scholarly journals Class Based Multi Stage Encryption for Efficient Data Security in Cloud Environment Using Profile Data

2019 ◽  
Vol 1 (1) ◽  
pp. 22-29
Author(s):  
Mouleeswaran S.K. ◽  
Kanya Devi J ◽  
Illayaraja
Keyword(s):  
Data Security ◽  
User Profile ◽  
Security Measures ◽  
Profile Data ◽  
Security Issues ◽  
Multi Stage ◽  
Data Owner ◽  
Efficient Data ◽  
Number Of Classes ◽  
Different Levels

The security issues in the cloud have been well studied. The data security has much importance in point of data owner. There are number of approaches presented earlier towards performance in data security in cloud. To overcome the issues, a class based multi stage encryption algorithm is presented in this paper. The method classifies the data into number of classes and different encryption scheme is used for different classes in different levels. Similarly, the user has been authenticated for their access and they have been classified into different categories. According to the user profile, the method restricts the access of user and based on the same, the method defines security measures. A system defined encryption methodology is used for encrypting the data. Moreover, the user has been returned with other encryption methods which can be decrypted by the user using their own key provided by the system. The proposed algorithm improves the performance of security and improves the data security.

Data Security for Connected Governments and Organisations

2021 ◽  
pp. 229-251
Author(s):  
Heru Susanto ◽  
Leu Fang Yie ◽  
Didi Rosiyadi ◽  
Akbari Indra Basuki ◽  
Desi Setiana
Keyword(s):  
Artificial Intelligence ◽  
Early Warning ◽  
Data Security ◽  
Data Privacy ◽  
Government Agencies ◽  
Security Measures ◽  
Security Issues ◽  
The Impact ◽  
Distributed Technologies

Digital ecosystems have grown rapidly over the years, and governments are investing in digital provision for their processes and services. Despite the advantages of distributed technologies, there are many security issues as well that result in breaches of data privacy with serious impact including legal and reputational implications. To deal with such threats, government agencies need to thoughtfully improve their security defences to protect data and systems by using automation and artificial intelligence (AI), as well as easing the data security measures including early warning of threats and detection. This study provides a comprehensive view of AI and automaton to highlight challenges and issues concerning data security and suggests steps to combat the issues. The authors demonstrate the role of AI-driven security tools and automation to mitigate the impact of data breaches to also propose recommendations for government agencies to enhance their data security protection.

G-Profile

2012 ◽  
Vol 25 (3) ◽  
pp. 61-77 ◽  
Author(s):  
Marco Viviani ◽  
Nadia Bennani ◽  
Elöd Egyed-Zsigmond
Keyword(s):  
Data Security ◽  
Identity Management ◽  
User Profile ◽  
General Purpose ◽  
Security Issues ◽  
Digital World ◽  
Identity Management Systems ◽  
Account Information ◽  
User Centric ◽  
Digital Identities

In the digital world, many organizations are developing different applications (with different purposes) where users are generally represented by a heterogeneous set of attributes. From time to time, depending on the context, different attributes can provide different digital identities for the same user, often involved in the identification/authentication processes. In the personalized service provision perspective, the scope of identity management becomes much larger, and takes into account information susceptible to change such as user profile information as a whole. Many purely user-centric identity management systems has emerged in the few last years, among them the Higgins project that provides the user with a direct control over his/her data and covers some data security issues. However, a complete user-centric view of extended user identity management is not realistic, in our opinion. In this paper, the authors present G-Profile: a hybrid, open, general-purpose and flexible user modeling system for extended identity management in multi-application environments. G-Profile also tackles the trade-off between users’ and applications’ requirements.

Data Security for Connected Governments and Organisations

2022 ◽  
pp. 191-213
Author(s):  
Heru Susanto ◽  
Leu Fang Yie ◽  
Didi Rosiyadi ◽  
Akbari Indra Basuki ◽  
Desi Setiana
Keyword(s):  
Artificial Intelligence ◽  
Early Warning ◽  
Data Security ◽  
Data Privacy ◽  
Government Agencies ◽  
Security Measures ◽  
Security Issues ◽  
The Impact ◽  
Distributed Technologies

Digital ecosystems have grown rapidly over the years, and governments are investing in digital provision for their processes and services. Despite the advantages of distributed technologies, there are many security issues as well that result in breaches of data privacy with serious impact including legal and reputational implications. To deal with such threats, government agencies need to thoughtfully improve their security defences to protect data and systems by using automation and artificial intelligence (AI), as well as easing the data security measures including early warning of threats and detection. This study provides a comprehensive view of AI and automaton to highlight challenges and issues concerning data security and suggests steps to combat the issues. The authors demonstrate the role of AI-driven security tools and automation to mitigate the impact of data breaches to also propose recommendations for government agencies to enhance their data security protection.

scholarly journals Real Time Class Based Encryption for Efficient Data Security in Cloud Environment using User Profile

2019 ◽  
Vol 8 (12) ◽  
pp. 1494-1499
Keyword(s):  
Data Security ◽  
Time Window ◽  
User Profile ◽  
Cloud Environment ◽  
Cloud Data ◽  
Time Class ◽  
Efficient Data ◽  
Performance Results ◽  
Network Overhead ◽  
Selection Of

The data security in cloud has been well studied towards the data present in the cloud environment. Number of techniques has been discussed earlier and each produces different performance results in data security. But still there are gaps in performance in security which should be optimized. To improve the security performance, an efficient class based encryption (CBE) with User profile (UP) is presented. The proposed CBE-UP method groups the cloud data at attribute level based on the importance mentioned in the taxonomy. The data taxonomy covers various information related to the attribute of any data point like their sensitivity, importance in different class and so on. According to the taxonomy, the method estimates the Class Sensitivity Measure (CSM) for each attribute, which has been used to classify the data attribute. Further, for each Attribute class, the method generates different key from the key set and assigns various scheme to perform encryption and decryption. The selection of key and method has been iterated at each time window. The performance of data security has been improved and reduces the network overhead in distribution of keys to the registered users.

A security study in Portuguese Public Hospitals - GDPR perspective (Preprint)

2020 ◽  
Author(s):  
Cátia Santos-Pereira
Keyword(s):  
Information Systems ◽  
Identity Management ◽  
Personal Data ◽  
Public Hospitals ◽  
Hospital Environment ◽  
Security Measures ◽  
Eu Member States ◽  
Security Issues ◽  
Management Processes ◽  
Authentication Security

BACKGROUND GDPR was scheduled to be formally adopted in 2016 with EU member states being given two years to implement it (May 2018). Given the sensitive nature of the personal data that healthcare organization process on a 24/7 basis, it is critical that the protection of that data in a hospital environment is given the high priority that data protection legislation (GDPR) requires. OBJECTIVE This study addresses the state of Public Portuguese hospitals regarding GDPR compliance in the moment of GDPR preparation period (2016-2018) before the enforcement in 25 May 2018, and what activities have started since then. The study focuses in three GDPR articles namely 5, 25 and 32, concerning authentication security, identity management processes and audit trail themes. METHODS The study was conducted between 2017 and 2019 in five Portuguese Public Hospitals (each different in complexity). In each hospital, six categories of information systems critical to health institutions were included in the study, trying to cover the main health information systems available and common to hospitals (ADT, EPR, PMS, RIS, LIS and DSS). It was conducted interviews in two phases (before and after GDPR enforcement) with the objective to identify the maturity of information systems of each hospital regarding authentication security, identity management processes and traceability and efforts in progress to avoid security issues. RESULTS A total of 5 hospitals were included in this study and the results of this study highlight the hospitals privacy maturity, in general, the hospitals studied where very far from complying with the security measures selected (before May 2018). Session account lock and password history policy were the poorest issues, and, on the other hand, store encrypted passwords was the best issue. With the enforcement of GDPR these hospitals started a set of initiatives to fill this gap, this is made specifically for means of making the whole process as transparent and trustworthy as possible and trying to avoid the huge fines. CONCLUSIONS We are still very far from having GDPR compliant systems and Institutions efforts are being done. The first step to align an organization with GDPR should be an initial audit of all system. This work collaborates with the initial security audit of the hospitals that belong to this study.

scholarly journals User profile correlation-based similarity (UPCSim) algorithm in movie recommendation system

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Triyanna Widiyaningtyas ◽  
Indriana Hidayah ◽  
Teguh B. Adji
Keyword(s):  
Collaborative Filtering ◽  
Recommendation System ◽  
User Behavior ◽  
Correlation Coefficients ◽  
User Profile ◽  
Profile Data ◽  
Similarity Algorithm ◽  
Previous Algorithm ◽  
Movie Recommendation ◽  
Recommendation Accuracy

AbstractCollaborative filtering is one of the most widely used recommendation system approaches. One issue in collaborative filtering is how to use a similarity algorithm to increase the accuracy of the recommendation system. Most recently, a similarity algorithm that combines the user rating value and the user behavior value has been proposed. The user behavior value is obtained from the user score probability in assessing the genre data. The problem with the algorithm is it only considers genre data for capturing user behavior value. Therefore, this study proposes a new similarity algorithm – so-called User Profile Correlation-based Similarity (UPCSim) – that examines the genre data and the user profile data, namely age, gender, occupation, and location. All the user profile data are used to find the weights of the similarities of user rating value and user behavior value. The weights of both similarities are obtained by calculating the correlation coefficients between the user profile data and the user rating or behavior values. An experiment shows that the UPCSim algorithm outperforms the previous algorithm on recommendation accuracy, reducing MAE by 1.64% and RMSE by 1.4%.

Provably Secure Authentication Approach for Data Security in Cloud Using Hashing, Encryption, and Chebyshev-Based Authentication

2022 ◽  
Vol 16 (1) ◽  
pp. 0-0
Keyword(s):  
Data Security ◽  
Security Analysis ◽  
Data Communication ◽  
Computation Time ◽  
Computational Time ◽  
Security Issues ◽  
Authentication Mechanism ◽  
Cloud Server ◽  
Secure Authentication ◽  
Provably Secure

Secure and efficient authentication mechanism becomes a major concern in cloud computing due to the data sharing among cloud server and user through internet. This paper proposed an efficient Hashing, Encryption and Chebyshev HEC-based authentication in order to provide security among data communication. With the formal and the informal security analysis, it has been demonstrated that the proposed HEC-based authentication approach provides data security more efficiently in cloud. The proposed approach amplifies the security issues and ensures the privacy and data security to the cloud user. Moreover, the proposed HEC-based authentication approach makes the system more robust and secured and has been verified with multiple scenarios. However, the proposed authentication approach requires less computational time and memory than the existing authentication techniques. The performance revealed by the proposed HEC-based authentication approach is measured in terms of computation time and memory as 26ms, and 1878bytes for 100Kb data size, respectively.

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