Cloud Data Storage Research Articles

M♡THer, an mHealth System to Support Women with Gestational Diabetes Mellitus: Feasibility and Acceptability Study.

Background: Gestational diabetes mellitus (GDM) is defined as glucose intolerance first identified during pregnancy. Delays in diagnosis and challenges in management can lead to serious adverse outcomes for the mother and child. As rates of GDM diagnosis increase worldwide, health systems and maternity services have become increasingly strained, especially with new restrictions around in-person care due to the current COVID-19 pandemic. Mobile health (mHealth) has increasingly shown promise for management of chronic disease, driven by smartphone adoption and increased internet connectivity. The aim of this work was to evaluate the adoption and multidisciplinary care coordination of an mHealth platform called M♡THer in a cohort of women with first-time diagnosis of GDM.Methods: The mHealth platform for GDM management was developed incorporating a smartphone application, clinician portal, and secure cloud data storage. Forty participants with a first-time diagnosis of GDM were recruited to use the app during their pregnancy. User attitudes from clinicians and women were captured through post-hoc surveys, and app-usage metrics.Results: Clinicians and women indicated satisfaction and ease of use of the mHealth platform, with some technological challenges around wireless connectivity. Blood glucose reviews and antenatal contact were higher with use of the M♡THer app compared with a matched historical sample.Conclusion: The M♡THer mHealth platform is a new comprehensive tool for health care of women with GDM, and may provide an effective new avenue to enhance multidisciplinary care in the face of COVID-19 disruptions and challenges to traditional care pathways.

Enhanced Effective and Privacy Preserving Multi Keyword Search over Encrypted Data in Cloud Storage Using Blowfish Algorithm

The data owner administers their data to the public cloud due to regulatory. Even this data encoded once it easily transmitted to the cloud. In order to ensure the privacy and security, cloud subscribers need a very different type of online data. This specific information must be germane to the recipient's query. The user to inspect the query too in the cloud with umpteen keywords can accomplish this. With the intention to defend the privacy of data, confidential data encoded before subcontracting by the metadata owner, attempting to make the traditional and efficient plaintext keyword search tactic pointless. Therefore, it is crucial to explore a secure data search service for encrypted user data. Due to the growing of massive number of digital users and legal documents in the cloud, umpteen keywords forced in the search request and documents returned in the order of their relevance to these keywords.Cloud assistance end-user demands cloud information by various paternoster inquiry, whichlabelled as umpteenkeywordstratified exploration over scrambled information. In the cloud server, all the client inquiries exchanged. Server looks through the significant matter by utilizing the harmonic equivalency and sends the applicable outcomes to the client. Information got from cloud server is in the scrambled configuration. To get to control to the client,Information proprietor furnishes with key for unscrambling of information. Message Authentication Code(MAC) calculation is utilized to check and confirm trustworthiness of information. Thusly this paper depicts the method of giving security to redistribute information on cloud and checking the trustworthiness of information using blowfish algorithm. Comparison results shows the improvement in efficiency of Data Retrieval and Time efficiency.

Biometric Based User Authentication and Privacy Preserving In Cloud Environment

Cloud technology provides advantage of storage services for individuals and organizations thus making file access easy and simple irrespective of location. The major concern is the security while the file is been outsourced. Maintaining integrity, file unchanged, gaining confidentiality during file outsourced plays an important role. In this paper, we propose identity based data outsourcing technique to provide data security during authorization and storage. For data authorization we propose finger print based authentication. The fingerprint based authentication is performed using Minutae Map algorithm (MM). For data security we convert the data owner files to hash values using SHA algorithm. Finally in the cloud storage stage, data security and data availability is addressed using multiple cloud storage system.

A Novel Technique for IDS in Distributed Data Environment Using Merkel Based Security Mechanism for Secure User Allocation

Multiple corporations and people frequently launching their data in the cloud environment. With the huge growth of data mining and the cloud storage paradigm without checking protection policies and procedures that can pose a great risk to their sector. The data backup in the cloud storage would not only be problematic for the cloud user but also the Cloud Service Provider (CSP). The unencrypted handling of confidential data is likely to make access simpler for unauthorized individuals and also by the CSP. Normal encryption algorithms need more primitive computing, space and costs for storage. It is also of utmost importance to secure cloud data with limited measurement and storage capacity. Till now, different methods and frameworks to maintain a degree of protection that meets the requirements of modern life have been created. Within those systems, Intrusion Detection Systems (IDS) appear to find suspicious actions or events which are vulnerable to a system's proper activity. Today, because of the intermittent rise in network traffic, the IDS face problems for detecting attacks in broad streams of links. In existing the Two-Stage Ensemble Classifier for IDS (TSE-IDS) had been implemented. For detecting trends on big data, the irrelevant data characteristics appear to decrease both the velocity of attack detection and accuracy. The computing resource available for training and testing of the IDS models is also increased. We have put forward a novel strategy in this research paper to the above issues to improve the balance of the server load effectively with protected user allocation to a server, and thereby minimize resource complexity on the cloud data storage device, by integrating the Authentication based User-Allocation with Merkle based Hashing-Tree (AUA-MHT) technique. Through this, the authentication attack and flood attack are detected and restrict unauthorized users. By this proposed model the cloud server verifies, by resolving such attacks, that only approved users are accessing the cloud info. The proposed framework AUA-MHT performs better than the existing model TSE-IDS for parameters such as User Allocation Rate, Intrusion Detection Rate and Space Complexity

Integrating a High-Reliability Multicriteria Trust Evaluation Model with Task Role-Based Access Control for Cloud Services

Cloud data storage is revolutionary because it eliminates the need for additional hardware, which is often costly, inconvenient, and requires additional space. Cloud data storage allows data owners to store large amounts of data in a flexible way and at low cost. The number of online cloud storage services and their consumers has therefore increased dramatically. However, ensuring the privacy and security of data on a digital platform is often a challenge. A cryptographic task-role-based access control (T-RBAC) approach can be used to protect data privacy. This approach ensures the accessibility of data for authorized consumers and keeps it safe from unauthorized consumers. However, this type of cryptographic approach does not address the issue of trust. In this paper, we propose a comprehensive trust model integrated with a cryptographic T-RBAC to enhance the privacy and security of data stored in cloud storage systems, and suggests that trust models involve inheritance and hierarchy in the roles and tasks of trustworthiness evaluation, where this study aims to identify the most feasible solution for the trust issue in T-RBAC approaches. Risk evaluations regarding other possible flaws of the design are also performed. The proposed design can decrease risk by providing high security for cloud storage systems and improve the quality of decisions of cloud operators and data owners.

Deniable search of encrypted cloud-storage data

Cloud storage services have grown extensively in recent years. For privacy and security purposes, outsourced data must be encrypted. Therefore, searching the encrypted cloud-stored data is a big challenge. Although there are plenty of searchable encryption schemes, most rely on keywords located in the encrypted data instead of more complex searching criteria. Moreover, they do not consider the malicious coercer issue. In this paper, we propose a searchable encryption scheme that supports expressive keyword-matching conditions and provides deniable searchability to the user.

Message Passing Over Cloud Using Cascade Ciphering With Randomized Algorithm

To solve the problem of poor security and performance caused by traditional encryption algorithm in the cloud data storage, we propose a cascade ciphering with randomized algorithm. The multiple encryption is a process to encrypt the data multiple times using the same algorithm or different algorithms, to provide multilayer and multilevel security over unreliable wireless network during communication. The encryption algorithms are AES, MD5, SHA 129, SHA 256, Whirlpool and Blowfish.

Blockchain-Based Fine-Grained Data Sharing for Multiple Groups in Internet of Things

Cloud-based Internet of Things, which is considered as a promising paradigm these days, can provide various applications for our society. However, as massive sensitive and private data in IoT devices are collected and outsourced to cloud for data storage, processing, or sharing for cost saving, the data security has become a bottleneck for its further development. Moreover, in many large-scale IoT systems, multiple group data sharing is practical for users. Thus, how to ensure data security in multiple group data sharing remains an open problem, especially the fine-grained access control and data integrity verification with public auditing. Therefore, in this paper, we propose a blockchain-based fine-grained data sharing scheme for multiple groups in cloud-based IoT systems. In particular, we design a novel multiauthority large universe CP-ABE scheme to guarantee the fine-grained access control and data integrity across multiple groups by integrating group signature into our scheme. Moreover, to ease the need for a trusted third auditor in traditional data public auditing schemes, we introduce blockchain technique to enable a distributed data public auditing. In addition, with the group signature, our scheme also realizes anonymity and traitor tracing. The security analysis and performance evaluation show that our scheme is practical for large-scale IoT systems.

Privacy Preservation-Based Access Control Intelligence for Cloud Data Storage in Smart Healthcare Infrastructure

Cloud service providers emphasize the concept of virtual machines, wherein resources and services are accessed over a distributed network system. The loss of user privacy is indeed contempt in concern to any individual or organization, particularly concerning the Healthcare infrastructure. This research paper introduces a Euclidean L3P-based Multi-Objective Successive Approximation (EMSA) algorithm, an efficient measure of privacy in the Healthcare Cloud. The role-based encryption keys are the critical foundation for the storage of sensitive data in cloud environments is presented here. The proposed EMSA algorithm is the hybridization of the existing Euclidean L3P Distance algorithm, Multi-objective Optimization algorithm, and Successive Approximation Iterative Proximate algorithm. In addition, the performance of the proposed EMSA compared with Bat, PUBAT, TPNGS, WOA, and CIC-WOA algorithms based on performance metrics, such as fitness, privacy, and utility. The simulation shows that, comparison to the existing state-of-the-art algorithms, the proposed EMSA model achieves higher privacy values of 0.34, 0.42, 0.42, 0.35, and 0.30.

Study and improved data storage in cloud computing using cryptography

Cloud computing is becoming a powerful network architecture to perform computing that is both large and complex. We present a cloud computing survey which outlines its core concepts, architectural principles, state-of- the art deployment and research challenges. Due to security issues, information over the Internet is becoming important. We have suggested a method to protect critical file data. Cryptography algorithms are an efficient way to encrypt sensitive data. It is a retrieval and transmission system that is readable only by intended users. The low cost and data usability of cloud computing is advantageous. Cloud storage has many advantages at low cost and data connectivity through the Internet. Ensured cloud data protection is an important part of the cloud computing environment because customers often store sensitive information with cloud storage services but they are not secure services. So, it remains a challenge to exchange data in a safe way while storing data from an unconfident cloud. Our solution guarantees consumer confidential data protection and privacy by using the AES, RC2 algorithm to store data in a single cloud. The cloud computing concept and transitional discussion under cloud computing will be provided previously proposed. The cryptographic algorithm used in cloud is then addressed and the latest trend for cloud security

WITHDRAWN: Bloom hash probabilistic data structure and Benaloh Cryptosystem for secured data storage and access control in cloud

Cloud service providers are responsible for these services to satisfy user requirements. The cloud users need SLAs to indicate their requirements related to the quality of service and security. A novel technique called Bloom Hashing Data Storage based Benaloh Cryptographic Data Accessing (BHDS-BCDA) is introduced for providing better service-level agreement with minimal space complexity and higher authentication accuracy. BHDS-BCDA technique contains three processes: registration and key generation, secure data storage, and access control to provide an efficient service level agreement between cloud user and server. In the registration, the cloud user details are registered to the cloud server. After the registration, the cloud server generates the public key and private key for every registered cloud user using Benaloh Cryptographic function. Whenever the cloud user needs to store the cloud server's data, they verify the user as an authorized or unauthorized user. The cloud server uses the Bloom hash probabilistic data structure to store the data in a cloud server with minimum space complexity for the authorized users. When a cloud user requests the data, the cloud service provider encrypts it and transmits it to the requested cloud user. From that point onward, the cloud user decrypts the data and obtains the original data. This, in turn, helps to improve the service level agreement during the data storage and access control. Experimental evaluation is carried out on space complexity, authentication accuracy, data confidentiality, and computation time with the number of cloud user requests. The outcomes confirmed that the presented BHDS-BCDA technique is better in higher authentication accuracy, data confidentiality rate with minimum space complexity, and computation time. Based on the observations, the BHDS-BCDA technique is more efficient than the other methods for handling secure data storage and access in the cloud.

Big Data Cloud Storage Optimization Scheme based on PSO Algorithm

PSO algorithm, as one of the best swarm intelligence algorithms, has a strong optimization ability. It has obvious advantages to apply PSO algorithm to the optimization of resource scheduling strategy of cloud computing platform. Through the research on the application of PSO algorithm in cloud computing, effective methods are provided for the improvement of efficiency of cloud computing platform. This paper analyzes and studies the application of PSO algorithm optimized by cloud model in business scheduling of big data cloud storage platform.

IoT Based Sensor for Humidity and Temperature Measurement in Smart HVAC Systems

The initials HVAC stand for Heating, Ventilation and Air Conditioning. They describe the functions of an HVAC system. This mechanical system’s design is primarily an attempt to take control of the environmental conditions inside the space of work by controlling and monitoring the temperature of a room through heating and cooling. It also controls the humidity level in that environment by controlling the movement and distribution of air inside the room. For determining the temperature and humidity, costly sensors are required. These sensors are the traditional mechanical sensors which can’t offer any additional services like cloud support, data storage, etc. Hence here I am proposing an IoT based sensor with cloud data storage using Arduino-Uno development board, ESP8266 and Thingspeak cloud. This sensor is economical and supports automatic reading and controlling of the humidity and temperature and sends this data to a secured server and thus monitors and controls the temperature and humidity of the system.

Encryption System for Hiding Information Based on Internet of Things

<p class="0abstract">One of the unexpected intelligence tactics known in World War II was to conceal the data in images that were reduced to the size of a point that was used in every text and transported in front of the enemy's eyes. In the new age, and after the expansion of Internet science and the use of the Internet worldwide, we will establish a security feature of the IOT service that will work more reliably and more effectively to deal with the Internet of Things and ensure the work of the services that the customer interacts with. A secret-key stenographic scheme that embeds four gray-scale secret size (128*128) pixel images into a size (512*512) pixel cover image in this work. Wavelet transform is the method used in this project to analyze the cover into its frequency components. In this work, combinations of steganography and cryptography were made to increase the level of safety and make the device more difficult for attackers to beat. The resulting stego-image that will be transmitted did not raise any suspicion by both objective and subjective evaluation, so the primary objective of Steganography is achieved. The proposed system was designed by using (MATLAB R2018b) and running on a Pentium-4 computer. The Internet of Things works with the encryption system for data in a synchronized manner with the technological development, and in order to maintain the stability of any Internet of things service, whether it is information signal services, visual or audio data, a remote control system, or data storage in the Internet cloud, we must focus on data preservation from internet pirates and internet system hackers. The picture Figure<strong> </strong>4 below shows the method of encryption and dealing with the Internet of things system..</p>

Data tag replacement algorithm for data integrity verification in cloud storage

Data integrity verification is an important technical method to detect the integrity of remote cloud storage data. At present, the existing data integrity verification algorithms generate data tags for outsourced data blocks before verification, and then use these data tags to verify the data integrity proofs provided by the data storage provider and determine whether the corresponding data blocks are intact. Unfortunately, most of these algorithms do not check the reliability of data tags. Once the data tags are compromised due to the exposure of the private key of data owner, the corrupted data can easily bypass subsequent verification, thereby invalidating the verification. To solve this issue, we propose a secure and reliable data tag replacement algorithm DTRA. The proposed algorithm uses proactive and reactive replacement to update the data owner’s private key. In addition, the algorithm applies homomorphic encryption to implement data tag replacement directly in the remote storage environment, avoids data owner downloading outsourced data from remote storage space, and reduces the data transmission overhead caused by data tag replacement. Theoretical analysis and experimental results indicate that the algorithm can achieve data tag replacement safely and reliably at a low cost.

Smart Surveillance System for Controlling Pandemic Diseases in Airports

As a pandemic outbreak that threatens the world, this project focus to minimize the community spread of COVID-19 especially during travel. The fever is turns out as a first symptom and later it turns out to a severe respiratory disorder that would even leads to death. Fever can show the variation in the body temperature after 4 hours of being tested. Hence, the chance of fever symptoms accelerated during the long travel time. So close observation and continuous monitoring of person is requires during travel. Therefore, a system is suggested that to monitor the temperature of passenger periodically and it uses thermal imaging technique. For abnormal variations in the temperature an alert is send to pilot system and also Emergency Operations Centre (EOC), National Transportation Safety Board (NTSB), Federal Emergency Management Agency (FEMA) by the smart IOT device. Smart Node MCU cloud system sends the alert message to the various aviation units. The thinkspeak is act as cloud storage & access of data for this applications. Social distancing is one criterion to avoid the spread of the virus but waiting area is the place where passengers wait for long time to be board to plane. People met other and cluster together with luggage’s in boarding zones. A proposed system reduces the risk of spreading to all the area by monitoring of passengers. Systems that calibrate the size of the waiting room and the person entering inside and leaving out is measure. With the factor of social distancing, the warning signal is trigger if a particular place is crowded with passenger.

Electromyography-Driven Exergaming in Wheelchairs on a Mobile Platform: Bench and Pilot Testing of the WOW-Mobile Fitness System.

BackgroundImplementing exercises in the form of video games, otherwise known as exergaming, has gained recent attention as a way to combat health issues resulting from sedentary lifestyles. However, these exergaming apps have not been developed for exercises that can be performed in wheelchairs, and they tend to rely on whole-body movements.ObjectiveThis study aims to develop a mobile phone app that implements electromyography (EMG)-driven exergaming, to test the feasibility of using this app to enable people in wheelchairs to perform exergames independently and flexibly in their own home, and to assess the perceived usefulness and usability of this mobile health system.MethodsWe developed an Android mobile phone app (Workout on Wheels, WOW-Mobile) that senses upper limb muscle activity (EMG) from wireless body-worn sensors to drive 3 different video games that implement upper limb exercises designed for people in wheelchairs. Cloud server recordings of EMG enabled long-term monitoring and feedback as well as multiplayer gaming. Bench testing of data transmission and power consumption were tested. Pilot testing was conducted on 4 individuals with spinal cord injury. Each had a WOW-Mobile system at home for 8 weeks. We measured the minutes for which the app was used and the exergames were played, and we integrated EMG as a measure of energy expended. We also conducted a perceived usefulness and usability questionnaire.ResultsBench test results revealed that the app meets performance specifications to enable real-time gaming, cloud storage of data, and live cloud server transmission for multiplayer gaming. The EMG sampling rate of 64 samples per second, in combination with zero-loss data communication with the cloud server within a 10-m range, provided seamless control over the app exergames and allowed for offline data analysis. Each participant successfully used the WOW-Mobile system at home for 8 weeks, using the app for an average of 146 (range 89-267) minutes per week with the system, actively exergaming for an average of 53% of that time (39%-59%). Energy expenditure, as measured by integrated EMG, was found to be directly proportional to the time spent on the app (Pearson correlation coefficient, r=0.57-0.86, depending on the game). Of the 4 participants, 2 did not exercise regularly before the study; these 2 participants increased from reportedly exercising close to 0 minutes per week to exergaming 58 and 158 minutes on average using the WOW-Mobile fitness system. The perceived usefulness of WOW-Mobile in motivating participants to exercise averaged 4.5 on a 5-point Likert scale and averaged 5 for the 3 participants with thoracic level injuries. The mean overall ease of use score was 4.25 out of 5.ConclusionsMobile app exergames driven by EMG have promising potential for encouraging and facilitating fitness for individuals in wheelchairs who have maintained arm and hand mobility.

Internet of Nonthermal Food Processing Technologies (IoNTP): Food Industry 4.0 and Sustainability

With the introduction of Industry 4.0, and smart factories accordingly, there are new opportunities to implement elements of industry 4.0 in nonthermal processing. Moreover, with application of Internet of things (IoT), smart control of the process, big data optimization, as well as sustainable production and monitoring, there is a new era of Internet of nonthermal food processing technologies (IoNTP). Nonthermal technologies include high power ultrasound, pulsed electric fields, high voltage electrical discharge, high pressure processing, UV-LED, pulsed light, e-beam, and advanced thermal food processing techniques include microwave processing, ohmic heating and high-pressure homogenization. The aim of this review was to bring in front necessity to evaluate possibilities of implementing smart sensors, artificial intelligence (AI), big data, additive technologies with nonthermal technologies, with the possibility to create smart factories together with strong emphasis on sustainability. This paper brings an overview on digitalization, IoT, additive technologies (3D printing), cloud data storage and smart sensors including two SWOT analysis associated with IoNTPs and sustainability. It is of high importance to perform life cycle assessment (LCA), to quantify (En)—environmental dimension; (So)—social dimension and (Ec)—economic dimension. SWOT analysis showed: potential for energy saving during food processing; optimized overall environmental performance; lower manufacturing cost; development of eco-friendly products; higher level of health and safety during food processing and better work condition for workers. Nonthermal and advanced thermal technologies can be applied also as sustainable techniques working in line with the sustainable development goals (SDGs) and Agenda 2030 issued by United Nations (UN).

Third Party Risk Management

Every organization relies upon third party vendors for a multitude of business operations. Despite the requirements to rely upon third party vendors, only 52% of organizations have security standards for third party vendors (Matis, 2019, para. 2). Furthermore, a study surveying 608 information technology (IT) professionals indicated that 69% of the respondents either definitely suffered a security breach or possibly suffered a security breach due to vendor access within the year (Bomgar, 2019, p. 2). Finally, a staggering 94.3% of executives possess low to moderate confidence in their third-party risk management tools and technology (Deloitte, 2018, para. 3). These statistics are the direct result of complex business relationships, dynamic information technology exchanges, and a lack of awareness outside of those directly working within the information technology realm. Additionally, the lack of information technology personnel who aspire to upper echelons of business management contribute to the overall risk factors. In June of 2018, Universal Music Group became aware of a massive data breach that exposed file transfer protocol credentials, Amazon Web Services cryptographic keys, and internal passwords due to improper handling of a third-party cloud storage provider. The technical aspects of the breach reveal that a contractor working at the cloud storage provider administered an apache airflow server without password requirements (Cimpanu, 2018, para. 3). The damage has yet to be quantified and it is unclear how many customers this data breach has affected (Cyber GRX, 2019, para. 7). What the data breach represents is something far greater than another data breach amongst many but rather how devastating the effects a single lackadaisical contractor can have for an organization. The Target data breach is a similar example with many more secondary and tertiary effects caused by a single heating, venting, and air conditioning contractor. Risk is generally dealt with through the use of transferring, accepting, avoiding and mitigating (Cannon, 2014, p. 48). Risk transference is the most popular method of handling risk and results in the use of many third-party vendors for organizations (ISACA, 2016, p. 113). When opting to use third party vendors, an organization is choosing to transfer risk due to the inability or lack of feasibility for conducting the action on their own. Across the cyber domain, many organizations opt to place their data in cloud storage as this is scalable and affordable. However, cloud solutions are just as vulnerable to exploitation as an on-premises datacenter (Muncaster, 2019, para. 3). Perhaps the issue rests in the lack of education on vendor risk management. Cyber insurance is another method of transferring risk as the cost of the average data breach continues to grow each year. This paper will aim to underscore the importance of vendor risk management and options organizations have to address such risks.

The Identical Data in Cloud Storage with ADJDUP Technique

Data deduplication is necessary for corporations to minimize the hidden charges linked with backing up their data using Public Cloud platform. Incapable data storage on its own can become improvident, and such problem are enlarging in the Public Cloud at other and scattered satisfied confirmed storage structure are creating multiple clone of single account for collating or other purposes. Deduplication is friendly in cost shrinking by lengthening the benefit of a precise volume of data. Miserably, data duplicity having several safety constraints, so more than one encoding is appropriate to validate the details. There is a system for dynamic Information-Locking and Encoding with Convergent Encoding. In this Information-Locking and Encoding with Convergent Encoding, the data is coded first and then the cipher text is encoded once more. Chunk volume is used for deduplication to diminish disk capacity. The same segments would still be encrypted in the same cipher message. The format of the key neither be abbreviated from encrypted chunk data by the hacker. The comprehension is also guarded from the cloud server. The center of attention of this document is to reducing disk storage and provides protection for online cloud deduplication.