This document discusses methods for enhancing data privacy through crypto clustering of heterogeneous and sensitive data. It first reviews existing literature on privacy-preserving techniques like local differential privacy and differential privacy-based clustering. It then proposes a method that uses cryptographic implementations based on sensitivity prediction and local differential privacy to automatically protect mixed data according to type and predicted sensitivity. Sensitive data is clustered and secured using these techniques to enhance privacy while maintaining data utility.
In this work we highlighted some of the concepts of data privacy, techniques used in data privacy, and some techniques used in data privacy in the cloud plus some new research trends.
DATA SCIENCE METHODOLOGY FOR CYBERSECURITY PROJECTS cscpconf
Cybersecurity solutions are traditionally static and signature-based. The traditional solutions
along with the use of analytic models, machine learning and big data could be improved by
automatically trigger mitigation or provide relevant awareness to control or limit consequences
of threats. This kind of intelligent solutions is covered in the context of Data Science for
Cybersecurity. Data Science provides a significant role in cybersecurity by utilising the power
of data (and big data), high-performance computing and data mining (and machine learning) to
protect users against cybercrimes. For this purpose, a successful data science project requires
an effective methodology to cover all issues and provide adequate resources. In this paper, we
are introducing popular data science methodologies and will compare them in accordance with
cybersecurity challenges. A comparison discussion has also delivered to explain methodologies’
strengths and weaknesses in case of cybersecurity projects.
Cluster Based Access Privilege Management Scheme for DatabasesEditor IJMTER
Knowledge discovery is carried out using the data mining techniques. Association rule mining,
classification and clustering operations are carried out under data mining. Clustering method is used to group up the
records based on the relevancy. Distance or similarity measures are used to estimate the transaction relationship.
Census data and medical data are referred as micro data. Data publish schemes are used to provide private data for
analysis. Privacy preservation is used to protect private data values. Anonymity is considered in the privacy
preservation process.
Data values are allowed to authorized users using the access control models. Privacy Protection Mechanism
(PPM) uses suppression and generalization of relational data to anonymize and satisfy privacy needs. Accuracyconstrained privacy-preserving access control framework is used to manage access control in relational database. The
access control policies define selection predicates available to roles while the privacy requirement is to satisfy the kanonymity or l-diversity. Imprecision bound constraint is assigned for each selection predicate. k-anonymous
Partitioning with Imprecision Bounds (k-PIB) is used to estimate accuracy and privacy constraints. Role-based Access
Control (RBAC) allows defining permissions on objects based on roles in an organization. Top Down Selection
Mondrian (TDSM) algorithm is used for query workload-based anonymization. The Top Down Selection Mondrian
(TDSM) algorithm is constructed using greedy heuristics and kd-tree model. Query cuts are selected with minimum
bounds in Top-Down Heuristic 1 algorithm (TDH1). The query bounds are updated as the partitions are added to the
output in Top-Down Heuristic 2 algorithm (TDH2). The cost of reduced precision in the query results is used in TopDown Heuristic 3 algorithm (TDH3). Repartitioning algorithm is used to reduce the total imprecision for the queries.
The privacy preserved access privilege management scheme is enhanced to provide incremental mining
features. Data insert, delete and update operations are connected with the partition management mechanism. Cell level
access control is provided with differential privacy method. Dynamic role management model is integrated with the
access control policy mechanism for query predicates.
A Study on Big Data Privacy Protection Models using Data Masking Methods IJECEIAES
In today’s predictive analytics world, data engineering play a vital role, data acquisition is carried out from various source systems and process as per the business applications and domain. Big Data integrates, governs, and secures big data with repeatable, reliable, and maintainable processes. Through volume, speed, and assortment of information characteristics try to reveal business esteem from enormous information. However, with information that is frequently deficient, conflicting, ungoverned, and unprotected, which is hazardous and enormous information being a risk instead of an advantage. What's more, with conventional methodologies that are manual and unpredictable, huge information ventures take too long to acknowledge business esteem. Reasonably and over and again conveying business esteem from enormous information requires another technique. In this connection, raw data has to be moved between onsite and offshore environment during this course of action, data privacy is a major concern and challenge. A Big Data Privacy platform can make it easier to detect, investigate, assess, and remediate threats from intruders. We tried to do complete study of Big Data Privacy using data masking methods on various data loads and different types. This work will help data quality analyst and big data developers while building the big data applications.
A systematic mapping study of security, trust and privacy in cloudsjournalBEEI
Cloud computing thrives around trust and security in the relationship between cloud providers and users of their services. The objective was the conduct of a systematic mapping study of cloud computing security, trust and privacy. The research was executed using three classes of facets, namely topic, contribution, and research based on the systematic mapping process. The result shows that privacy issues and challenges on metric had 4.76% of the publications. On cloud trust in the domain of tool, the publications were 8.75%. The publications on design within the domain of model stood at 12.38%, and publications on privacy issues and challenges in the area of process were 8.57%. Furthermore, there were more articles published on privacy issues and challenges within the domain of evaluation research with 10.43%. The publications on design based on validation research made up 7.83% of the study. More papers were also published on frameworks and techniques within the domain of solution research with 5.22% each. There were more articles published on privacy issues and challenges with regards to philosophical research with 4.35%. Shortcomings in the fields of security, trust and privacy in the cloud, were identified through this study, which should motivate further research.
Sheet1Country ACountry BProduct 110 Reds9 GreensProduct 22 Reds2.2 GreensProduct 37 Red4 GreenProduct 45 Red5 GreenProduct 54 Red4.5 Green
8/2/2019 Originality Report
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SafeAssign Originality Report
Summer 2019 - Cloud Computing (ITS-532-06) - Second Bi-Term • Week 5 - Assignment • Submitted on Fri, Aug 02, 2019, 8:55 AM
Sai Kumar Baruri View Report Summary
View Originality Report - Old Design
INCLUDED SOURCES
Sources
Institutional database (8) %92
Student paper
Student paper
Student paper
Student paper
Student paper
Student paper
Student paper
Student paper
Top sources
Attachment 1
Week_5_Assignment_Microseg…
%92
4
8
1
5
7
6
2
3
Running head: MICROSEGMENTATION AND ZERO TRUST SECURITY 1
MICROSEGMENTATION AND ZERO TRUST SECURITY 2
Microsegmentation and Zero Trust Security
Week 5 - Assignment
by Sai Kumar Baruri
Professor D. Barrett
University of Cumberland’s
ITS 532 - 06
08/02/2019
Microsegmentation and Zero Trust Security
Introduction
The 21st century is much characterized by increased technology, access to the internet and the adoption of
information systems. Due to the adoption of technologies, there is an increase in the realization of the
benefits that come with IT value. However, technological advancements have negatively affected society
and brought about security threats. This has resulted in the implementation of security mechanisms
that enhance the security of IT assets. Such mechanisms include physical network segmentation, micro-
segmentation and zero-trust security. Physical network segmentation
The physical network segmentation in the cloud includes the segmentation of IT components that are
based on the logic outlines the endpoints to be on each network. The physical network segmentation seeks
to group some of the logical components into specific groups according to their functions and in turn,
access, the privileges assigned (Mammela et al., 2016). The physical network segmentation concerning
cloud computing implies the logical division of the network into minor segments that share the same
access permissions and characteristics. For instance, the cloud computing network is physically segmented
as a private cloud computing. Micro-segmentation
The micro-segmentation comprises of security-enhancing technology that is used in breaking down a given
data Centre which is a cloud-based into logical elements. This facilitates s the implementation of high-level
information technology security policies on the logical elements to aid in their control (Baum & Chang,
2014). The micro-segmentation in cloud computing seeks to break down the applications and the
various network segments into workloads. This implies that the communication and access of applications
are restricted according to the IT policies definition to build on security. Moreover.
In this work we highlighted some of the concepts of data privacy, techniques used in data privacy, and some techniques used in data privacy in the cloud plus some new research trends.
DATA SCIENCE METHODOLOGY FOR CYBERSECURITY PROJECTS cscpconf
Cybersecurity solutions are traditionally static and signature-based. The traditional solutions
along with the use of analytic models, machine learning and big data could be improved by
automatically trigger mitigation or provide relevant awareness to control or limit consequences
of threats. This kind of intelligent solutions is covered in the context of Data Science for
Cybersecurity. Data Science provides a significant role in cybersecurity by utilising the power
of data (and big data), high-performance computing and data mining (and machine learning) to
protect users against cybercrimes. For this purpose, a successful data science project requires
an effective methodology to cover all issues and provide adequate resources. In this paper, we
are introducing popular data science methodologies and will compare them in accordance with
cybersecurity challenges. A comparison discussion has also delivered to explain methodologies’
strengths and weaknesses in case of cybersecurity projects.
Cluster Based Access Privilege Management Scheme for DatabasesEditor IJMTER
Knowledge discovery is carried out using the data mining techniques. Association rule mining,
classification and clustering operations are carried out under data mining. Clustering method is used to group up the
records based on the relevancy. Distance or similarity measures are used to estimate the transaction relationship.
Census data and medical data are referred as micro data. Data publish schemes are used to provide private data for
analysis. Privacy preservation is used to protect private data values. Anonymity is considered in the privacy
preservation process.
Data values are allowed to authorized users using the access control models. Privacy Protection Mechanism
(PPM) uses suppression and generalization of relational data to anonymize and satisfy privacy needs. Accuracyconstrained privacy-preserving access control framework is used to manage access control in relational database. The
access control policies define selection predicates available to roles while the privacy requirement is to satisfy the kanonymity or l-diversity. Imprecision bound constraint is assigned for each selection predicate. k-anonymous
Partitioning with Imprecision Bounds (k-PIB) is used to estimate accuracy and privacy constraints. Role-based Access
Control (RBAC) allows defining permissions on objects based on roles in an organization. Top Down Selection
Mondrian (TDSM) algorithm is used for query workload-based anonymization. The Top Down Selection Mondrian
(TDSM) algorithm is constructed using greedy heuristics and kd-tree model. Query cuts are selected with minimum
bounds in Top-Down Heuristic 1 algorithm (TDH1). The query bounds are updated as the partitions are added to the
output in Top-Down Heuristic 2 algorithm (TDH2). The cost of reduced precision in the query results is used in TopDown Heuristic 3 algorithm (TDH3). Repartitioning algorithm is used to reduce the total imprecision for the queries.
The privacy preserved access privilege management scheme is enhanced to provide incremental mining
features. Data insert, delete and update operations are connected with the partition management mechanism. Cell level
access control is provided with differential privacy method. Dynamic role management model is integrated with the
access control policy mechanism for query predicates.
A Study on Big Data Privacy Protection Models using Data Masking Methods IJECEIAES
In today’s predictive analytics world, data engineering play a vital role, data acquisition is carried out from various source systems and process as per the business applications and domain. Big Data integrates, governs, and secures big data with repeatable, reliable, and maintainable processes. Through volume, speed, and assortment of information characteristics try to reveal business esteem from enormous information. However, with information that is frequently deficient, conflicting, ungoverned, and unprotected, which is hazardous and enormous information being a risk instead of an advantage. What's more, with conventional methodologies that are manual and unpredictable, huge information ventures take too long to acknowledge business esteem. Reasonably and over and again conveying business esteem from enormous information requires another technique. In this connection, raw data has to be moved between onsite and offshore environment during this course of action, data privacy is a major concern and challenge. A Big Data Privacy platform can make it easier to detect, investigate, assess, and remediate threats from intruders. We tried to do complete study of Big Data Privacy using data masking methods on various data loads and different types. This work will help data quality analyst and big data developers while building the big data applications.
A systematic mapping study of security, trust and privacy in cloudsjournalBEEI
Cloud computing thrives around trust and security in the relationship between cloud providers and users of their services. The objective was the conduct of a systematic mapping study of cloud computing security, trust and privacy. The research was executed using three classes of facets, namely topic, contribution, and research based on the systematic mapping process. The result shows that privacy issues and challenges on metric had 4.76% of the publications. On cloud trust in the domain of tool, the publications were 8.75%. The publications on design within the domain of model stood at 12.38%, and publications on privacy issues and challenges in the area of process were 8.57%. Furthermore, there were more articles published on privacy issues and challenges within the domain of evaluation research with 10.43%. The publications on design based on validation research made up 7.83% of the study. More papers were also published on frameworks and techniques within the domain of solution research with 5.22% each. There were more articles published on privacy issues and challenges with regards to philosophical research with 4.35%. Shortcomings in the fields of security, trust and privacy in the cloud, were identified through this study, which should motivate further research.
Sheet1Country ACountry BProduct 110 Reds9 GreensProduct 22 Reds2.2 GreensProduct 37 Red4 GreenProduct 45 Red5 GreenProduct 54 Red4.5 Green
8/2/2019 Originality Report
https://ucumberlands.blackboard.com/webapps/mdb-sa-BB5a31b16bb2c48/originalityReport/ultra?course_id=_109247_1&includeDeleted=true&attem… 1/2
SafeAssign Originality Report
Summer 2019 - Cloud Computing (ITS-532-06) - Second Bi-Term • Week 5 - Assignment • Submitted on Fri, Aug 02, 2019, 8:55 AM
Sai Kumar Baruri View Report Summary
View Originality Report - Old Design
INCLUDED SOURCES
Sources
Institutional database (8) %92
Student paper
Student paper
Student paper
Student paper
Student paper
Student paper
Student paper
Student paper
Top sources
Attachment 1
Week_5_Assignment_Microseg…
%92
4
8
1
5
7
6
2
3
Running head: MICROSEGMENTATION AND ZERO TRUST SECURITY 1
MICROSEGMENTATION AND ZERO TRUST SECURITY 2
Microsegmentation and Zero Trust Security
Week 5 - Assignment
by Sai Kumar Baruri
Professor D. Barrett
University of Cumberland’s
ITS 532 - 06
08/02/2019
Microsegmentation and Zero Trust Security
Introduction
The 21st century is much characterized by increased technology, access to the internet and the adoption of
information systems. Due to the adoption of technologies, there is an increase in the realization of the
benefits that come with IT value. However, technological advancements have negatively affected society
and brought about security threats. This has resulted in the implementation of security mechanisms
that enhance the security of IT assets. Such mechanisms include physical network segmentation, micro-
segmentation and zero-trust security. Physical network segmentation
The physical network segmentation in the cloud includes the segmentation of IT components that are
based on the logic outlines the endpoints to be on each network. The physical network segmentation seeks
to group some of the logical components into specific groups according to their functions and in turn,
access, the privileges assigned (Mammela et al., 2016). The physical network segmentation concerning
cloud computing implies the logical division of the network into minor segments that share the same
access permissions and characteristics. For instance, the cloud computing network is physically segmented
as a private cloud computing. Micro-segmentation
The micro-segmentation comprises of security-enhancing technology that is used in breaking down a given
data Centre which is a cloud-based into logical elements. This facilitates s the implementation of high-level
information technology security policies on the logical elements to aid in their control (Baum & Chang,
2014). The micro-segmentation in cloud computing seeks to break down the applications and the
various network segments into workloads. This implies that the communication and access of applications
are restricted according to the IT policies definition to build on security. Moreover.
Similar to THE CRYPTO CLUSTERING FOR ENHANCEMENT OF DATA PRIVACY (20)
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
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Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.