Data protection in transactional and statistical applications of databases

2020 ◽  
Vol 0 (10/2019) ◽  
pp. 31-39
Author(s):  
Bolesław Szafrański ◽  
Rafał Bałazy
Keyword(s):  
Access Control ◽  
Flow Control ◽  
Data Protection ◽  
Database System ◽  
Database Management System ◽  
Oracle Database ◽  
Access Control Models ◽  
Control Models ◽  
Transactional Databases ◽  
Protection Mechanisms

The article describes a discussion on the issue of data protection in databases. The discussion attempts to answer the question about the possibility of using a transactional database system as a system capable of data protection in a statistical database. The discussion is preceded by a reminder of the basic issues related to data protection in databases, including reminder of flow control models, access control models and the inference. The key element of the article is the analysis, based on the example of the Oracle database management system, whether data protection mechanisms in transactional databases can be effective in case of data protection in statistical databases.

An Overview on Access Control Models

2015 ◽  
Vol 6 (4) ◽  
pp. 28-38 ◽  
Author(s):  
Mouad Mammass ◽  
Fattehallah Ghadi
Keyword(s):  
Access Control ◽  
Flow Control ◽  
Control Flow ◽  
United States Department ◽  
Security Systems ◽  
Social Challenges ◽  
Access Control Models ◽  
Control Models ◽  
Security Models ◽  
Set Up

Research in the field of information security systems and access control were initiated in the early seventies by United States Department of Defense, following the emergence of new technical, scientific and social challenges. Since, many models of security have been set up to answer to some specific needs with more or less accuracy in term of security. This manuscript gives a survey on the current security models with a specific classification in term of their use: Access Control, Flow Control and Administration. This manuscript is the subject of an assessment of advantages and drawbacks of access control models cited in literature and also the efficiency of their security policies. Finally, a presentation of the contributions of Flow Control and Administration models that allow the reinforcement of the security.

scholarly journals Preserving Privacy in Multimedia Social Networks Using Machine Learning Anomaly Detection

2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Randa Aljably ◽  
Yuan Tian ◽  
Mznah Al-Rodhaan
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Access Control ◽  
Anomaly Detection ◽  
Privacy Preservation ◽  
Support Vector ◽  
Detection Techniques ◽  
Access Control Models ◽  
Control Models ◽  
Multimedia Social Networks

Nowadays, user’s privacy is a critical matter in multimedia social networks. However, traditional machine learning anomaly detection techniques that rely on user’s log files and behavioral patterns are not sufficient to preserve it. Hence, the social network security should have multiple security measures to take into account additional information to protect user’s data. More precisely, access control models could complement machine learning algorithms in the process of privacy preservation. The models could use further information derived from the user’s profiles to detect anomalous users. In this paper, we implement a privacy preservation algorithm that incorporates supervised and unsupervised machine learning anomaly detection techniques with access control models. Due to the rich and fine-grained policies, our control model continuously updates the list of attributes used to classify users. It has been successfully tested on real datasets, with over 95% accuracy using Bayesian classifier, and 95.53% on receiver operating characteristic curve using deep neural networks and long short-term memory recurrent neural network classifiers. Experimental results show that this approach outperforms other detection techniques such as support vector machine, isolation forest, principal component analysis, and Kolmogorov–Smirnov test.

Access Control Models for Online Social Networks

2014 ◽  
pp. 451-484
Author(s):  
Rula Sayaf ◽  
Dave Clarke
Keyword(s):  
Social Networks ◽  
Access Control ◽  
Online Social Networks ◽  
Personal Data ◽  
Security And Privacy ◽  
Open Problems ◽  
Access Control Models ◽  
Control Models ◽  
Underlying Mechanisms ◽  
High Level

Access control is one of the crucial aspects in information systems security. Authorizing access to resources is a fundamental process to limit potential privacy violations and protect users. The nature of personal data in online social networks (OSNs) requires a high-level of security and privacy protection. Recently, OSN-specific access control models (ACMs) have been proposed to address the particular structure, functionality and the underlying privacy issues of OSNs. In this survey chapter, the essential aspects of access control and review the fundamental classical ACMs are introduced. The specific OSNs features and review the main categories of OSN-specific ACMs are highlighted. Within each category, the most prominent ACMs and their underlying mechanisms that contribute enhancing privacy of OSNs are surveyed. Toward the end, more advanced issues of access control in OSNs are discussed. Throughout the discussion, different models and highlight open problems are contrasted. Based on these problems, the chapter is concluded by proposing requirements for future ACMs.

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