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The recent advancement in cloud computing and Internet of Things (IoT) paradigms, paves a way to support the patients through remote monitoring and they can enjoy their health services at home. The medical professional (MP) needs to analyze IoT health data or Electronic Health Records (EHR) from a cloud server using their authorized login credentials. However, the Cloud-IoT network is vulnerable to many malicious attacks, it is necessary to make strong user authentication. Therefore, strong user authentication is a prerequisite for a successful global deployment of centralized healthcare systems. In this paper, we present a secure, efficient authentication protocol to allow MPs to access patient data through a Cloud IoT network. The proposed protocol contains Light Weight Self-Adaptive Honey Encryption (LWSHE) for securing the Internet of Things (IoT) medical data in a cloud server. The traditional Honey encryption algorithm has a message space limitation problem which is overcome through a discrete distribution function in Distribution Transforming Encoder (DTE) which maps the plain text strings into the seed strings. In the honey encryption algorithm, our proposed honeyword generation method can eliminate storage overhead and typo safety problems. Based on the result of the security and performance comparison analysis, the proposed protocol does not only prevents the vulnerable attacks from being performed but also achieves more complex security operations and efficient user authentication. [ABSTRACT FROM AUTHOR]

Cloud computing is clutching and tantalizing the world and taking the distributed computing archetype into different dimensions with different names in recent decades. In today's scenario, 99 percent of the organizations and even the common people are migrating to adopt storage services on cloud for their business and personal usages because of its attractive and beneficial features with less maintenance. The most popular service providers like Google, amazon, Yahoo, and Microsoft are increasing their users to millions in every moment because of their attractive and promoting mechanisms. But, at the same time, their services are hosted from different data centers that contain thousands of servers, as well as power delivery (and backup) and networking infrastructures. In this scenario, when users demand high availability and low response times, each service is mirrored by multiple data centers that are geographically distributed. This may leads the high cost for maintenance and some challenges to provide integrity and consistency. So, the predecessor of this research work investigated the issues in Providers' and user' perspective to provide cost-effective optimized cloud storage while meeting the reliability and availability requirement throughout the whole Cloud storage process. And also, the research has proposed the RAAES framework to optimize and to provide efficient cloud Storage in order to significantly reduce the occupied space and cost jointly with meeting the reliability assurance requirements. Thus, through this paper this research has been proven that it could ultimately reduce the request-response time delay while enhancing the availability requirements by implementing the RAAES, hence it has a positive effect on promoting the development of Cloud by an efficient Storage. [ABSTRACT FROM AUTHOR]

A smart and intelligent cloud system virtually provides computing resources to enhance the user computing requirement. Computing resources are provided to the user based on their demand. A hybrid cloud is most effective for using and maintaining user data in the cloud deployment. However, no matter what kind of cloud technology the user adopts, it is open to security vulnerability. It's tedious to keep security in the hybrid cloud environment. Maintaining the user's data with a proper security mechanism, this paper proposes a new approach to maintaining data security in the hybrid cloud. The proposed approach uses cryptography techniques to secure the user's data in a hybrid cloud. The solid purpose of proposing this approach is to protect users' data in a public and private cloud using different encryption techniques. The proposed data security model provides users and suppliers with many benefits concerning the security of the data. Three encryption techniques are proposed and provided as Symmetric Encryption as a service from the cloud. Three techniques are measured for their efficiency by implementing the proposal as a cloud-based application hosted in the cloud. The proposed techniques are measured for performance and security strength. The results show that the proposed encryption techniques are more efficient for a hybrid cloud environment to secure data. [ABSTRACT FROM AUTHOR]

Cloud computing paved an excellent platform for the emergence of cost effective technological solutions. However, security and privacy issues still remain as a stringent challenge during service catering. Explicitly, the service utility anomalies are liable to cause severe privacy and security issues in cloud service delivery. So, the overall performance of Cloud service consumption and end-user applications' service levels utility is degraded. The open access and distributed nature of the cloud computing is the major reason for its vulnerability to intruders. The security and privacy in cloud services have many challenges and problems still open for research. This paper proposes an intrusion detection method capable of detecting nine categories of attacks in two stages. This paper focuses on establishing a network based intrusion detection mechanism using machine learning techniques. A model will be constructed with a supervised learning methodology using historical network flowdata and flowdata collected from Internet. [ABSTRACT FROM AUTHOR]

In recent years, the data storage system plays important role in the technology called big data management and cloud storage systems. Duplication of the data in the cloud system is a key problem, which decreases the data storage efficiency in the system. To avoid this problem, the data deduplication technology helps to improve the efficiency of the data storage systems. The data deduplication shrinks the need for storage by removing and avoiding uploads of duplicate data in the particular cloud environment. The integrity and confidentiality of the data are essential factors of the data deduplication technologies. As well as, the security measure of the data storage systems needs to be considered while building the data deduplication technologies. Because most common data encryption algorithms cannot be applied while performing the data deduplication process. This paper describes the process behind the data deduplication and analyzes various data deduplication techniques in terms of security threats. [ABSTRACT FROM AUTHOR]

Now a day new technology is growing at a fantastic rate irrespective of the domain like Information Technology, Medical, Infrastructures, Telecommunication named a few. Organizations are striving to keep up to date pace of technology to trap the business from the market to get maximum profits and to deliver in the quickest time to their customers with agreed quality. To take managerial decision regarding adoption of new technology or not, with certainty; few basic rules devised in this paper after doing an extensive exploratory research[1]. With extensive use of new technology, company operate in efficient and profitable mode. It has been observed champions are assigned identify and evaluate new technologies that are beneficial to the company. Based on your business model, you may be negotiate with vendors who promise that adoption of new technology will save you cost, quality and productive. Based on the risk appetite of the group, the impact of new technology will have on your business processes and people, it forward in bringing path-breaking technology in house. After adopting a new technology successfully, people feel proud to be working on the cutting-edge technology makes them much confident to take their next assignment. It takes organization to be ahead of the peers in term of technology innovations to get more business from the clients. Companies like IBM, Accenture, Microsoft, and Google have already spending lot of revenue on research work on adopting new technology in the market like social media, cloud computing, mobile tablets, and analytics named a few in IT domains. Similarly, Medical Industries have already started research in new technologies like nano structures to enhance their diagnostics imaging capability and other biological advances to detect and treating many diseases. [ABSTRACT FROM AUTHOR]

Evolving cloud has compelled people and organizations of every size - whether large or small to migrate data to public or private server for the reasons: scalability, agility, reliability, accessibility, cost saving. But along with the benefits, the risk to the safety of user data has also increased as it is always at a risk of data breach. Therefore, the Security and privacy of this data has become the most important foundation for a reliable server depository and a major challenge and key issue. We often ignore the safety of our data and completely rely on server service provider which is deficient. This paper proposes a crypto stegno technique using Blowfish and LSB (Least Significant Bit) algorithm for data encryption to secure sensitive data over the server from unauthorized access. Hence, preserving the privacy and securing the cloud stored sensitive data. The results are represented in the form of execution time, PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error) and the histogram of main and covered image. The experimental results reveal that all the algorithms achieve appropriate quality of stego image. They can be used as cryptographic algorithms to encrypt a message before applying steganography algorithms. [ABSTRACT FROM AUTHOR]

Cloud computing is a high demanding technology since the users and their data are increasing extremely day-by-day. Through an extensive utilization of cloud computing and storage devices, sensitive data is increasingly centralized into the cloud for reducing the maintenance cost which increases concerns about data privacy. One of the promising techniques to maintain the confidentiality of outsourced sensitive data is encryption schemes, however effective data utilization and also an efficient searching on encrypted data in cloud security are still challenging processes. Over the decades, many encryption techniques, namely Public-Key Encryption (PKE) and Identity-Based Encryption (IBE) with keyword searching and Equality Testing (ET) have been adopted to tackle those challenges over the encrypted data, but Private Matching (PM) over encrypted data is still difficult. In this paper, different researches based on PKEET and IBEET schemes in cloud computing are briefly studied which are utilized for data authorization and privacy-preserving. In addition, a comparative analysis is conducted to address the limitations in those schemes and suggest a further solution to tackle the identified issues. This survey helps us to overcome the PM over encrypted data in IBEET schemes and simplify the certificate management. [ABSTRACT FROM AUTHOR]

In the present business scenario, Cloud Computing has taken a centerstageduetoitscosteffectiveness, efficiency, andscalability. There has been broad use of cloud-based systems and its services by most of the organizations in current times. And in order to safeguard the different transactions of information over the cloudenvironment, itisverymuchessential toprovideasecureplatform for the users. Therefore cloud security plays a significant role in ensuring confidentiality, integrity, andavailabilityofinformation. This paper mainly focused on the use of Machine learning(ML)algorithms as atool tosecuredatastoredin thecloud. It is worthmentioning that Machine learning has been widely used in analyzing data anomalies, predicting threats, classify data's, etc. in cloud-based system. The main objective of thispaperistoproposeasecurecloudframeworkwithtwodistinguishedparti.e.classification and encryption. Here we mainly focused on the classification of data usingone of the Machine Learning Algorithm i.e. Hybrid Naïve Bayes Algorithm where dataareclassified into threelevels viz. basic, sensitive, and highly sensitive. The proposedML algorithm is experimented using cloudsim simulating tool, results are analyzed andcompared with existing other ML classification algorithms namely K-Nearest Neighbor(KNN)andSupportVectorMachine(SVM). [ABSTRACT FROM AUTHOR]

In the 21st century, the biggest issue is produced in terms of storage, processing, and sharing of computing resources with the enhancement of techniques. This issue is resolved with the amalgamation of big data and Cloud Computing techniques. Big data techniques help in handling new datasets efficiently Whereas Cloud Computing techniques provide an online storage model where the concept of virtualization is used. The combination of cloud computing and big data has set a new standard for future educational institutions and corporations. Users are capable to work according to their convenience by using Cloud Computing environments, while big data environments provide useful insights and information to them. This paper introduces big data along with various machine learning methods and Cloud Computing concepts. It also discusses the relationship between big data and cloud computing platforms, as well as the issues they pose. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) is a worldwide rapid growing technology. It provides a seamless connectivity via smart devices all over the world. Lot of communication mechanisms are playing important role in Machine Type Communication (MTC) to achieve the modern IoT vision. Cellular network is a key factor for long range communication in IoT. 5G cellular network overcome the limitations of previous cellular technologies and provide a large research scope in future IoT. Cloud computing also plays an significant role in IoT. An extensive good communication can be established at a low cost using the cloud service of IoT. This paper presets the research challenges collaborating the 5G cellular network and cloud computing in IoT. [ABSTRACT FROM AUTHOR]

Cloud computing is a client-driven requirement that provides many resources with the goal of sharing them as a service over the internet. It is a stage in which Cloud clients can access a unique pool of resources and virtualization. Cloud computing provides dynamic resource allocation on demand, as well as scalability, availability, and various services. The cloud provides services to organizations such as processing, storage, server, and applications that are located in remote areas by utilising cloud servers. The system's performance suffers if tasks are not properly scheduled As a result, resource allocation is critical to improving overall system performance. The scheduling of user tasks is critical for improving the performance of cloud services. Cloud providers must effectively schedule their resources for maximum utilisation and user satisfaction. In this paper has given a optimize the scheduling algorithm based on Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Firefly Algorithm, Lion Optimization Algorithm (LOA) to improve the performance of cloud task scheduling. The simulation results show the effectiveness of the comparison by using research parameters like Cost, Resource Utilization, Make span, Execution Time and Completion Time. [ABSTRACT FROM AUTHOR]

In recent times one of the emerging and intelligent tool is Cloud Computing. It has developed a leading model of computing and IT service delivery. Cloud Computing is characterized by three-layered basic service forms such as, Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS) and Infrastructure-as-a Service (IaaS). Pushing information into the cloud extends larger closeness since users are not necessary to be concerned about the storage capacity, storing techniques, hardware management, or data maintenance. A key problem that requires specific consideration is security of clouds. Existing approaches for secured outsourcing of information and random calculations are either support on a single tamperproof hardware, or based on homomorphic encryption. To overcome existing issues a novel approach is proposed to focus on security experiments in cloud computing and to provide solutions. To provide unfailing security to the users, the purpose of this paper is in three folding. 1) To design a mathematical model for trust and reputation calculation. 2) To propose TRSS algorithm for calculation of security score. 3) To compare the security score of trust and reputation factors by Fuzzy Logic System, Neural Network. This work is focused on controlling the security issues in cloud environment by means of trust and reputation factors using mathematical model, Trust and Reputation Security Score (TRSS) algorithm, Fuzzy Logic System, Neural Network in Internet of Things applications. [ABSTRACT FROM AUTHOR]

Farmers used to evaluate the soil's maturity and manipulate suspicions in order to generate which type of yield. They can't be responsible for humidity, water level, or any other variables. Especially concerning are the horrible weather conditions that are wreaking havoc on farms. Agriculture is being transformed by the Internet of Things (IOT). Agriculturists overcome problems in the field by delivering a varied range of services methods, such as precision farming and practical farming. With the help of IOT modernization, crop web-based examination permits the discovery of wild plants, water levels, bug locations, creature disturbance in the field, trim development, and horticulture. IoT allows farmers to connect to their homes from anywhere and at any time. Remote sensor structures are used to monitor the homestead's conditions, while smaller scale controllers are used to control and mechanize the home shapes. To watch the occurrences as photographs and films from a distance, remote cameras were used. [ABSTRACT FROM AUTHOR]

Software service depend on wireless sensor network is very famous in the systematic deployment world. Simultaneously many famous companies are trying to solve this network problem by their invention but later only service software (cloud computing app) plays a major role to solve the problem. Many problems are faced by service software. They are loss of sufficient safety, evaluation of problem, endangered of software, placing the correct sources, managing the information, honesty over the system etc. These problems all have effect of compromising in the nature of cloud devices. Institution depend on invention get worry to create a sufficient survey for assuage to have impact on the measure to manage and have correct balance between users and providers of service software. This topic made great interest to researchers to focus on the service software approval and execution with low endangered activities and threats in service software. This institution creates a latest methods or transferring information to services software. During this creation it changes the data security and methods to proceed. This procedure is used to alter the problems, issues and danger when it compelled in the services of software. While proceedings, the experts found 5 problems and issues that insist in the service of software. Here each and every problem and issues are operated and controlled using the service of software. [ABSTRACT FROM AUTHOR]

Cloud Computing is A Remarkable technology in the IT field Various services are provided by the cloud computing over the internet. According to the usage computing resource services IT charges in the cloud Yahoo, Amazon, Google are some of the cloud used organisations which are having number of users. Cloud Computing is an internet based computing approach. So there is a sharing of applications resources and software in between the computing devices. Mentioning of loads in cloud environment is most challenging issue. Balancing of float in the main intention in making of visual machine balance which not be overload or underload. An efficient and its dynamic load balancing weighted Round Robin algorithm for virtual machine in cloud computing is presented in this paper. Task or uses the modified algorithm of inspired Honey Bee behaviour and for balancing the workload on virtual machine uses the modified Round Robin Algorithm in the cloud system. By using this energy system performance is improved minimum completion time can be achieved and better resources are utilized. The efficiency of this load balancing method is better than the previous methods. [ABSTRACT FROM AUTHOR]

Sensor hubs in a Wireless Sensor Network include sound sensors, camera sensors, temperature sensors, proximity sensors, movement sensors, light sensors, shade sensors, and accelerometer sensors. Sensor hubs have several limitations, including restricted memory, power, and handling. W.S.N.'s capabilities have expanded significantly in recent years and include social insurance monitoring, disaster detection, military applications, savvy home inspection, and alert urban communities, among other things. Despite its various applications, adaptability, hub control, asset booking, board portability, and security are some of the research difficulties with W.S.N. Increasing the number of sent sensors to fulfil demand is difficult with the growing popularity of W.S.N. applications. In this approach, cloud and virtualization can help with the problem. Sensor Cloud is the result of combining cloud and W.S.N. One of the research issues that sensor clouds encounter is security. This study, reported in this publication, focuses on a few of the most severe security breaches in sensor clouds. [ABSTRACT FROM AUTHOR]

The recent years, Machine Learning (ML) and Educational Data Mining (EDM) methods received significant attention for several aspects. Data Mining Methods can be employed for extracting meaningful data for the educational datasets. CMT (Cloud Mapping Tables), a result based mostly on utilization of information storage repository techniques for cloud-based Big - data analysis, can provide not only improved information management but also endurance with multidimensional information processing capacities. It could be utilized for a prediction of the current educational system, Student Academic Performance (SAP) has been used to appropriate corrective measures.. Data Storage is one of the best techniques to handle Big data. The information is frequently not even in the correct format to assist a company's decision-making process. In this paper, the issue addressed was applying a feature selection-based classification model for SAP. Initially, an adjusted Particle Swarm Optimization (MPSO) algorithm was applied effectively to select the set of features. For information categorization, the Multi-Layer Perceptron using Stochastic Gradient Descent (MLP-SGD) framework has been used. The suggested students ' performance approaches were combined with the Radial Basis Function (RBF) approach to reduce the miscategorized cases in the collected data, resulting in improved classification results. To verify the efficiency of the suggested, sets of data on the academic performance of students was obtained from secondary schools in Tanjore, Tamil Nadu, India. The modeled results demonstrated that the proposed significantly outperform the previous techniques. [ABSTRACT FROM AUTHOR]

Background:With the rise of cloud computing. mobile devices may now store and access personal data at any time and from any location. As a result, the mobile cloud's data security issue only gets worse, impeding the technology's ability to advance. For the purpose of enhancing cloud security, extensive research has been done. The majority of them, nonetheless, are not appropriate for mobile clouds because of the constrained computational capabilities of mobile devices. Mobile cloud applications have a huge need for solutions with reduced computational overhead. For cloud computing on mobile devices, we suggest a lightweight data sharing scheme (LDSS). It adopts the CP-ABE access control technology, which is utilized in a typical cloud environment but modifies the access control tree's structure to make it appropriate for mobile cloud environments. Through the use of LDSS, a significant chunk of the computationally demanding CP-ABE access control tree transformation is transferred from mobile devices to external proxy servers in order to lower the cost of user revocation. To solve the tricky problem of lazy revocation in program based CP-ABE systems, it includes attribute description fields. Objective: An approach that re-examines the concept of public key cryptography is attribute-based encryption, which came about somewhat later. The secret key of a person and the cypher text are established based on attributes in attribute-based encryption, also known as ABE. A symmetric key can only decrypt a particular cipher-text using an ABE if the cipher-attributes text's match those of the person's key. Both keys and cipher-texts are labelled with units of descriptive attributes. Because fewer keys are required, the encryption and decryption processes are quicker as a result. Conclusion: Users can safely share data via the cloud between one other. In order to provide effective access control over cypher text, we build an algorithm called LDSS-CP-ABE based on the Attribute-Based Encryption (ABE) approach. For encryption and decryption processes, we use proxy servers. The computational cost on client-side mobile devices is significantly reduced by our technique, which conducts computationally complex processes in ABE on proxy servers. With the cost down, performance has gone up. [ABSTRACT FROM AUTHOR]

Cloud computing plays a significant role in effective data handling based on the increase in data usage in various realtime applications. Data auditing is performed on certain files and the authenticator with deduplication. It addresses the problem of key management to deduce the file content based on the malicious activities performed on the cloud. So, based on effective auditing of the integrity of the data and authenticator, the data is checked properly and minimizes the overhead of cloud storage overhead. In this work, the cloud audit and authenticator approach is proposed based on a certain file system, which makes the malicious user get authenticate the data auditing verification as the existing algorithm has low security based on entropy. They propose a data auditing approach that integrates with file management and the authenticator of data deduplication. The proposed approach performs the authenticator process and new form of file tag, which helps guarantee effective security based on the random generation of message key. The proposed approach achieves minimum computational overhead based on the authenticator and data block generation in the performance analysis. Then the security verification is performed on various attacks, such as brute force attack, a man-in-the-middle attack, etc., to check whether the approach is safe or unsafe against the attacks. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is a network of millions of computers and sensors that generate enormous amounts of data. It is sent to the cloud to be processed and computed; however, some computing paradigms are required near the edge devices due to latency, bandwidth, and storage constraints. Fog computing is a more advanced kind of cloud computing that extends some of its capabilities to end users. Within the Internet of Things, fog computing provides end-users with computational, storage, and network resources. One of the primary concerns of fog computing is authentication and safe data access between fog servers and fog nodes, as well as fog nodes and IoT users. Experiments were carried out to check communication between them, encrypting the data on transit, using symmetric and will a lightweight cryptographic algorithm. The experiments use PRESENT and AES algorithms to prove it. The system was breached to test the Ping of death and Smurf attack as DOS attack. The Sniffing for the password was done by Wireshark that also helped in the monitoring of the network. Thus, proving that encryption was a good solution for implementing security but the network was venerable to DOS and DDOS attack. In the objective to improving the security and privacy of edge device the research work opened avenue of using block chain a concept of implementing security by constructing two contract that were linked with each other. The concept helps to encrypt the data within the transaction while the sender and the receiver addresses are hashed which is the security benefits of the block chain. [ABSTRACT FROM AUTHOR]

Changes and advances in data advances have assumed a significant part in the improvement of wise vehicle frameworks lately. Driver weakness is a significant variable in vehicle mishaps. Therefore, auto collisions including driver exhaustion and driver indiscretion have been trailed by scientists. In this article, a Multi-entrusting Convulational Neural Network (ConNN) model is proposed to identify driver laziness/weariness. Eye and mouth attributes are used for driver's conduct model. Changes to these attributes are utilized to screen driver weariness. With the proposed Multi-task ConNN model, dissimilar to the examinations in the writing, both mouth and eye data are arranged into a solitary model simultaneously. Driver not entirely settled by computing eyes' conclusion length/Percentage of the eye conclusion (PERCLOS) and the yawning recurrence/recurrence of mouth (FOM). In this review, the weakness level of the driver is isolated into 3 classes. The proposed model accomplished 98.81% weakness location on YawdDD and NthuDDD dataset. The accomplishment of the model is introduced nearly. [ABSTRACT FROM AUTHOR]

Scheduling workflows on the cloud is recognised to be an NP-complete problem. But metaheuristic algorithms have been successfully tweaked to deal with this issue in a more efficient manner. Grey wolf optimization (GWO) is a fascinating new metaheuristic approach proposed recently for dealing with continuous optimization issues. Here, we propose the IGWO algorithm as a chaotic-theory-enhanced replacement for the GWO method. The proposed strategy has the potential to prevent the system from settling into a local optimum and speed up the rate at which the GWO converges. Using the CloudSim simulator, we simulate the proposed workflow scheduling system, and the results show that our solution is superior to the alternatives in terms of energy efficiency, cost, and maketime. [ABSTRACT FROM AUTHOR]

Cloud computing refers to both the hardware and system software in the datacenters that provide the applications delivered as services via the Web. The services themselves have long been referred to as Software as a Service (SaaS). The hardware and software that make up the datacenters are what we will refer to as a cloud. When a cloud is made available to the general public on a pay-as-you-go basis, we refer to it as an open cloud. The service being offered is utility computing. You can create and improve the policies that will be used by all of the CloudSim components with the help of the toolkit. As a result of its ability to mimic the complexity that manifests itself in many circumstances, it will be viewed as a helpful study aid. [ABSTRACT FROM AUTHOR]