Improved Software Implementation for Montgomery Elliptic Curve Cryptosystem

The last decade witnessed rapid increase in multimedia and other applications that require transmitting and protecting huge amount of data streams simultaneously.For such applications,a high-performance cryptosystem is compulsory to provide necessary security services.Elliptic curve cryptosystem(ECC)has been introduced as a considerable option.However,the usual sequential implementation of ECC and the standard elliptic curve(EC)form cannot achieve required performance level.Moreover,the widely used Hardware implementation of ECC is costly option and may be not affordable.This research aims to develop a high-performance parallel software implementation for ECC.To achieve this,many experiments were performed to examine several factors affecting ECC performance including the projective coordinates,the scalar multiplication algorithm,the elliptic curve(EC)form,and the parallel implementation.The ECC performance was analyzed using the different factors to tune-up them and select the best choices to increase the speed of the cryptosystem.Experimental results illustrated that parallel Montgomery ECC implementation using homogenous projection achieves the highest performance level,since it scored the shortest time delay for ECC computations.In addition,results showed thatNAF algorithm consumes less time to perform encryption and scalar multiplication operations in comparison withMontgomery ladder and binarymethods.Java multi-threading technique was adopted to implement ECC computations in parallel.The proposed multithreaded Montgomery ECC implementation significantly improves the performance level compared to previously presented parallel and sequential implementations.

Remote sensing image encryption algorithm based on novel hyperchaos and an elliptic curve cryptosystem

Remote sensing images carry crucial ground information,often involving the spatial distribution and spatiotemporal changes of surface elements.To safeguard this sensitive data,image encryption technology is essential.In this paper,a novel Fibonacci sine exponential map is designed,the hyperchaotic performance of which is particularly suitable for image encryption algorithms.An encryption algorithm tailored for handling the multi-band attributes of remote sensing images is proposed.The algorithm combines a three-dimensional synchronized scrambled diffusion operation with chaos to efficiently encrypt multiple images.Moreover,the keys are processed using an elliptic curve cryptosystem,eliminating the need for an additional channel to transmit the keys,thus enhancing security.Experimental results and algorithm analysis demonstrate that the algorithm offers strong security and high efficiency,making it suitable for remote sensing image encryption tasks.

Privacy Preserving Blockchain Technique to Achieve Secure and Reliable Sharing of IoT Data

In present digital era,an exponential increase in Internet of Things(IoT)devices poses several design issues for business concerning security and privacy.Earlier studies indicate that the blockchain technology is found to be a significant solution to resolve the challenges of data security exist in IoT.In this view,this paper presents a new privacy-preserving Secure Ant Colony optimization with Multi Kernel Support Vector Machine(ACOMKSVM)with Elliptical Curve cryptosystem(ECC)for secure and reliable IoT data sharing.This program uses blockchain to ensure protection and integrity of some data while it has the technology to create secure ACOMKSVM training algorithms in partial views of IoT data,collected from various data providers.Then,ECC is used to create effective and accurate privacy that protects ACOMKSVM secure learning process.In this study,the authors deployed blockchain technique to create a secure and reliable data exchange platform across multiple data providers,where IoT data is encrypted and recorded in a distributed ledger.The security analysis showed that the specific data ensures confidentiality of critical data from each data provider and protects the parameters of the ACOMKSVM model for data analysts.To examine the performance of the proposed method,it is tested against two benchmark dataset such as Breast Cancer Wisconsin Data Set(BCWD)and Heart Disease Data Set(HDD)from UCI AI repository.The simulation outcome indicated that the ACOMKSVM model has outperformed all the compared methods under several aspects.

Secure and Efficient Digital Rights Management Mechanisms with Privacy Protection

In the Internet or cloud computing environments, service providers provide more and more content services. Users can use these convenient content services in daily life. The major data of the user are maintained by the service providers except that some personal privacy data are stored at the client device. An attacker may try to invade the systems, and it will cause the damage of users and service providers. Also, users may lose their mobile devices and then it may cause the data disclosure problem. As a result, the data and privacy protection of users become an important issue in these environments. Besides, since many mobile devices are used in these environments, secure authentication and data protection methods must be efficient in these low resource environments. In this paper, we propose an efficient and privacy protection digital rights management(DRM)scheme that users can verify the valid service servers and the service servers can ensure the legal users. Since the key delegation center of the third party has the robust security protection, our proposed scheme stores the encrypted secret keys in the key delegation center. This approach not only can reduce the storage space of the user devices, but also can recover the encrypted secret keys in the key delegation center when a user loses her/his devices for solving the device losing problem.