Awareness of Sustainability, Green IT, and Cloud Computing in Indian Organisations

2015 ◽  
pp. 269-287 ◽  
Author(s):  
Tomayess Issa ◽  
Girish Tolani ◽  
Vanessa Chang ◽  
Theodora Issa
Keyword(s):  
Cloud Computing ◽  
Online Survey ◽  
Security And Privacy ◽  
Research Papers ◽  
Green It ◽  
Public And Private

This chapter examines the level of awareness that organizations in India have of the concepts, strengths and benefits of sustainability, green IT and cloud computing. Very few research papers have examined the sustainability, green IT awareness and cloud computing issues in India, and it has become necessary to ascertain just where Indian organizations stand when it comes to these concerns. Before determining whether these organisations are progressing towards sustainability, green IT and cloud computing, it is first necessary to determine whether, and to what extent, they are aware of these concepts. This research is to obtain answers, which hopefully will be a first step in a shift towards sustainability and green IT, via an online survey. Seventy-five respondents from public and private Indian organizations participated in this survey and confirmed that cloud computing is efficient, flexible and easy to maintain, although security and privacy are major concerns for Indian organizations.

Awareness of Sustainability, Green IT, and Cloud Computing in Indian Organisations

2019 ◽  
pp. 1591-1609
Author(s):  
Tomayess Issa ◽  
Girish Tolani ◽  
Vanessa Chang ◽  
Theodora Issa
Keyword(s):  
Cloud Computing ◽  
Online Survey ◽  
Security And Privacy ◽  
Research Papers ◽  
Green It ◽  
Public And Private

This chapter examines the level of awareness that organizations in India have of the concepts, strengths and benefits of sustainability, green IT and cloud computing. Very few research papers have examined the sustainability, green IT awareness and cloud computing issues in India, and it has become necessary to ascertain just where Indian organizations stand when it comes to these concerns. Before determining whether these organisations are progressing towards sustainability, green IT and cloud computing, it is first necessary to determine whether, and to what extent, they are aware of these concepts. This research is to obtain answers, which hopefully will be a first step in a shift towards sustainability and green IT, via an online survey. Seventy-five respondents from public and private Indian organizations participated in this survey and confirmed that cloud computing is efficient, flexible and easy to maintain, although security and privacy are major concerns for Indian organizations.

Awareness of Sustainability, Green IT, and Cloud Computing in Indian Organisations

2019 ◽  
pp. 1360-1378
Author(s):  
Tomayess Issa ◽  
Girish Tolani ◽  
Vanessa Chang ◽  
Theodora Issa
Keyword(s):  
Cloud Computing ◽  
Online Survey ◽  
Security And Privacy ◽  
Research Papers ◽  
Green It ◽  
Public And Private

This chapter examines the level of awareness that organizations in India have of the concepts, strengths and benefits of sustainability, green IT and cloud computing. Very few research papers have examined the sustainability, green IT awareness and cloud computing issues in India, and it has become necessary to ascertain just where Indian organizations stand when it comes to these concerns. Before determining whether these organisations are progressing towards sustainability, green IT and cloud computing, it is first necessary to determine whether, and to what extent, they are aware of these concepts. This research is to obtain answers, which hopefully will be a first step in a shift towards sustainability and green IT, via an online survey. Seventy-five respondents from public and private Indian organizations participated in this survey and confirmed that cloud computing is efficient, flexible and easy to maintain, although security and privacy are major concerns for Indian organizations.

Analysis of the Join Performance in Vertically Distributed Cloud Databases

2015 ◽  
Vol 6 (2) ◽  
pp. 65-87 ◽  
Author(s):  
Jens Kohler ◽  
Kiril Simov ◽  
Thomas Specht
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Security And Privacy ◽  
Sensitive Data ◽  
Public And Private ◽  
Huge Data ◽  
Cloud Databases ◽  
Accounting Model ◽  
Privacy Constraints ◽  
Distributed Cloud

Cloud Computing becomes interesting for enterprises across all branches. Renting computing capabilities from external providers avoids initial investments, as only those resources have to be paid that were used eventually. Especially in the context of “Big Data” this pay-as-you-go accounting model is particularly important. The dynamically scalable resources from the Cloud enable enterprises to store or analyze these huge amounts of unstructured data without using their own hardware infrastructure. However, Cloud Computing is currently facing severe data security and protection issues. These challenges require new ways to store and analyze data, especially when huge data volumes with sensitive data are stored at external locations. The presented approach separates data on database table level into independent chunks and distributes them across several clouds. Hence, this work is a contribution to a more secure and resilient cloud architecture as multiple public and private cloud providers can be used independently to store data without losing data security and privacy constraints.

Issues in security and privacy of big data

2018 ◽  
Vol 7 (12) ◽  
pp. 1
Author(s):  
Shaveta Bhatia
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Approximate Method ◽  
Biomedical Research ◽  
Cyber Security ◽  
Data Science ◽  
Third Party ◽  
Security And Privacy ◽  
Security Threats ◽  
The Third

 The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity.  It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.

scholarly journals A Multi-Tiered Framework for Insider Threat Prevention

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1005
Author(s):  
Rakan A. Alsowail ◽  
Taher Al-Shehari
Keyword(s):  
Real World ◽  
Relevant Literature ◽  
Security And Privacy ◽  
Insider Threat ◽  
Unified Framework ◽  
Insider Threats ◽  
Public And Private ◽  
Private Organizations ◽  
Confidential Data ◽  
Real Value

As technologies are rapidly evolving and becoming a crucial part of our lives, security and privacy issues have been increasing significantly. Public and private organizations have highly confidential data, such as bank accounts, military and business secrets, etc. Currently, the competition between organizations is significantly higher than before, which triggers sensitive organizations to spend an excessive volume of their budget to keep their assets secured from potential threats. Insider threats are more dangerous than external ones, as insiders have a legitimate access to their organization’s assets. Thus, previous approaches focused on some individual factors to address insider threat problems (e.g., technical profiling), but a broader integrative perspective is needed. In this paper, we propose a unified framework that incorporates various factors of the insider threat context (technical, psychological, behavioral and cognitive). The framework is based on a multi-tiered approach that encompasses pre, in and post-countermeasures to address insider threats in an all-encompassing perspective. It considers multiple factors that surround the lifespan of insiders’ employment, from the pre-joining of insiders to an organization until after they leave. The framework is utilized on real-world insider threat cases. It is also compared with previous work to highlight how our framework extends and complements the existing frameworks. The real value of our framework is that it brings together the various aspects of insider threat problems based on real-world cases and relevant literature. This can therefore act as a platform for general understanding of insider threat problems, and pave the way to model a holistic insider threat prevention system.

Cloud computing security and privacy: Standards and regulations

2017 ◽  
Vol 54 ◽  
pp. 1-2 ◽  
Author(s):  
Yong Yu ◽  
Atsuko Miyaji ◽  
Man Ho Au ◽  
Willy Susilo
Keyword(s):  
Cloud Computing ◽  
Security And Privacy ◽  
Cloud Computing Security ◽  
Standards And Regulations

scholarly journals Data Security and Privacy in Cloud Computing

2014 ◽  
Vol 10 (7) ◽  
pp. 190903 ◽  
Author(s):  
Yunchuan Sun ◽  
Junsheng Zhang ◽  
Yongping Xiong ◽  
Guangyu Zhu
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Security And Privacy

Proposed Back Propagation Deep Neural Network for Intrusion Detection in Internet of Things Fog Computing

2021 ◽  
Vol 9 (4) ◽  
pp. 464-469
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Fog Computing ◽  
Denial Of Service ◽  
Back Propagation ◽  
Security And Privacy ◽  
Brute Force ◽  
Iot Platform ◽  
Proposed Model

Internet of things (IoT) is an emerging concept which aims to connect billions of devices with each other anytime regardless of their location. Sadly, these IoT devices do not have enough computing resources to process huge amount of data. Therefore, Cloud computing is relied on to provide these resources. However, cloud computing based architecture fails in applications that demand very low and predictable latency, therefore the need for fog computing which is a new paradigm that is regarded as an extension of cloud computing to provide services between end users and the cloud user. Unfortunately, Fog-IoT is confronted with various security and privacy risks and prone to several cyberattacks which is a serious challenge. The purpose of this work is to present security and privacy threats towards Fog-IoT platform and discuss the security and privacy requirements in fog computing. We then proceed to propose an Intrusion Detection System (IDS) model using Standard Deep Neural Network's Back Propagation algorithm (BPDNN) to mitigate intrusions that attack Fog-IoT platform. The experimental Dataset for the proposed model is obtained from the Canadian Institute for Cybersecurity 2017 Dataset. Each instance of the attack in the dataset is separated into separate files, which are DoS (Denial of Service), DDoS (Distributed Denial of Service), Web Attack, Brute Force FTP, Brute Force SSH, Heartbleed, Infiltration and Botnet (Bot Network) Attack. The proposed model is trained using a 3-layer BP-DNN

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