we give a compact and an up-to-date recipe of the correct use of pairings.Comment: 25 page