Multiranges and Multitrackers in Statistical Databases

1988 ◽  
Vol 11 (1) ◽  
pp. 41-48
Author(s):  
Zbigniew Michalewicz ◽  
Anthony Yeo
Keyword(s):  
Control Mechanism ◽  
Sensitive Data ◽  
Inference Problem ◽  
Inference Control ◽  
Statistical Databases ◽  
Set Size ◽  
Confidential Data

The goal of statistical databases is to provide statistics about groups of individuals while protecting their privacy. Sometimes. by correlating enough statistics, sensitive data about individual can be inferred. The problem of protecting against such indirect disclosures of confidential data is called the inference problem and a protecting mechanism – an inference control. A good inference control mechanism should be effective (it should provide security to a reasonable extent) and feasible (a practical way exists to enforce it). At the same time it should retain the richness of the information revealed to the users. During the last few years several techniques were developed for controlling inferences. One of the earliest inference controls for statistical databases restricts the responses computed over too small or too large query-sets. However, this technique is easily subverted. In this paper we propose a new query-set size inference control which is based on the idea of multiranges and has better performance then the original one.

scholarly journals Coupling of Inference and Access Controls to Ensure Privacy Protection

2021 ◽  
Vol 11 (5) ◽  
pp. 529-535
Author(s):  
Jihane El Mokhtari ◽  
Anas Abou El Kalam ◽  
Siham Benhaddou ◽  
Jean-Philippe Leroy
Keyword(s):  
Access Control ◽  
Privacy Protection ◽  
Multidimensional Analysis ◽  
Sensitive Data ◽  
Inference Control ◽  
External Data ◽  
Control Rules ◽  
Access Controls ◽  
Policy Information ◽  
History Of

This article is devoted to the topic of coupling access and inference controls into security policies. The coupling of these two mechanisms is necessary to strengthen the protection of the privacy of complex systems users. Although the PrivOrBAC access control model covers several privacy protection requirements, the risk of inferring sensitive data may exist. Indeed, the accumulation of several pieces of data to which access is authorized can create an inference. This work proposes an inference control mechanism implemented through multidimensional analysis. This analysis will take into account several elements such as the history of access to the data that may create an inference, as well as their influence on the inference. The idea is that this mechanism delivers metrics that reflect the level of risk. These measures will be considered in the access control rules and will participate in the refusal or authorization decision with or without obligation. This is how the coupling of access and inference controls will be applied. The implementation of this coupling will be done via the multidimensional OLAP databases which will be requested by the Policy Information Point, the gateway brick of XACML to the various external data sources, which will route the inference measurements to the decision-making point.

Editorial: TRENDS IN AGGREGATION AND SECURITY ASSESSMENT FOR INFERENCE CONTROL IN STATISTICAL DATABASES

2002 ◽  
Vol 10 (05) ◽  
pp. 453-457 ◽  
Author(s):  
VICENÇ TORRA ◽  
JOSEP DOMINGO-FERRER
Keyword(s):  
Artificial Intelligence ◽  
Soft Computing ◽  
Data Handling ◽  
Security Assessment ◽  
Special Issue ◽  
Inference Control ◽  
Artificial Intelligence Techniques ◽  
Statistical Databases ◽  
Statistical Agencies ◽  
The Individual

As e-commerce and Internet-based data handling become pervasive, companies and statistical agencies have the need to exploit the data they accumulate without violating citizens' privacy. Inference control is a discipline whose goal is to prevent published/exchanged data from being linked with the individual respondents they originated from. This special issue illustrates that inference control largely draws on soft computing and artificial intelligence techniques.

scholarly journals Hide text depending on the three channels of pixels in color images using the modified LSB algorithm

2020 ◽  
Vol 10 (1) ◽  
pp. 809
Author(s):  
Rusul Mohammed Neamah ◽  
Jinan Ali Abed ◽  
Elaf Ali Abbood
Keyword(s):  
Color Image ◽  
Information And Communications Technology ◽  
Secret Message ◽  
Sensitive Data ◽  
Hide Information ◽  
Confidential Data ◽  
Xnor Gate ◽  
A New Technique ◽  
The Moment

At the moment, with the great development of information and communications technology, the transfer of confidential and sensitive data through public communications such as the Internet is very difficult to keep them from hackers and attackers. Therefore, it is necessary to work on the development of new and innovative ways to transfer such information and protect it to ensure that it reaches the desired goal. The goal of a new technique to hide information design not only hides the secret message behind the center cover, but it also provides increased security. The most common way to transfer important and confidential data is through embedding it into cover medium files in a way that does not affect the accuracy of the carrier file, which is known as hiding. In this paper, encryption and concealment techniques were used to protect data transferred from attackers. The proposed method relied on encryption of confidential information using the encryption key and the Xnor gate, after which the encrypted information was hidden in a color image using the LSB algorithm. The method of concealment depends on the extraction of chromatic channels of three RGB for each pixel and specifying the channel in which the bit of the encryption message will be hidden. Some metrics have been adopted to measure the quality of the resulting picture after hiding as PSNR and MSE, and achieve good results.

scholarly journals Prediction of DDoS Attacksusing Machine Learning and Deep Learning Algorithms

2019 ◽  
Vol 8 (4) ◽  
pp. 4860-4867
Keyword(s):  
Computer Security ◽  
Fog Computing ◽  
The Internet ◽  
Research Gaps ◽  
Sensitive Data ◽  
Security Breaches ◽  
Ddos Attack ◽  
Massive Growth ◽  
Confidential Data ◽  
Ubiquitous Network

With the emergence of network-based computing technologies like Cloud Computing, Fog Computing and IoT (Internet of Things), the context of digitizing the confidential data over the network is being adopted by various organizations where the security of that sensitive data is considered as a major concern. Over a decade there is a massive growth in the usage of internet along with the technological advancements that demand the need for the development of efficient security algorithms that could withstand various patterns of the security breaches. The DDoS attack is the most significant network-based attack in the domain of computer security that disrupts the internet traffic of the target server. This study mainly focuses to identify the advancements and research gaps in the development of efficient security algorithms addressing DDoS attacks in various ubiquitous network environments.

scholarly journals LEAKING AGENT DETECTION AND EMAIL FILTERING

2013 ◽  
pp. 80-83
Author(s):  
GIRISH SHANKAR ◽  
SOMESHWAR DHAYALAN ◽  
ASHISH ANAND
Keyword(s):  
Data Allocation ◽  
Text File ◽  
Severe Damage ◽  
Sensitive Data ◽  
Confidential Data ◽  
Sample Data ◽  
Modern Business ◽  
Marking Technique ◽  
Data Request ◽  
Allocation Strategies

Leaking of confidential data to an unauthorized agent is a major concern for an organization. In this article we seek to detect the trusted node that leaks the confidential data to an unauthorized agent. Traditionally, leakage of data is handled by water marking technique which requires data modification. If the watermarked copy is found at some unauthorized site then distributor can claim his ownership. But one of the issues with watermarking method is data modification. To overcome the disadvantages of using watermark, data allocation strategies are used to improve the probability of identifying guilty third parties. The idea is to distribute the data intelligently to agents based on sample data request and explicit data request in order to improve the chance of detecting the guilty agents. Modern business activities also rely on extensive email exchange. Email leakages have become widespread, and the severe damage caused by such leakages constitutes a disturbing problem for organizations. Hence, filtering of E-mails is also necessary. This can be done by blocking E-mails which contains images, videos or sensitive data and filtering the text file of an organization.

scholarly journals Securing Criminal Records using R-Pi, QR code and Steganography

2020 ◽  
Vol 9 (6) ◽  
pp. 684-689
Keyword(s):  
Crime Scene ◽  
Raspberry Pi ◽  
Qr Code ◽  
Criminal Record ◽  
Criminal Records ◽  
Sensitive Data ◽  
Rsa Algorithm ◽  
File Formats ◽  
Wide Range ◽  
Confidential Data

In today`s digital scenario it has become very essential to maintain secrecy of criminal records otherwise forgery could happen. Using steganography it is possible to provide security for the information which is communicated over the internet from one crime branch to the other. Steganography one of the emerging security fields works to mask the very existence of the message. A wide range of carrier file formats can be utilized, but digital steganography is the extremely beneficial data hiding technique to secure criminal image as well as the crime scene images. Various applications have various prerequisites of the steganography method utilized. In this paper, we proposed CRSS (Criminal Record Security System) an image steganography method with LSB and RSA technique for enhanced security and along with that Raspberry pi and GSM module is used. Thus, for a more secure approach, the proposed method hides the criminal`s confidential records such as criminal`s image, crime scene digital images etc. using LSB steganography and also encrypts the confidential data making use of a private key using RSA algorithm and then sends it to the desired end. The receiver then decrypts the confidential data to get the original criminal information. CRSS is also proposed to send a QR code to the receiver which hides sensitive data and may include criminal`s previous crime history and other written proofs which are scanned at the receiving end reveals the entire criminal record. The entire system is implemented on Raspberry Pi 3 processor and thus a secure transmission of data without traditional desktop dependency in a more economical way could be established.

Cloud Security Using 2-Factor Image Authentication Technique

2017 ◽  
pp. 135-147
Author(s):  
Ratish Agarwal ◽  
Anjana Pandey ◽  
Mahesh Pawar
Keyword(s):  
Cloud Computing ◽  
User Authentication ◽  
Image Authentication ◽  
Experimental Result ◽  
Cloud Environment ◽  
Sensitive Data ◽  
It Industry ◽  
Authentication Mechanism ◽  
Confidential Data ◽  
Pixel Value

Cloud computing is being anticipated as the infrastructural basis of tomorrow's IT industry and continues to be a topic of interest of many new emerging IT firms. Cloud can deliver resources and services to computers and devices through internet. Since Cloud Computing involves outsourcing of sensitive data and critical information the security aspects of cloud need to be dealt carefully. Strong authentication, focusing mainly on user-authentication, acts as a pre-requisite for access control in the cloud environment. In this paper we discuss an efficient authentication mechanism to deal with the security threats that are faced by cloud. The method proposed in this paper prevents the confidential data and information of end users stored in a private cloud from unauthorized access by using a two-factor authentication involving shared image concept in addition with encrypted key authentication.MD5 hashing technique is used which takes binary pixel value of image as input and convert it into a 128-bit hash value. The overall process of authentication has been shown through experimental result and implementation which shows a series of snapshots taken from the chapter.

Data Security and Chase

2011 ◽  
pp. 114-120
Author(s):  
Zbigniew W. Ras ◽  
Seunghyun Im
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Missing Values ◽  
Database Systems ◽  
Data Encryption ◽  
Data Confidentiality ◽  
Sensitive Data ◽  
Confidential Data ◽  
Non Local ◽  
Missing Value Prediction

This article describes requirements and approaches necessary for ensuring data confidentiality in knowledge discovery systems. Data mining systems should provide knowledge extracted from their data which can be used to identify underlying trends and patterns, but the knowledge should not be used to compromise data confidentiality. Confidentiality for sensitive data is achieved, in general, by hiding them from unauthorized users in conventional database systems (e.g., data encryption and/or access control methods can be considered as data hiding). However, it is not sufficient to hide the confidential data in knowledge discovery systems (KDSs) due to Chase (Dardzinska & Ras, 2003a, 2003c). Chase is a missing value prediction tool enhanced by data mining technologies. For example, if an attribute is incomplete in an information system, we can use Chase to approximate the missing values to make the attribute more complete. It is also used to answer user queries containing non-local attributes (Ras & Joshi, 1997). If attributes in queries are locally unknown, we search for their definitions from KDSs and use the results to replace the non-local part of the query.

Android Application Security

2019 ◽  
pp. 46-67 ◽  
Author(s):  
Marwan Omar ◽  
Derek Mohammed ◽  
Van Nguyen ◽  
Maurice Dawson ◽  
Mubarak Banisakher
Keyword(s):  
Central Issue ◽  
Financial Loss ◽  
Sensitive Data ◽  
Confidential Data ◽  
Android Market ◽  
Malicious Apps ◽  
Android Permission ◽  
Monitoring Application ◽  
Free Open Source ◽  
Installation Time

Android is a free, open source platform that allows any developer to submit apps to the Android Market with no restrictions. This enables hackers to pass their malicious apps to the Android Market as legitimate apps. The central issue lies at the heart of the Android permission mechanism, which is not capable of blocking malicious apps from accessing sensitive phone resources (e.g., contact info and browsing history); it either allows or disallows apps from accessing the resources requested by the app at the installation time. This chapter investigated the scope of this issue and concluded that hackers use malicious apps as attack vectors to compromise Android smartphones and steal confidential data and that no security solutions exist to combat malicious apps. The researcher suggested designing a real time monitoring application to detect and deter malicious apps from compromising users' sensitive data; such application is necessary for Android users to protect their privacy and prevent financial loss.

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