scholarly journals Highly Efficient Implementation of Block Ciphers on Graphic Processing Units for Massively Large Data

2020 ◽  
Vol 10 (11) ◽  
pp. 3711 ◽  
Author(s):  
SangWoo An ◽  
Seog Chung Seo
Keyword(s):  
Cloud Computing ◽  
Block Cipher ◽  
Personal Information ◽  
Large Data ◽  
Block Ciphers ◽  
Optimization Techniques ◽  
Graphic Processing Units ◽  
Highly Efficient ◽  
Cloud Computing Service ◽  
Graphic Processing

With the advent of IoT and Cloud computing service technology, the size of user data to be managed and file data to be transmitted has been significantly increased. To protect users’ personal information, it is necessary to encrypt it in secure and efficient way. Since servers handling a number of clients or IoT devices have to encrypt a large amount of data without compromising service capabilities in real-time, Graphic Processing Units (GPUs) have been considered as a proper candidate for a crypto accelerator for processing a huge amount of data in this situation. In this paper, we present highly efficient implementations of block ciphers on NVIDIA GPUs (especially, Maxwell, Pascal, and Turing architectures) for environments using massively large data in IoT and Cloud computing applications. As block cipher algorithms, we choose AES, a representative standard block cipher algorithm; LEA, which was recently added in ISO/IEC 29192-2:2019 standard; and CHAM, a recently developed lightweight block cipher algorithm. To maximize the parallelism in the encryption process, we utilize Counter (CTR) mode of operation and customize it by using GPU’s characteristics. We applied several optimization techniques with respect to the characteristics of GPU architecture such as kernel parallelism, memory optimization, and CUDA stream. Furthermore, we optimized each target cipher by considering the algorithmic characteristics of each cipher by implementing the core part of each cipher with handcrafted inline PTX (Parallel Thread eXecution) codes, which are virtual assembly codes in CUDA platforms. With the application of our optimization techniques, in our implementation on RTX 2070 GPU, AES and LEA show up to 310 Gbps and 2.47 Tbps of throughput, respectively, which are 10.7% and 67% improved compared with the 279.86 Gbps and 1.47 Tbps of the previous best result. In the case of CHAM, this is the first optimized implementation on GPUs and it achieves 3.03 Tbps of throughput on RTX 2070 GPU.

scholarly journals Parallel Implementations of ARX-Based Block Ciphers on Graphic Processing Units

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1894
Author(s):  
SangWoo An ◽  
YoungBeom Kim ◽  
Hyeokdong Kwon ◽  
Hwajeong Seo ◽  
Seog Chung Seo
Keyword(s):  
Graphics Processing Units ◽  
Block Cipher ◽  
Personal Information ◽  
Operation Mode ◽  
Optimization Methods ◽  
Block Ciphers ◽  
Optimization Techniques ◽  
Parallel Optimization ◽  
Graphic Processing Units ◽  
Iot Devices

With the development of information and communication technology, various types of Internet of Things (IoT) devices have widely been used for convenient services. Many users with their IoT devices request various services to servers. Thus, the amount of users’ personal information that servers need to protect has dramatically increased. To quickly and safely protect users’ personal information, it is necessary to optimize the speed of the encryption process. Since it is difficult to provide the basic services of the server while encrypting a large amount of data in the existing CPU, several parallel optimization methods using Graphics Processing Units (GPUs) have been considered. In this paper, we propose several optimization techniques using GPU for efficient implementation of lightweight block cipher algorithms on the server-side. As the target algorithm, we select high security and light weight (HIGHT), Lightweight Encryption Algorithm (LEA), and revised CHAM, which are Add-Rotate-Xor (ARX)-based block ciphers, because they are used widely on IoT devices. We utilize the features of the counter (CTR) operation mode to reduce unnecessary memory copying and operations in the GPU environment. Besides, we optimize the memory usage by making full use of GPU’s on-chip memory such as registers and shared memory and implement the core function of each target algorithm with inline PTX assembly codes for maximizing the performance. With the application of our optimization methods and handcrafted PTX codes, we achieve excellent encryption throughput of 468, 2593, and 3063 Gbps for HIGHT, LEA, and revised CHAM on RTX 2070 NVIDIA GPU, respectively. In addition, we present optimized implementations of Counter Mode Based Deterministic Random Bit Generator (CTR_DRBG), which is one of the widely used deterministic random bit generators to provide a large amount of random data to the connected IoT devices. We apply several optimization techniques for maximizing the performance of CTR_DRBG, and we achieve 52.2, 24.8, and 34.2 times of performance improvement compared with CTR_DRBG implementation on CPU-side when HIGHT-64/128, LEA-128/128, and CHAM-128/128 are used as underlying block cipher algorithm of CTR_DRBG, respectively.

scholarly journals Efficient Implementation of ARX-Based Block Ciphers on 8-Bit AVR Microcontrollers

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1837
Author(s):  
YoungBeom Kim ◽  
Hyeokdong Kwon ◽  
SangWoo An ◽  
Hwajeong Seo ◽  
Seog Chung Seo
Keyword(s):  
Personal Information ◽  
Block Ciphers ◽  
Efficient Implementation ◽  
Optimization Techniques ◽  
Sensitive Data ◽  
Additional Function ◽  
Performance Improvements ◽  
Function Calls ◽  
Improved Performance ◽  
The Cost

As the development of Internet of Things (IoT), the data exchanged through the network has significantly increased. To secure the sensitive data with user’s personal information, it is necessary to encrypt the transmitted data. Since resource-constrained wireless devices are typically used for IoT services, it is required to optimize the performance of cryptographic algorithms which are computation-intensive tasks. In this paper, we present efficient implementations of ARX-based Korean Block Ciphers (HIGHT and LEA) with CounTeR (CTR) mode of operation, and CTR_DRBG, one of the most widely used DRBGs (Deterministic Random Bit Generators), on 8-bit AVR Microcontrollers (MCUs). Since 8-bit AVR MCUs are widely used for various types of IoT devices, we select it as the target platform in this paper. We present an efficient implementation of HIGHT and LEA by making full use of the property of CTR mode, where the nonce value is fixed, and only the counter value changes during the encryption. On our implementation, the cost of additional function calls occurred by the generation of look-up table can be reduced. With respect to CTR_DRBG, we identified several parts that do not need to be computed. Thus, precomputing those parts in offline and using them online can result in performance improvements for CTR_DRBG. Furthermore, we applied several optimization techniques by making full use of target devices’ characteristics with AVR assembly codes on 8-bit AVR MCUs. Our proposed table generation way can reduce the cost for building a precomputation table by around 6.7% and 9.1% in the case of LEA and HIGHT, respectively. Proposed implementations of LEA and HIGHT with CTR mode on 8-bit AVR MCUs provide 6.3% and 3.8% of improved performance, compared with the previous best results, respectively. Our implementations are the fastest compared to previous LEA and HIGHT implementations on 8-bit AVR MCUs. In addition, the proposed CTR_DRBG implementations on AVR provide better performance by 37.2% and 8.7% when the underlying block cipher is LEA and HIGHT, respectively.

scholarly journals Efficient Parallel Implementations of LWE-Based Post-Quantum Cryptosystems on Graphics Processing Units

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1781
Author(s):  
SangWoo An ◽  
Seog Chung Seo
Keyword(s):  
Cloud Computing ◽  
Parallel Processing ◽  
Graphics Processing Units ◽  
Optimization Techniques ◽  
Parallel Optimization ◽  
Processing Unit ◽  
Processing Technologies ◽  
Performance Improvements ◽  
Cloud Computing Service ◽  
Graphics Processing

With the development of the Internet of Things (IoT) and cloud computing technology, various cryptographic systems have been proposed to protect increasing personal information. Recently, Post-Quantum Cryptography (PQC) algorithms have been proposed to counter quantum algorithms that threaten public key cryptography. To efficiently use PQC in a server environment dealing with large amounts of data, optimization studies are required. In this paper, we present optimization methods for FrodoKEM and NewHope, which are the NIST PQC standardization round 2 competition algorithms in the Graphics Processing Unit (GPU) platform. For each algorithm, we present a part that can perform parallel processing of major operations with a large computational load using the characteristics of the GPU. In the case of FrodoKEM, we introduce parallel optimization techniques for matrix generation operations and matrix arithmetic operations such as addition and multiplication. In the case of NewHope, we present a parallel processing technique for polynomial-based operations. In the encryption process of FrodoKEM, the performance improvements have been confirmed up to 5.2, 5.75, and 6.47 times faster than the CPU implementation in FrodoKEM-640, FrodoKEM-976, and FrodoKEM-1344, respectively. In the encryption process of NewHope, the performance improvements have been shown up to 3.33 and 4.04 times faster than the CPU implementation in NewHope-512 and NewHope-1024, respectively. The results of this study can be used in the IoT devices server or cloud computing service server. In addition, the results of this study can be utilized in image processing technologies such as facial recognition technology.

scholarly journals An Analysis of Data Security and Privacy for Cloud Computing

2020 ◽  
Vol 9 (1) ◽  
pp. 27-39
Author(s):  
Akella Subhadra
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Large Data ◽  
Cost Effective ◽  
Cloud Service ◽  
Third Party ◽  
Security And Privacy ◽  
Service Users ◽  
Digital Information ◽  
Cloud Computing Service

Cloud Computing is the important buzzword in the today’s world of computer. Cloud is global platform that allows digital information to be stored and distributed at very less cost and very fast to use. In these days since the data is very big in size many users are interested to store their valuable data in the cloud .The application software and databases in cloud computing are moved to the centralized large data centers, where the management of the data and services may not be fully trustworthy. Cloud Computing is scalable, fast, flexible, and cost-effective technology platform for IT enabled services over the internet. There are various advantages of cloud computing but ultimately cloud service users have to put their data over the cloud i.e., third party servers which are not directly controlled by the data owner Data security has consistently been a major issue in information technology In cloud computing in users perspective mainly in government ,industry and business Data security and ivacy protection issues are relevant to both hardware and software in the cloud architecture. Cloud security is becoming a key differentiator and competitive edge between cloud providers. In spite of various benefits that are provided by the cloud computing services, cloud computing service users are very much afraid about the security of their data .So this paper focuses on various issues regarding cloud computing, data security and how cloud provides data integrity, confidentiality, availability over user’s data? How data stored over cloud storage servers will be protected from attackers? Risk management of data present on the Cloud is another challenge. There is a requirement to identify the risks an organization would be taking while hosting data and services on the Cloud. In this paper, we present those issues that are preventing people from adopting the cloud and to minimize risks of these issues.

Highly Efficient, Linear-Scaling Seminumerical Exact-Exchange Method for Graphic Processing Units

2020 ◽  
Vol 16 (3) ◽  
pp. 1456-1468 ◽  
Author(s):  
Henryk Laqua ◽  
Travis H. Thompson ◽  
Jörg Kussmann ◽  
Christian Ochsenfeld
Keyword(s):  
Linear Scaling ◽  
Graphic Processing Units ◽  
Exchange Method ◽  
Highly Efficient ◽  
Exact Exchange ◽  
Graphic Processing

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

A Circular Business Model for Cloud Computing Services Providers

10.31355/33 ◽  
2018 ◽  
Vol 2 ◽  
pp. 105-120
Author(s):  
Hamed Motaghi ◽  
Saeed Nosratabadi ◽  
Thabit Qasem Atobishi
Keyword(s):  
Cloud Computing ◽  
Business Model ◽  
Circular Economy ◽  
Service Providers ◽  
Sustainable Consumption ◽  
Future Research ◽  
Extensive Literature ◽  
Computing Services ◽  
Proposed Model ◽  
Cloud Computing Service

NOTE: THIS ARTICLE WAS PUBLISHED WITH THE INFORMING SCIENCE INSTITUTE. Aim/Purpose................................................................................................................................................................................................. The main objective of the current study is to develop a business model for service providers of cloud computing which is designed based on circular economy principles and can ensure the sustainable consumption. Background Even though the demand for cloud computing technology is increasing day by day in all over the world, the current the linear economy principles are incapable to ensure society development needs. To consider the benefit of the society and the vendors at the same time, the principles of circular economy can address this issue. Methodology................................................................................................................................................................................................. An extensive literature review on consumption, sustainable consumption, circular economic, business model, and cloud computing were conducted. the proposed model of Osterwalder, Pigneur and Tucci (2005) is admitted designing the circular business model. Contribution................................................................................................................................................................................................. The proposed model of the study is the contribution of this study where provides the guidelines for the cloud computing service providers to achieve both their economic profits and the society’ needs. Findings Finding reveals that if the cloud computing service providers design their business model based on the “access” principle of circular economy, they can meet their economic profits and the society’ needs at a same time. Recommendations for Practitioners.............................................................................................................................................................. It is recommended to the startup and the existing businesses to utilize the proposed model of this study to reach a sustainable development. Recommendation for Researchers................................................................................................................................................................ It proposes a new circular business model and its linkages with community building. Impact on Society............................................................................................................................................................................................ The proposed model of the study provides guidelines to the cloud computing service providers to design a business model which is able not only to meet their economic profit, but also to meet the society’s and customers’ benefits. Future Research............................................................................................................................................................................................... Future researches can build on this research model which proposed in this study to examine the limitations of this model by using empirical researches.

Sign in / Sign up

Export Citation Format

Share Document