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Novel trusted hardware extensions such as Intel's SGX enable user-space applications to be protected against potentially malicious operating systems. Moreover, SGX supports strong attestation guarantees, whereby remote parties can be convinced of the trustworthy nature of the executing user-space application. These developments are particularly interesting in the context of large-scale privacy-preserving...
This paper studies the feasibility of privacy-preservingdata mining in epidemiological study. As for the data-miningalgorithm, we focus to a linear multiple regression thatcan be used to identify the most significant factorsamong many possible variables, such as the historyof many diseases. We try to identify the linear model to estimate a lengthof hospital stay from distributed dataset related tothe...
Privacy preservation is one of the major issue in digital products. In current era, web search engine has become vital tool for internet users. However, most search engines maintains user profile and analyze them which could compromise privacy. In order to preserve the user privacy from a search engine, many privacy preserving solution have been proposed including query obfuscation, anonymizing networks...
Smart Entertainment Devices (SEDs) are a subclass of Consumer Electronics (CE) devices and can be found in almost every household. SEDs have interfaces to communicate with other parties, e.g., other SEDs in the local network, third parties in the Internet or vendors. Examples of SEDs are Smart TVs, Bluray players, gaming consoles and many more. It becomes more important for vendors and third parties...
Various health care devices owned by either hospitals or individuals are producing huge amount of health care data. The big health data may contain valuable knowledge and new business opportunities. Obviously, cloud is a good candidate to collect, store and analyse such big health care data. However, health care data is very sensitive for its owners, and thus should be well protected on cloud. This...
We present a technique that uses privacy enhancing technologies and biometrics to prevent the unauthorized lending of credentials. Current credential schemes suffer the weakness that issued credentials can be transferred between users. Our technique ensures the biometric identity of the individual executing the Issue and Show protocols of an existing credential system in a manner analogous to the...
Secure multiparty computation allows multiple parties to participate in a computation. SMC (secure multiparty computation) assumes n parties where n>1. All the parties jointly compute a function. Privacy preserving data mining has become an emerging field in the secure multiparty computation. Privacy preserving data mining preserves the privacy of individual's data. Privacy preserving data mining...
This paper studies a privacy-preserving decision tree learning protocol (PPDT) for vertically partitioned datasets. In the vertically partitioned datasets, a single class (target) attribute are shared by both parities or carefully treated by either party in the existing studies. The proposed scheme allows both parties to have independent class attributes in secure way and to combine multiple class...
The growing population and global warming have been calling for more effective energy usage, which have stimulated the emergence of smart sustainable energy technology. The distinct feature of this newly emerging technology is the incorporation of advanced information and communication technologies (ICT), which collects more detailed information on how energy is generated, distributed, and consumed...
Non-verbal human social signals have emerged as an important area of study including the analysis of human deception. The ability to credibly detect truth and deception can be critical today especially due to the wave of terrorism acts and illegal immigration upheavals just to mention a few instances where individuals might not be forthright with their information. Unlike for non-verbal human social...
Now-a-days privacy has become a major concern; the goals of security like confidentiality, integrity and availability do not ensure privacy. Data mining is a threat to privacy. Researchers today focus on how to ensure privacy while performing data mining task. As Data mining algorithms are typically complex and furthermore the input usually consists of massive data sets, the generic protocols in such...
The following topics are dealt with: distributed and parallel computing; semantic Web; mobile networks; peer-to-peer computing; sealable computing; Internet; opportunistic and delay tolerant networks; agent and dependable systems; intelligent computing; communication networks; service oriented architecture; security; wireless sensor networks; privacy; ad hoc networks; life science modeling and computing;...
There has been concern over the apparent conflict between privacy and data mining. Attribute reduction is one of the most important contributions of rough set theory to data mining. In this paper, we address the issue of privacy preserving attribute reduction. Specifically, we consider a scenario in which two parties owning private data, wish to run a attribute reduction algorithm on the union of...
The increasing ability to track and collect large amounts of data with the use of current hardware and software technology has lead to immense challenge and consequent interest in the development of data mining algorithms which preserve user security and privacy in a large distributed system. Secure data aggregation with privacy preserving feature is a demanding task. Privacy preservation is becoming...
Within the context of privacy preserving data mining, several solutions for privacy-preserving classification rules learning such as association rules mining have been proposed. Each solution was provided for horizontally or vertically distributed scenario. The aim of this work is to study privacy-preserving classification rules learning in two-dimension distributed data, which is a generalisation...
The following topics are dealt with: cyber-enabled distributed computing; knowledge discovery; distributed control; data mining; wireless communication; mobile communication; agent; middleware; mobile system; Internet protocol; quality of service; parallel computing; authentication; privacy; system management; neural network; reasoning; and cloud computing.
Secure scalar product protocol is an important fundamental protocol in secure multi-party computation. Serving as a basic building block for many other secure protocols, it is widely used in data mining, statistical analysis and scientific computation. Based on additive homomorphism public key cryptosystem, we develop a new secure scalar product protocol under semi-honest model with low communication...
The growth of the Internet has prompted tremendous opportunities for cooperative computation, where people are jointly conducting computation tasks based on the private inputs they each supplies. These computations can occur between mutually untrusted parties, or even between competitors. For example, customers might send to a remote database queries that contain private information, two competing...
The secure sum protocol is a well-known protocol for computing the sum of private inputs from distributed entities such that the inputs remain private. In this paper we present protocols for computing reputation in a privacy preserving manner that are inspired by the secure sum protocol. We provide a protocol that is secure under the semi-honest adversarial model as well as one that is secure under...
Association rule mining is one of the hottest research areas that investigate the automatic extraction of previously unknown patterns or rules from large amounts of data. Recently, there has been growing concern over the privacy implications of association rule mining. This paper described the basic concepts related to association rule mining, and analyzed and summarized the general principles and...
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