Cloud Cryptography for Cloud Data Analytics in IoT
N. Jayashri
Department of Computer Applications, Dr. M.G.R. Educational and Research Institute, Chennai, Tamilnadu, India
Search for more papers by this authorK. Kalaiselvi
Department of Computer Applications, School of Computing Sciences, Vels Institute of Science, Technology and Advanced Studies (Formerly Vels University), Chennai, Tamil Nadu, India
Search for more papers by this authorN. Jayashri
Department of Computer Applications, Dr. M.G.R. Educational and Research Institute, Chennai, Tamilnadu, India
Search for more papers by this authorK. Kalaiselvi
Department of Computer Applications, School of Computing Sciences, Vels Institute of Science, Technology and Advanced Studies (Formerly Vels University), Chennai, Tamil Nadu, India
Search for more papers by this authorSachi Nandan Mohanty
Search for more papers by this authorJyotir Moy Chatterjee
Search for more papers by this authorMonika Mangla
Search for more papers by this authorSuneeta Satpathy
Search for more papers by this authorSirisha Potluri
Search for more papers by this authorInstitutional Login
Log in to Wiley Online Library
If you have previously obtained access with your personal account, please log in.
Purchase single chapter
-
Details
- View the article/chapter PDF and any associated supplements and figures for a period of 48 hours.
- Article/Chapter can not be printed.
- Article/Chapter can not be downloaded.
- Article/Chapter can not be redistributed.
-
Details
- Unlimited viewing of the article/chapter PDF and any associated supplements and figures.
- Article/Chapter can not be printed.
- Article/Chapter can not be downloaded.
- Article/Chapter can not be redistributed.
-
Details
- Unlimited viewing of the article/chapter PDF and any associated supplements and figures.
- Article/chapter can be printed.
- Article/chapter can be downloaded.
- Article/chapter can not be redistributed.
Summary
The potential Internet of Things (IoT) will have a profoundly prudent business and social impact on our lives. A hub of interest in IoT systems is typically an asset obligation, which makes them focus on digital assault baiting. In this way, broad attempts have been devoted to identifying security and safety difficulties in trendy IoT, primarily through conventional cryptographic methodologies. In any case, the remarkable qualities of IoT hubs make it the main objective of the association and collaboration between objects and objects sent through remote systems to satisfy the target set for them as a united element, to achieve a superior domain for the use of big data. What is more, based on the creativity of remote systems, both platforms and IoT may grow quickly and together. In this section, it methodically audits the security needs, the assault vectors, and the current security responses for IoT systems. It also addresses insights into current machine learning solutions for solving various security issues in IoT systems and a few future cryptography cloud analysis headlines.
References
- Security Guidance for Critical Areas of Focus in Cloud Computing V3.0 , 177 pp, 2011 ( http://www.cloudsecurityalliance.org/guidance/csaguide.pdf ).
- Information Assurance Technology Analysis Center (IATAC) , Information Assurance Technology Analysis Center Falls Church VA. July 31, 2007.
- Komaroff , M. and Baldwin , K. , DoD Software Assurance Initiative . Software security assurance: A state-of-art report (sar). Information Assurance Technology Analysis Center (IATAC) Herndon VA. September 13, 2005 , ( https://acc.dau.mil/CommunityBrowser.aspx?id=25749 ).
- Goertzel , K. , Winograd , T. et al., Enhancing the Development Life Cycle to Produce Secure Software, Draft Version 2.0, United States Department of Defense Data and Analysis Center for Software , Rome, New York, July 2008 .
- Saltzer , J.H. and Schroeder , M.D. , The Protection of Information in Computer Systems . Fourth ACM Symposium on Operating Systems Principles , October 1974 .
-
Davis , J. F.
,
Information systems security engineering: A critical component of the systems engineering lifecycle
.
ACM SIGAda Ada Letters
,
24
,
4
,
13
–
18
,
2004
.
10.1145/1046191.1032300 Google Scholar
- Goertzel , K. , Winograd , T. et al., Enhancing the development life cycle to produce secure software , vol. 1, pp. i-iv, U.S. Department of Defense, 2008 .
- van Lamsweerde , A. , Brohez , S. , De Landtsheer , R. , Janssens , D. , From System Goals to Intruder Anti-Goals: Attack Generation and Resolution for Security Requirements Engineering , in: Proceedings of the Requirements for High Assurance Workshop , Monterey Bay, CA , September 8, 2003 , pp. 49 – 56 .
- American Institute of Certified Public Accountants (AICPA), Accounting for the Costs of Computer Software Developed or Obtained for Internal Use, AICPA Statement of Position (SOP) No. 98–1, The Evolution of Computer Software on Business Practices and Standards . Academy of Legal, Ethical and Regulatory Issues, 19., March 1998, www.aicpa.org .
- ISACA , IS Auditing Guideline on Due Professional Care , Information Systems Audit and Control Association, March 1, 2008, Mangla, M., Akhare, R., Ambarkar, S., Context-Aware Automation Based Energy Conservation Techniques for IoT Ecosystem, in: Energy Conservation for IoT Devices , pp. 129–153, Springer, Singapore, 2019.
-
Akhare , R.
,
Mangla , M.
,
Deokar , S.
,
Wadhwa , V.
,
Proposed Framework for Fog Computing to Improve Quality-of-Service in IoT Applications
, in:
Fog Data Analytics for IoT Applications
, pp. 123–143, Springer, Singapore,
2020
.
10.1007/978-981-15-6044-6_7 Google Scholar
- Deokar , S. , Mangla , M. , Akhare , R. , A Secure Fog Computing Architecture for Continuous Health Monitoring , in: Fog Computing for Healthcare 4.0 Environments , pp. 269–290, Springer, Cham., 2021 .
- Potluri , S. , Quality of Service based Task Scheduling Algorithms in Cloud Computing . Int. J. Electr. Comput. Eng. , 7 , 2 , 1088 – 1095 , April 2017 .
- Potluri , S. , Efficient Hybrid QoS Driven Task Scheduling Algorithm in Cloud Computing Using a Toolkit: Clouds . JARDCS , 12-Special Issue, 1270–1283, 2017 .
-
Potluri , S.
,
A study on technologies in cloud-based design and manufacturing
.
IJMPERD
,
8
,
6
,
187
–
192
,
2018
.
10.24247/ijmperddec201822 Google Scholar
- Potluri , S. , Software virtualization using containers in google cloud platform . IJITEE , 8 , 7 , 2430 – 2432 , May 2019 .
- Potluri , S. , Simulation of QoS-Based Task Scheduling Policy for Dependent and Independent Tasks in a Cloud Environment, in : Smart Intelligent Computing and Applications , vol. 159 , pp. 515 – 525 , May 2019 .
- Potluri , S. , Quality of Service-Based Cloud Models in Manufacturing Process Automation, in: Lecture Notes in Networks and Systems , vol. 32 , pp. 231 – 240 , 2019 .
-
Potluri , S.
,
Optimization model for QoS based task scheduling in cloud computing environment
.
IJEECS
,
18
,
2
,
1081
–
1088
,
2020
.
10.11591/ijeecs.v18.i2.pp1081-1088 Google Scholar
- Potluri , S. , IOT Enabled Cloud Based Healthcare System Using Fog Computing: A Case Study . J. Crit. Rev. , 7 , 6 , 1068 – 1072 , 2020 .
- Potluri , S. , Improved quality of service-based cloud service ranking and recommendation model . TELKOMNIKA Telecommun. Comput. Electron. Control , 18 , 3, 1252–1258, June 2020, accredited First Grade by Kemenristekdikti, Decree No: 21/E/KPT/2018.
- Potluri , S. , A Hybrid PSO Based Task Selection and Recommended System for Cloud Data . Test Eng. Manage. , 83 , 10210 – 10217 , March-April 2020 .
- Potluri , S. , A Hybrid Self-Adaptive PSO and QoS Based Machine Learning Model for Cloud Service Data . Test Eng. Manage. , 83 , 23736 – 23748 , May-June 2020 .
-
Le , D.N.
,
Kumar , R.
,
Nguyen , G.N.
,
Chatterjee , J.M.
,
Cloud computing and virtualization
,
John Wiley & Sons
,
India
,
2018
.
10.1002/9781119488149 Google Scholar
- Jha , S. , Kumar , R. , Chatterjee , J.M. , Khari , M. , Collaborative handshaking approaches between internet of computing and internet of things towards a smart world: a review from 2009–2017 . Telecommun. Syst. , 70 , 4 , 617 – 634 , 2019 .
- Chatterjee , J.M. , Kumar , R. , Khari , M. , Hung , D.T. , Le , D.N. , Internet of Things based system for Smart Kitchen. Int. J. Eng. Manuf. , 8, 4, 29, 2018 .
- Sujath , R. , Chatterjee , J.M. , Hassanien , A.E. , A machine learning forecasting model for COVID-19 pandemic in India . Stochastic Environ. Res. Risk Assess. , 1 , 34 , 2020 .
- Chatterjee , J. , IoT with Big Data Framework using Machine Learning Approach . Int. J. Mach. Learn. Networked Collab. Eng. , 2 , 02 , 75 – 85 , 2018 .
- Moy Chatterjee , J. , Fog computing: beginning of a new era in cloud computing . Int. Res. J. Eng. Technol. (IRJET) , 4, 05, 735, 2017 .
- Iwendi , C. , Bashir , A.K. , Peshkar , A. , Sujatha , R. , Chatterjee , J.M. , Pasupuleti , S. , Jo , O. , COVID-19 Patient Health Prediction Using Boosted Random Forest Algorithm . Front. Public Health , 8 , 357 , 2020 .
-
Kumar , A.
,
Chatterjee , J.M.
,
Díaz , V.G.
,
A novel hybrid approach of SVM combined with NLP and probabilistic neural network for email phishing
.
Int. J. Electr. Comput. Eng.
,
10
, 1, 486,
2020
.
10.4018/978-1-7998-2803-7 Google Scholar
-
Chatterjee , J.M.
,
Priyadarshini , I.
,
Le , D.N.
,
Fog Computing and Its security issues
, in:
Security Designs for the Cloud, Iot, and Social Networking
, pp. 59–76,
2019
.
10.1002/9781119593171.ch4 Google Scholar
- Choudhuri , A. , Chatterjee , J.M. , Garg , S. , Internet of Things in Healthcare: A Brief Overview , in: Internet of Things in Biomedical Engineering , pp. 131–160, Academic Press, India, 2019 .
- Chatterjee , J.M. , Bioinformatics Using Machine Learning . Global J. Internet Interv. Fusion , 1 , 1 , 28 – 35 , 2018 .
- Shri , M.L. , Devi , E.G. , Balusamy , B. , Chatterjee , J.M. , Ontology-Based Information Retrieval and Matching in IoT Applications , in: Natural Language Processing in Artificial Intelligence , pp. 113–130, Apple Academic Press, India, 13, 4, 2020 .
- Radhakrishnan , S. , Lakshminarayanan , A.S. , Chatterjee , J.M. , Hemanth , D.J. , Forest data visualization and land mapping using support vector machines and decision trees . Earth Sci. Inf. , 1–19 , 2020 .
-
V. Jain
and
J.M. Chatterjee
(Eds.),
Machine Learning with Health Care Perspective: Machine Learning and Healthcare
, vol.
13
,
Springer Nature
,
India
,
2020
.
10.1007/978-3-030-40850-3 Google Scholar
- Chatterjee , J.M. , COVID-19 Mortality Prediction for India using Statistical Neural Network Models . Front. Public Health , 8 , 441 , 2020 .
-
Kumar , A.
,
Payal , M.
,
Dixit , P.
,
Chatterjee , J.M.
,
Framework for Realization of Green Smart Cities Through the Internet of Things (IoT)
, in:
Trends in Cloud-based IoT
, pp. 85–111, Springer, Cham,
2020
.
10.1007/978-3-030-40037-8_6 Google Scholar
- Sujatha , R. , Nathiya , S. , Chatterjee , J.M. , Clinical Data Analysis Using IoT Data Analytics Platforms , in: Internet of Things Use Cases for the Healthcare Industry , pp. 271–293, Springer, Cham, 2020 .
Citing Literature
Recommended
Details
© 2021 Scrivener Publishing LLC
Keywords
Publication History
- 03 August 2021
- 13 July 2021
ISBN Information
- Online ISBN: 9781119785873
- Print ISBN: 9781119785804
