Biblio

How to analyze users' data without compromising individual privacy is an important issue in cloud computing. In order to protect privacy and enable the cloud to perform computing, users can apply homomorphic encryption schemes to their data. Most of existing homomorphic encryption-based cloud computing methods require that users' data are encrypted with the same key. While in practice, different users may prefer to use different keys. In this paper, we propose a privacy-preserving cloud computing method which adopts a double-trapdoor homomorphic encryption scheme to deal with the multi-key issue. The proposed method uses two cloud servers to analyze users' encrypted data. And we propose to use blockchain to monitor the information exchanged between the servers. Security analysis shows that the introduction of blockchain can help to prevent the two servers from colluding with each other, hence data privacy is further enhanced. And we conduct simulations to demonstrate the feasibility of the propose method.

With the rapid development of cloud computing which has been extensively applied in the health research, the concept of medical cloud has become widespread. In this paper, we proposed an integrated medical cloud architecture with multiple applications based on privacy protection. The scheme in this paper adopted attribute encryption to ensure the PHR files encrypted all the time in order to protect the health privacy of the PHR owners not leaked. In addition, the medical cloud architecture proposed in this paper is suitable for multiple application scenarios. Different from the traditional domain division which has public domain (PUD) and private domain (PSD), the PUD domain is further divided into PUD1and PUD2 with finer granularity based on different permissions of the PHR users. In the PUD1, the PHR users have read or write access to the PHR files, while the PHR users in the PUD2 only have read permissions. In the PSD, we use key aggregation encryption (KAE) to realize the access control. For PHR users of PUD1 and PUD2, the outsourcable ABE technology is adopted to greatly reduce the computing burden of users. The results of function and performance test show that the scheme is safe and effective.

Cloud computing is one of the greatest and authoritative paradigms in computing as it provides access and use of various third-party services at a lower cost. However, there exist various security challenges facing cloud computing especially in the aspect of data privacy and this is more critical when dealing with sensitive personal or organization's data. Cloud service providers encrypt data during transfer from the local hard drive to the cloud server and at the server-side, the only problem is that the encryption key is stored by the service provider meaning they can decrypt your data. This paper discusses how cloud security can be enhanced by using client-side data encryption (pre-internet encryption), this will allow the clients to encrypt data before uploading to the cloud and store the key themselves. This means that data will be rendered to the cloud in an unreadable and secure format that cannot be accessed by unauthorized persons.

Cloud technology is advancing rapidly because of it’s capability to replace the traditional computing techniques. Cloud offers various kinds of services for the user that are being used. In this research paper, storage as a service provided by cloud is examined as the data of the owner is being shared to the cloud so we have to ensure that data integrity is being maintained. In order to have a robust mechanism that offers a secure pathway for sharing data different encryption algorithms have been utilized. We investigate all the suitable algorithms with various combinations because any single algorithm is prone to some kind of attack. Testing of these algorithms is done by analyzing the parameters such as time required for execution, use of computational resources, key management, etc. Finally the best one that stands and fulfill all the criteria in a reasonable manner is selected for the purpose of storage.

The power grid has high requirements for data security, and data security audit technology is facing challenges. Because the server in the power grid operating environment is considered untrustworthy and does not have the authority to obtain the secret key, the encrypted data cannot be parsed and the data processing ability of the data center is restricted. In response to the above problems, the power grid database encryption system was designed, and the access control module and the encryption module that should be written based on SQL statements were explained. The database encryption system was developed using the Java language and deployed in the cloud environment. Finally, the method was proved by experiments. feasibility.

Cloud based cyber physical system (CPS) enables individuals to store and share data collected from both cyberspace and the physical world. This leads to the proliferation of massive data at a user's local site. Since local storage systems can't store and maintain huge data, it is a wise and practical way to outsource such huge data to the cloud. Cloud storage provides scalable storage space to manage data economically and flexibly. However, the integrity of outsourced data is a critical challenge because user's lose control of their data once it's transferred to cloud servers. Several auditing schemes have been put forward based on public key infrastructure (PKI) or identity-based cryptography to verify data integrity. However, “the PKI-based schemes suffer from certificate management problem and identity-based schemes face the key escrow” problem. Therefore, to address these problems, certificateless public auditing schemes have been introduced on the basis of bilinear pairing, which incur high computation overhead, and thus it is not suitable for CPS. To reduce the computation overhead, in this paper, Using elliptic curve cryptography, we propose an efficient pairing-free certificateless public auditing scheme for cloud-based CPS. The proposed scheme is more secure against type I/II/III adversaries and efficient compared to other certificateless based schemes.

Information Security is a unified piece of information technology that has emerged as vibrant technology in the last two decades. To manage security, authentication assumes a significant part. Biometric is the physical unique identification as well as authentication for the third party. We have proposed the security model for preventing many attacks so we are used the innermost layer as a 3DES (Triple Encryption standard) cryptography algorithm that is providing 3- key protection as 64-bit and the outermost layer used the MD5 (Message Digest) algorithm. i. e. providing 128-bit protection as well as we is using fingerprint identification as physical security that is used in third-party remote integrity auditing. Remote data integrity auditing is proposed to ensure the uprightness of the information put away in the cloud. Data Storage of cloud services has expanded paces of acknowledgment because of their adaptability and the worry of the security and privacy levels. The large number of integrity and security issues that arise depends on the difference between the customer and the service provider in the sense of an external auditor. The remote data integrity auditing is at this point prepared to be viably executed. In the meantime, the proposed scheme is depending on identity-based cryptography, which works on the convoluted testament of the executives. The safety investigation and the exhibition assessment show that the planned property is safe and productive.

In a Leading field of Information Technology moreover make information Security a unified piece of it. To manage security, Authentication assumes a significant part. Biometric is the physical unique identification as well as Authentication for third party. We are proposed the Security model for preventing many attacks so we are used Inner most layer as a 3DES (Triple Encryption standard) Cryptography algorithm that is providing 3-key protection as 64-bit And the outer most layer used the MD5 (Message Digest) Algorithm. i. e. Providing 128 – bit protection. As well as we are using Fingerprint Identification as a physical Security that used in third party remote integrity auditing, and remote data integrity auditing is proposed to ensure the uprightness of the information put away in the cloud. Data Storage of cloud services has expanded paces of acknowledgment because of their adaptability and the worry of the security and privacy levels. The large number of integrity and security issues that arise depends on the difference between the customer and the service provider in the sense of an external auditor. The remote data integrity auditing is at this point prepared to be viably executed. In the meantime, the proposed scheme is depends on identity-based cryptography, which works on the convoluted testament the executives. The safety investigation and the exhibition assessment show that the planned property is safe and productive.

Cloud computing has revolutionized the way how users store, process, and use data. It has evolved over the years to put forward various sophisticated models that offer enhanced performance. The growth of electronic data stored in the Cloud has made it crucial to access data without data loss and leakage. Security threats still prevent significant corporations that use sensitive data to employ cloud computing to handle their data. Traditional cryptographic techniques like DES, AES, etc... provide data confidentiality but are computationally complex. To overcome such complexities, a unique field of cryptography known as DNA Cryptography came into existence. DNA cryptography is a new field of cryptography that utilizes the chemical properties of DNA for secure data encoding. DNA cryptographic algorithms are much faster than traditional cryptographic methods and can bring about greater security with lesser computational costs. In this paper, we have proposed an enhanced DNA cryptosystem involving operations such as encryption, encoding table generation, and decryption based on the chemical properties of DNA. The performance analysis has proven that the proposed DNA cryptosystem is secure and efficient in Cloud data storage.

The emergence of the 5G network has boosted the advancements in the field of the internet of things (IoT) and edge/cloud computing. We present a novel architecture to detect fire in indoor and outdoor environments, dubbed as EAC-FD, an abbreviation of edge and cloud-based fire detection. Compared with existing frameworks, ours is lightweight, secure, cost-effective, and reliable. It utilizes a hybrid edge and cloud computing framework with Intel neural compute stick 2 (NCS2) accelerator is for inference in real-time with Raspberry Pi 3B as an edge device. Our fire detection model runs on the edge device while also capable of cloud computing for more robust analysis making it a secure system. We compare different versions of SSD-MobileNet architectures with ours suitable for low-end devices. The fire detection model shows a good balance between computational cost frames per second (FPS) and accuracy.

A smart home provides better living environment by allowing remote Internet access for controlling the home appliances and devices. Security of smart homes is an important application area commonly using Passive Infrared Sensors (PIRs), image capture and analysis but such solutions sometimes fail to detect an event. An unambiguous person detection is important for security applications so that no event is missed and also that there are no false alarms which result in waste of resources. Cloud platforms provide deep learning and IoT services which can be used to implement an automated and failsafe security application. In this paper, we demonstrate reliable person detection for indoor and outdoor scenarios by integrating an application running on an edge device with AWS cloud services. We provide results for identifying a person before authorizing entry, detecting any trespassing within the boundaries, and monitoring movements within the home.

With the development of cloud computing, a growing number of users use the cloud to store their sensitive data. To protect privacy, users often encrypt their data before outsourcing. Searchable Symmetric Encryption (SSE) enables users to retrieve their encrypted data. Most prior SSE schemes did not focus on malicious servers, and users could not confirm the correctness of the search results. Blockchain-based SSE schemes show the potential to solve this problem. However, the expensive nature of storage overhead on the blockchain presents an obstacle to the implementation of these schemes. In this paper, we propose a lightweight blockchain-based searchable symmetric encryption scheme that reduces the space cost in the scheme by improving the data structure of the encrypted index and ensuring efficient data retrieval. Experiment results demonstrate the practicability of our scheme.

Homomorphic Encryption (HE) comes as a sophisticated and powerful cryptography system that can preserve the privacy of data in all cases when the data is at rest or even when data is in processing and computing. All the computations needed by the user or the provider can be done on the encrypted data without any need to decrypt it. However, HE has overheads such as big key sizes and long ciphertexts and as a result long execution time. This paper proposes a novel solution for big data analytic based on clustering and the Elliptical Curve Cryptography (ECC). The Extremely Distributed Clustering technique (EDC) has been used to divide big data into several subsets of cloud computing nodes. Different clustering techniques had been investigated, and it was found that using hybrid techniques can improve the performance and efficiency of big data analytic while at the same time data is protected and privacy is preserved using ECC.

The transmission of various facilities and services via the network is known as cloud computing. They involve data storage, data centers, networks, internet, and software applications, among other systems and features. Cryptography is a technique in which plain text is converted into cipher-text to preserve information security. It basically consists of encryption and decryption. The level of safety is determined by the category of encryption and decryption technique employed. The key plays an important part in the encryption method. If the key is leaked, anyone can intrude into the data and there is no use of this encryption. When the data is lost and the server fails to deliver it to the user, then it is to be recovered from any of the backup server using a recovery technique. The main objective is to develop an advanced method to increase the scope for data protection in cloud. Elliptic Curve Cryptography is a relatively new approach in the area of cryptography. The degree of security provides higher as compared to other Cryptographic techniques. The raw data and it’s accompanying as CII characters are combined and sent into the Elliptic Curve Cryptography as a source. This method eliminates the need for the transmitter and recipient to have a similar search database. Finally, a plain text is converted into cipher-text using Elliptic Curve Cryptography. The results are oat aimed by implementing a C program for Elliptic Curve Cryptography. Encryption, decryption and recovery using suitable algorithms are done.

Cloud security includes the strategies which works together to guard data and infrastructure with a set of policies, procedures, controls and technologies. These security events are arranged to protect cloud data, support supervisory obedience and protect customers' privacy as well as setting endorsement rules for individual users and devices. The partition-based handling and encryption mechanism which provide fine-grained admittance control and protected data sharing to the data users in cloud computing. Graph partition problems fall under the category of NP-hard problems. Resolutions to these problems are generally imitative using heuristics and approximation algorithms. Partition problems strategy is used in bi-criteria approximation or resource augmentation approaches with a common extension of hyper graphs, which can address the storage hierarchy.

In this paper we propose a security and cost aware scheduling heuristic for real-time workflow jobs that process Internet of Things (IoT) data with various security requirements. The environment under study is a four-tier architecture, consisting of IoT, mist, fog and cloud layers. The resources in the mist, fog and cloud tiers are considered to be heterogeneous. The proposed scheduling approach is compared to a baseline strategy, which is security aware, but not cost aware. The performance evaluation of both heuristics is conducted via simulation, under different values of security level probabilities for the initial IoT input data of the entry tasks of the workflow jobs.

Fog computing is a new computing paradigm that utilizes numerous mutually cooperating terminal devices or network edge devices to provide computing, storage, and communication services. Fog computing extends cloud computing services to the edge of the network, making up for the deficiencies of cloud computing in terms of location awareness, mobility support and latency. However, fog nodes are not active enough to perform tasks, and fog nodes recruited by cloud service providers cannot provide stable and continuous resources, which limits the development of fog computing. In the process of cloud service providers using the resources in the fog nodes to provide services to users, the cloud service providers and fog nodes are selfish and committed to maximizing their own payoffs. This situation makes it easy for the fog node to work negatively during the execution of the task. Limited by the low quality of resource provided by fog nodes, the payoff of cloud service providers has been severely affected. In response to this problem, an appropriate incentive mechanism needs to be established in the fog computing environment to solve the core problems faced by both cloud service providers and fog nodes in maximizing their respective utility, in order to achieve the incentive effect. Therefore, this paper proposes an incentive model based on repeated game, and designs a trigger strategy with credible threats, and obtains the conditions for incentive consistency. Under this condition, the fog node will be forced by the deterrence of the trigger strategy to voluntarily choose the strategy of actively executing the task, so as to avoid the loss of subsequent rewards when it is found to perform the task passively. Then, using evolutionary game theory to analyze the stability of the trigger strategy, it proves the dynamic validity of the incentive consistency condition.

The spread of Internet of Things (IoT) devices and high-speed communications, such as 5G, makes their services rich and diverse. Therefore, it is desirable to perform functions of rich services transparently and use edge computing environments flexibly at intermediate locations on the Internet, from the perspective of a network system. When this type of edge computing environment is achieved, IoT nodes as end devices of the Internet can fully utilize edge computing systems and cloud systems without any change, such as switching destination IP addresses between them, along with protocol maintenance for the switching. However, when the data transfer in the communication is encrypted, a decryption method is necessary at the edge, to realize these transparent edge services. In this study, a transparent common key-exchanging method with cloud service has been proposed as the destination node of a communication pair, to transparently decrypt a secure sockets layer-encrypted communication stream at the edge area. This enables end devices to be free from any changes and updates to communicate with the destination node.

This paper designs a data anomaly detection method for power grid data centers. The method uses cloud computing architecture to realize the storage and calculation of large amounts of data from power grid data centers. After that, the STL decomposition method is used to decompose the grid data, and then the decomposed residual data is used for anomaly analysis to complete the detection of abnormal data in the grid data. Finally, the feasibility of the method is verified through experiments.

The paper deals with exponentially growing technology - Internet of Things (IoT) in the field of healthcare. It is spoken about the networked healthcare and medical architecture. The attention is given to the analysis of the international regulations on medical and healthcare cybersecurity. For building a trustworthy healthcare IoT solution, a developed normative hierarchical model of the international cybersecurity standards is provided. For cybersecurity assessment of such systems the case-oriented technique, which includes Advanced Security Assurance Case (ASAC) and an example on a wireless insulin pump of its application are provided.

Cloud computing facilitates the access of applications and data from any location by using any device with an internet connection. It enables multiple applications and users to access the same data resources. Cloud based information sharing is a technique that allows researchers to communicate and collaborate, that leads to major new developments in the field. It also enables users to access data over the cloud easily and conveniently. Privacy, authenticity and confidentiality are the three main challenges while sharing data in cloud. There are many methods which support secure data sharing in cloud environment such as Attribute Based Encryption(ABE), Role Based Encryption, Hierarchical Based Encryption, and Identity Based Encryption. ABE provides secure access control mechanisms for integrity. It is classified as Key Policy Attribute Based Encryption(KP-ABE) and Ciphertext Policy Attribute Based Encryption(CP-ABE) based on access policy integration. In KPABE, access structure is incorporated with user's private key, and data are encrypted over a defined attributes. Moreover, in CPABE, access structure is embedded with ciphertext. This paper reviews CP-ABE methods that have been developed so far for achieving secured data sharing in cloud environment.

With the processes of collecting, analyzing, and transmitting the data in the Internet of Things (IoT), the Internet of Medical Things (IoMT) comprises the medical equipment and applications connected to the healthcare system and offers an entity with real time, remote measurement, and analysis of healthcare data. However, the IoMT ecosystem deals with some great challenges in terms of security, such as privacy leaking, eavesdropping, unauthorized access, delayed detection of life-threatening episodes, and so forth. All these negative effects seriously impede the implementation of the IoMT ecosystem. To overcome these obstacles, this article presents an efficient, outsourced online/offline revocable ciphertext policy attribute-based encryption scheme with the aid of cloud servers and blockchains in the IoMT ecosystem. Our proposal achieves the characteristics of fine-grained access control, fast encryption, outsourced decryption, user revocation, and ciphertext verification. It is noteworthy that based on the chameleon hash function, we construct the private key of the data user with collision resistance, semantically secure, and key-exposure free to achieve revocation. To the best of our knowledge, this is the first protocol for a revocation mechanism by means of the chameleon hash function. Through formal analysis, it is proven to be secure in a selectively replayable chosen-ciphertext attack (RCCA) game. Finally, this scheme is implemented with the Java pairing-based cryptography library, and the simulation results demonstrate that it enables high efficiency and practicality, as well as strong reliability for the IoMT ecosystem.

As the public cloud becomes one of the leading ways in data sharing nowadays, data confidentiality and user privacy are increasingly critical. Partially policy-hidden ciphertext policy attribute-based encryption (CP-ABE) can effectively protect data confidentiality while reducing privacy leakage by hiding part of the access structure. However, it cannot satisfy the need of data sharing in the public cloud with complex users and large amounts of data, both in terms of less expressive access structures and limited granularity of policy hiding. Moreover, the verification of access right to shared data and correctness of decryption are ignored or conducted by an untrusted third party, and the prime-order groups are seldom considered in the expressive policy-hidden schemes. This paper proposes a fully policy-hidden CP-ABE scheme constructed on LSSS access structure and prime-order groups for public cloud data sharing. To help users decrypt, HVE with a ``convert step'' is applied, which is more compatible with CP-ABE. Meanwhile, decentralized credible verification of access right to shared data and correctness of decryption based on blockchain are also provided. We prove the security of our scheme rigorously and compare the scheme with others comprehensively. The results show that our scheme performs better.

In the era of big data, more and more users store data in the cloud. Massive amounts of data have brought huge storage costs to cloud storage providers, and data deduplication technology has emerged. In order to protect the confidentiality of user data, user data should be encrypted and stored in the cloud. Therefore, deduplication of encrypted data has become a research hotspot. Cloud storage provides users with data sharing services, and the sharing of encrypted data is another research hotspot. The combination of encrypted data deduplication and sharing will inevitably become a future trend. The current better-performing updateable block-level message-locked encryption (UMLE) deduplication scheme does not support data sharing, and the performance of the encrypted data de-duplication scheme that introduces data sharing is not as good as that of UMLE. This paper introduces the ciphertext policy attribute based encryption (CP-ABE) system sharing mechanism on the basis of UMLE, applies the CP-ABE method to encrypt the master key generated by UMLE, to achieve secure and efficient data deduplication and sharing. In this paper, we propose a permission verification method based on bilinear mapping, and according to the definition of the security model proposed in the security analysis phase, we prove this permission verification method, showing that our scheme is secure. The comparison of theoretical analysis and simulation experiment results shows that this scheme has more complete functions and better performance than existing schemes, and the proposed authorization verification method is also secure.

Recently, with the development of the cloud environment, users can store their data or share it with other users. However, various security threats can occur in data sharing systems in the cloud environment. To solve this, data sharing systems and access control methods using the CP-ABE method are being studied, but the following problems may occur. First, in an outsourcing server that supports computation, it is not possible to prove that the computed result is a properly computed result when performing the partial decryption process of the ciphertext. Therefore, the user needs to verify the message obtained by performing the decryption process, and verify that the data is uploaded by the data owner through verification. As another problem, because the data owner encrypts data with attribute-based encryption, the number of attributes included in the access structure increases. This increases the size of the ciphertext, which can waste space in cloud storage. Therefore, a ciphertext of a constant size must be output regardless of the number of attributes when generating the ciphertext. In this paper, we proposes a CP-ABE based data sharing system that provides signature-based verifiable outsourcing. It aims at a system that allows multiple users to share data safely and efficiently in a cloud environment by satisfying verifiable outsourcing and constant-sized ciphertext output among various security requirements required by CP-ABE.