Cloud-based Quadratic Optimization with Partially Homomorphic Encryption

The development of large-scale distributed control systems has led to the outsourcing of costly computations to cloud-computing platforms, as well as to concerns about privacy of the collected sensitive data. This paper develops a cloud-based protocol for a quadratic optimization problem involving multiple parties, each holding information it seeks to maintain private. The protocol is based on the projected gradient ascent on the Lagrange dual problem and exploits partially homomorphic encryption and secure multi-party computation techniques. Using formal cryptographic definitions of indistinguishability, the protocol is shown to achieve computational privacy, i.e., there is no computationally efficient algorithm that any involved party can employ to obtain private information beyond what can be inferred from the party's inputs and outputs only. In order to reduce the communication complexity of the proposed protocol, we introduced a variant that achieves this objective at the expense of weaker privacy guarantees. We discuss in detail the computational and communication complexity properties of both algorithms theoretically and also through implementations. We conclude the paper with a discussion on computational privacy and other notions of privacy such as the non-unique retrieval of the private information from the protocol outputs

Secure and Private Implementation of Dynamic Controllers Using Semi-Homomorphic Encryption

This paper presents a secure and private implementation of linear time-invariant dynamic controllers using Paillier's encryption, a semi-homomorphic encryption method. To avoid overflow or underflow within the encryption domain, the state of the controller is reset periodically. A control design approach is presented to ensure stability and optimize performance of the closed-loop system with encrypted controller.Comment: Improved numerical exampl

Iris Recognition Approach for Preserving Privacy in Cloud Computing

Biometric identification systems involve securing biometric traits by encrypting them using an encryption algorithm and storing them in the cloud. In recent decades, iris recognition schemes have been considered one of the most effective biometric models for identifying humans based on iris texture, due to their relevance and distinctiveness. The proposed system focuses on encrypting biometric traits. The user’s iris feature vector is encrypted and stored in the cloud. During the matching process, the user’s iris feature vector is compared with the one stored in the cloud. If it meets the threshold conditions, the user is authenticated. Iris identification in cloud computing involves several steps. First, the iris image is pre-processed to remove noise using the Hough transform. Then, the pixel values are normalized, Gabor filters are applied to extract iris features. The features are then encrypted using the AES 128-bit algorithm. Finally, the features of the test image are matched with the stored features on the cloud to verify authenticity. The process ensures the privacy and security of the iris data in cloud storage by utilizing encryption and efficient image processing techniques. The matching is performed by setting an appropriate threshold for comparison. Overall, the approach offers a significant level of safety, effectiveness, and accuracy

Securing the Cloud: A Critical Appraisal of Data Security Strategies

Cloud computing, a paradigm shift in the evolution of the internet, has garnered significant attention. However, security remains a primary concern, hindering its widespread adoption. Cloud computing essentially transfers user data and applications to remote data centers, where users relinquish control, and data management practices may not always adhere to the highest security standards. This unique characteristic of cloud computing raises a multitude of security concerns that warrant careful consideration and understanding. One of the most crucial and prevalent security concerns is the potential exposure of user data and applications stored on service provider premises. In this article, an attempt is made to review the literature in this area of research

A Survey: Secure Data Storage Techniques in Cloud Computing

Cloud computing is an era of research where we are looking for a fast and efficient computing solution with dynamic data. Cloud computing provide us a service which is use and pay on demand services, thus the user can have multiple options for data processing system. Many of the techniques to store data using security algorithm have been applied on cloud computing, but still the issue is its giving slow speed compare to server technique. Thus, a secure encryption technique with low computation and early scheme is always required. In this paper, we utilize and uniquely combine the Optimized blowfish homomorphism encryption with SHA-2 for key generation to make encryption more authentic. The proposed solution mentioned by us can give enhancement in security aspects as well as it compute fast data processing

Encryption as a Service (EaaS) as a Solution for Cryptography in Cloud

AbstractIn recent years, there has been a vast interest in optimal usage of computing resources so that massive data can be processed with minimal cost. The need to use a pool of shared resources in a wide area network that provide elasticity, high capacity of computation and ability to store information on location-independent storages have led to the advent of cloud-computing. However, the global nature of cloud brings about some challenges in security domain when physical control over our information in cloud is impossible. Thus, encrypting critical data becomes essential, and strongly advisable. The server-side encryption in an untrustworthy environment like public cloud is too risky. On the other hand, client-side encryption can undermine the benefits of cloud since it is a time-consuming task for encryption and decryption. To address this issue, we developed a private cloud as an intermediary. In this paper, based on XaaS concept, we design an Encryption as a Service in order to get rid of the security risks of cloud provider's encryption and the inefficiency of client-side encryption