scholarly journals Design and implementation of E-discovery as a service based on cloud computing

2013 ◽  
Vol 10 (2) ◽  
pp. 703-724 ◽  
Author(s):  
Taerim Lee ◽  
Hun Kim ◽  
Kyung-Hyune Rhee ◽  
Uk Shin
Keyword(s):  
Cloud Computing ◽  
Direct Contact ◽  
State Of The Art ◽  
Service Systems ◽  
Target System ◽  
Design And Implementation ◽  
Discovery Service ◽  
New Type ◽  
It Compliance ◽  
Network Device

Recently, as IT Compliance becomes more diverse, companies have to take a great amount of effort to comply with it and prepare countermeasures. Especially, E-Discovery is also one of the most notable compliances for IT and law. In order to minimize the time and cost for E-Discovery, many service systems and solutions using the state-of-the-art technology have been competitively developed. Among them, Cloud Computing is one of the most exclusive skills as a computing infrastructure for E-Discovery Service. Unfortunately, these products actually do not cover all kinds of E-Discovery works and have many drawbacks as well as considerable limitations. This paper, therefore, proposes a new type of E-Discovery Service Structure based on Cloud Computing called EDaaS(E-Discovery as a Service) to make the best usage of its advantages and overcome the limitations of the existing E-Discovery solutions. EDaaS enables E-Discovery participants to smoothly collaborate by removing constraints on working places and minimizing the number of direct contact with target systems. What those who want to use the EDaaS need is only a network device for using the Internet. Moreover, EDaaS can help to reduce the waste of time and human resources because no specific software to install on every target system is needed and the relatively exact time of completion can be obtained from it according to the amount of data for the manpower control. As a result of it, EDaaS can solve the litigant?s cost problem.

scholarly journals Design and Implementation of an IoT-based Transactional System for Quality Management

2021 ◽  
pp. 658-675
Author(s):  
Mohammed Issam Younis ◽  
Athraa H. Alwan
Keyword(s):  
Quality Management ◽  
Internet Of Things ◽  
Digital Signature ◽  
Direct Contact ◽  
State Of The Art ◽  
Current Development ◽  
Home Office ◽  
Design And Implementation ◽  
Network Communications ◽  
Access Right

The spread of Coronavirus has forced populations around the globe to adopt strict measures such as lockdown, home quarantine, and home office. Moreover, in the current development of network communications, people can exploit internet and intranet features in many systems that need to be faster, more efficient, and available on time. Furthermore, with the benefits of using internet-of-things (IoT), through which things are generated, gained, discovered, and proposed without interference, the user could receive the last status without exertion and direct contact (i.e., in a contactless manner). These specifications can be used in a transaction system. This paper proposes an electronic transaction system (ETS) as a replacement for the current paper transaction used in most organizations’ environments. The progress includes the signing privilege, access right for each position, delivery reports, transaction tracking, and transaction storage safety. Transactions will be stored in an encrypted way at the database to keep them safe from illegal changes. For that, a secure electronic transaction is created with digital signature services. The negligence can be identified in the workflow by tracking the operations and receiving exceptional cases’ alerts. Finally, this paper compared the proposed system against state-of-the-art systems.

scholarly journals Robust CNN Compression Framework for Security-Sensitive Embedded Systems

2021 ◽  
Vol 11 (3) ◽  
pp. 1093
Author(s):  
Jeonghyun Lee ◽  
Sangkyun Lee
Keyword(s):  
Embedded Systems ◽  
Optimization Problem ◽  
State Of The Art ◽  
Classification Problems ◽  
Proximal Gradient Method ◽  
Knowledge Distillation ◽  
New Type ◽  
Adversarial Examples ◽  
Adversarial Training ◽  
Memory Efficient

Convolutional neural networks (CNNs) have achieved tremendous success in solving complex classification problems. Motivated by this success, there have been proposed various compression methods for downsizing the CNNs to deploy them on resource-constrained embedded systems. However, a new type of vulnerability of compressed CNNs known as the adversarial examples has been discovered recently, which is critical for security-sensitive systems because the adversarial examples can cause malfunction of CNNs and can be crafted easily in many cases. In this paper, we proposed a compression framework to produce compressed CNNs robust against such adversarial examples. To achieve the goal, our framework uses both pruning and knowledge distillation with adversarial training. We formulate our framework as an optimization problem and provide a solution algorithm based on the proximal gradient method, which is more memory-efficient than the popular ADMM-based compression approaches. In experiments, we show that our framework can improve the trade-off between adversarial robustness and compression rate compared to the existing state-of-the-art adversarial pruning approach.

scholarly journals A Rigorous Evaluation of State-of-the-Art Scheduling Algorithms for Cloud Computing

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 75033-75047 ◽  
Author(s):  
Altaf Hussain ◽  
Muhamamd Aleem ◽  
Muhammad Arshad Islam ◽  
Muhammad Azhar Iqbal
Keyword(s):  
Cloud Computing ◽  
State Of The Art ◽  
Scheduling Algorithms ◽  
Rigorous Evaluation

State-of-the-art of design, evaluation, and operation methodologies in product service systems

2016 ◽  
Vol 77 ◽  
pp. 1-14 ◽  
Author(s):  
Min Qu ◽  
Suihuai Yu ◽  
Dengkai Chen ◽  
Jianjie Chu ◽  
Baozhen Tian
Keyword(s):  
State Of The Art ◽  
Service Systems ◽  
Design Evaluation ◽  
Product Service ◽  
Product Service Systems

Towards Update-Efficient and Parallel-Friendly Content-Based Indexing Scheme in Cloud Computing

2018 ◽  
Vol 12 (02) ◽  
pp. 191-213
Author(s):  
Nan Zhu ◽  
Yangdi Lu ◽  
Wenbo He ◽  
Hua Yu ◽  
Jike Ge
Keyword(s):  
Cloud Computing ◽  
State Of The Art ◽  
High Volume ◽  
Data Partitioning ◽  
The State ◽  
Computing Systems ◽  
Indexing System ◽  
Indexing Method ◽  
Concurrent User ◽  
Art Research

The sheer volume of contents generated by today’s Internet services is stored in the cloud. The effective indexing method is important to provide the content to users on demand. The indexing method associating the user-generated metadata with the content is vulnerable to the inaccuracy caused by the low quality of the metadata. While the content-based indexing does not depend on the error-prone metadata, the state-of-the-art research focuses on developing descriptive features and misses the system-oriented considerations when incorporating these features into the practical cloud computing systems. We propose an Update-Efficient and Parallel-Friendly content-based indexing system, called Partitioned Hash Forest (PHF). The PHF system incorporates the state-of-the-art content-based indexing models and multiple system-oriented optimizations. PHF contains an approximate content-based index and leverages the hierarchical memory system to support the high volume of updates. Additionally, the content-aware data partitioning and lock-free concurrency management module enable the parallel processing of the concurrent user requests. We evaluate PHF in terms of indexing accuracy and system efficiency by comparing it with the state-of-the-art content-based indexing algorithm and its variances. We achieve the significantly better accuracy with less resource consumption, around 37% faster in update processing and up to 2.5[Formula: see text] throughput speedup in a multi-core platform comparing to other parallel-friendly designs.

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