Uploaded on Sep 27, 2019
AI promises to booth data access control in cloud computing platforms. Developing a novel algorithm using the ML approach to classify user’s behaviour is significant to bridge the gap among theory and real-time application. The access control and security management framework along with effective ML would provide guidance information for the cloud customers and administrators to make decisions. Read More: http://bit.ly/2mtNbTL Need Help to Select your Research Topics: http://bit.ly/32L7L2q
Secure Access Control Framework for Fully Fledged Network Security Control: How Machine Learning Algorithms Helps to Improve Security 2019
Tutors India Lab
Tutors India Lab
Secure Access Control
Framework for Fully Fledged
Network Security Control
How Machine Learning Algorithms Helps to Improve Security
Tutors India Lab
2 | How Machine Learning Algorithms Helps to Improve Security Engineering and Technology
Tutors India Lab
EXEXEECCUTTIVIEVE
SU SMUMMMAARRYRY
1 AI promises to booth data access control
incloud computing platforms.
2 Developing a novel algorithm using the ML
approach to classify user’s behaviour is
significant to bridge the gap among
theory and real-time application.
3 The access control and security manage
ment framework along with effective ML
would provide guidance information for
the cloud customers and administrators
to make decisions.
3 | How Machine Learning Algorithms Helps to Improve Security Engineering and Technology
Tutors India Lab
INTRINOTRODDUCTIOTNION
At the present scenario, the cloud environment widely used in numerous fields, namely, web applications,
healthcare, mobile social networks, e-commerce, data storage, gaming, and so on. Thus the huge collection of
data becomes complex in terms of data access control and authentication in the distributed environment.
Especially, the data access control is not fine-grained, and this may result in data leakage and other security
threats. So apart from the traditional security, there is a special focus
required in the field of data access control in cloud computing platforms.
4 | How Machine Learning Algorithms Helps to Improve Security Engineering and Technology
Tutors India Lab
BREIF NOTE OF CLOUD ACCESS
CONTROL SYSTEM
Generally, the term data access cess control system is restricting control system has its methods
control system defines the huge a user to exactly what they should and functions, own
collection of components and be able to do and how can protect attributes, that derive from
techniques which define the ap- data from unauthorized access. either set of policies or policy.
propriate administrator to activate There is a wide variety of models, The systematic representation
valid user on the basis of privileges administrative capabilities, meth- of cloud access control with
outlined and preconfigured access ods and technologies are utilized a service provider is shown
permissions in the access security toward design and propose ac- below.
policy. The primary aim of any ac- cess control systems. Each access
Apart from this, one of the primary issues which we are facing is accuracy while we access the data in
terms of detecting user behaviour. For addressing this issue, there is a potential extension by considering
multi-authority access control which aggregates data from different resources to profile the user’s be-
haviour. Developing a novel algorithm using a machine learning approach to classify user’s behaviour is
significant to bridge the gap among theory and real-time application.
5 | How Machine Learning Algorithms Helps to Improve Security Engineering and Technology
Tutors India Lab
The novel algorithm should consider the below factors in order to develop a secure access
control system:
1 Should consider different flexible functionalities like self-managed and self-defined
access control, user-friendly deletion and addition of group users, separation of access
authentication from system authentication and iterative access control proxy server.
2 Reduce the computational complexity which comprises both encryption and
decryption algorithms.
3 Multi-authority Access Control and Fine-Grained Data Access Control scheme for
supporting dynamic behaviours of users over the cloud platform.
4 To enhance the complexity by fast decryption technique and outsourcing the pairing
computations to the cloud by adding dynamic attributes.
SUMMARY
The access control and security management
framework along with effective machine learning
would provide guidance information for the cloud
customers and administrators to make decisions,
for instance,migrating tasks from dynamically
allocating resources, suspect nodes to trustworthy
nodes and managing the trade-off among the cost of
resources and degree of redundancy.
6 | How Machine Learning Algorithms Helps to Improve Security Engineering and Technology
Tutors India Lab
REFERENCES ABOUT THE DEPARTMENT
[1] A. Younis, Y., Kifayat, K., & Merabti, M. (2014).
An access control model for cloud Engineering and Technology Lab at Tutors India is involved
computing. Journal of Information Security and in exploring novel research areas for the challenges faced
Applications, 19(1), 45–60. https://doi.org/10.1016/j. by today’s technology-oriented business or organisation, the
jisa.2014.04.003 market, the economy, finance and sales. The research team
explores and identifies troubling questions that exist in schol-
[2] Anderson, R. (2010). ” Security Engineering – A arly literature, in theory, or in practices that needs deliberate
Guide to Building Dependable Distributed Systems , investigation.
2nd edition ” by Ross Anderson John Wiley & Sons
2008 What the book is about.
[3] Stobert, E., & Biddle, R.(n.d.). The Password Life
Cycle : User Behaviour in Managing Passwords,
243–255.
[4] Sasse, M. A., Brostoff, S., & Weirich, D. (n.d.).
Transforming the ‘Weakest Link’ — a Human/Com
puter Interaction Approach to Usable and Effective ABOUT US
Se, 4–6.
[5] Li, F., Rahulamathavan, Y., Conti, M., & Rajarajan,
M. (2015). Robust access control framework for Tutors India, is world’s reputed academic guidance provider for
mobile cloud computing network. Computer have guided more than 4,500 Ph.D. scholars and 10,500 Masters
Communications, 68, 61–72. https://doi.org/10.1016/j. Students across the globe. We support students, research scholars,
comcom.2015.07.005 entrepreneurs, and professionals from various organizations in pro-viding consistently high-quality writing and data analytical services
every time. We value every client and make sure their requirements
[6] Ren, W., Liu, R., Lei, M., & Choo, K.-K. R. (2017). are identified and understood by our specialized professionals and
SeGoAC: A tree-based model for self-defined, analysts, enriched in experience to deliver technically sound output
proxy-enabled and group-oriented access con within the requested timeframe. Writers at Tutors India are best
trol in mobile cloud computing. Computer Stan referred as ‘Researchers’ since every topic they handle unique and
dards & Interfaces, 54, 29–35. https://doi. challenging. We specialize in handling text and data, i.e., content
org/10.1016/j.csi.2016.09.001 development and Statistical analysis where the latest statistical ap-plications are exhausted by our expert analysts for determining the
outcome of the data analysed. Qualified and experienced research-
[7] Ruan, Y., & Durresi, A. (2019). A trust management ers including Ph.D. holders, statisticians, and research analysts
framework for clouds. Computer Communica offer cutting edge research consulting and writing services to meet
tions, 144, 124–131. https://doi.org/10.1016/j.com your business information or academic project requirement. Our
com.2019.05.018 expertise has passion towards research and personal assistance as
we work closely with you for a very professional and quality output
[8] Thota, C., Sundarasekar, R., Manogaran, G., R, V., & within your stipulated time frame. Our services cover vast areas, and we also support either part or entire research paper/service as
M. K., P. (2018). Centralized Fog Computing Security per your requirement at competitive prices.
Platform for IoT and Cloud in Healthcare System
(pp. 141–154). https://doi.org/10.4018/978-1-5225-
2947-7.ch011
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