K-Means Clustering Using Homomorphic Encryption and an Updatable Distance Matrix: Secure Third Party Data Clustering with Limited Data Owner Interaction

2017 ◽  
pp. 274-285 ◽  
Author(s):  
Nawal Almutairi ◽  
Frans Coenen ◽  
Keith Dures
Keyword(s):  
Data Clustering ◽  
Homomorphic Encryption ◽  
Distance Matrix ◽  
Third Party ◽  
Limited Data ◽  
Data Owner

scholarly journals A Password Meter without Password Exposure

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 345
Author(s):  
Pyung Kim ◽  
Younho Lee ◽  
Youn-Sik Hong ◽  
Taekyoung Kwon
Keyword(s):  
Performance Enhancement ◽  
Homomorphic Encryption ◽  
Optimization Techniques ◽  
Third Party ◽  
Fully Homomorphic Encryption ◽  
Performance Achievement ◽  
Server Side ◽  
On Line ◽  
Internal Mechanism ◽  
High Chance

To meet password selection criteria of a server, a user occasionally needs to provide multiple choices of password candidates to an on-line password meter, but such user-chosen candidates tend to be derived from the user’s previous passwords—the meter may have a high chance to acquire information about a user’s passwords employed for various purposes. A third party password metering service may worsen this threat. In this paper, we first explore a new on-line password meter concept that does not necessitate the exposure of user’s passwords for evaluating user-chosen password candidates in the server side. Our basic idea is straightforward; to adapt fully homomorphic encryption (FHE) schemes to build such a system but its performance achievement is greatly challenging. Optimization techniques are necessary for performance achievement in practice. We employ various performance enhancement techniques and implement the NIST (National Institute of Standards and Technology) metering method as seminal work in this field. Our experiment results demonstrate that the running time of the proposed meter is around 60 s in a conventional desktop server, expecting better performance in high-end hardware, with an FHE scheme in HElib library where parameters support at least 80-bit security. We believe the proposed method can be further explored and used for a password metering in case that password secrecy is very important—the user’s password candidates should not be exposed to the meter and also an internal mechanism of password metering should not be disclosed to users and any other third parties.

scholarly journals Controlled Functional Encryption Revisited: Multi-Authority Extensions and Efficient Schemes for Quadratic Functions

2021 ◽  
Vol 2021 (1) ◽  
pp. 21-42
Author(s):  
Miguel Ambrona ◽  
Dario Fiore ◽  
Claudio Soriente
Keyword(s):  
Homomorphic Encryption ◽  
Linear Functions ◽  
Quadratic Functions ◽  
Functional Encryption ◽  
Fine Grained ◽  
Multiple Data ◽  
Garbled Circuits ◽  
Private Data ◽  
Data Owner ◽  
Single Data

AbstractIn a Functional Encryption scheme (FE), a trusted authority enables designated parties to compute specific functions over encrypted data. As such, FE promises to break the tension between industrial interest in the potential of data mining and user concerns around the use of private data. FE allows the authority to decide who can compute and what can be computed, but it does not allow the authority to control which ciphertexts can be mined. This issue was recently addressed by Naveed et al., that introduced so-called Controlled Functional encryption (or C-FE), a cryptographic framework that extends FE and allows the authority to exert fine-grained control on the ciphertexts being mined. In this work we extend C-FE in several directions. First, we distribute the role of (and the trust in) the authority across several parties by defining multi-authority C-FE (or mCFE). Next, we provide an efficient instantiation that enables computation of quadratic functions on inputs provided by multiple data-owners, whereas previous work only provides an instantiation for linear functions over data supplied by a single data-owner and resorts to garbled circuits for more complex functions. Our scheme leverages CCA2 encryption and linearly-homomorphic encryption. We also implement a prototype and use it to showcase the potential of our instantiation.

scholarly journals Privacy Preserving Analytics in Outsourced Healthcare System

2020 ◽  
Vol 9 (9) ◽  
pp. 329-333
Keyword(s):  
Healthcare System ◽  
Cloud Storage ◽  
Learning Algorithm ◽  
Homomorphic Encryption ◽  
Digital Health ◽  
Health Data ◽  
Third Party ◽  
Sensitive Data ◽  
Data Intensive ◽  
Cloud Server

The most data intensive industry today is the healthcare system. The advancement in technology has revolutionized the traditional healthcare practices and led to enhanced E-Healthcare System. Modern healthcare systems generate voluminous amount of digital health data. These E-Health data are shared between patients and among groups of physicians and medical technicians for processing. Due to the demand for continuous availability and handling of these massive E-Health data, mostly these data are outsourced to cloud storage. Being cloud-based computing, the sensitive patient data is stored in a third-party server where data analytics are performed, hence more concern about security raises. This paper proposes a secure analytics system which preserves the privacy of patients’ data. In this system, before outsourcing, the data are encrypted using Paillier homomorphic encryption which allows computations to be performed over encrypted dataset. Then Decision Tree Machine Learning algorithm is used over this encrypted dataset to build the classifier model. This encrypted model is outsourced to cloud server and the predictions about patient’s health status is displayed to the user on request. In this system nowhere the data is decrypted throughout the process which ensures the privacy of patients’ sensitive data.

scholarly journals ANALISIS FAKTOR-FAKTOR INTERNAL YANG MEMPENGARUHI PEMBIAYAAN USAHA MIKRO KECIL DAN MENENGAH (UMKM) PADA BANK SYARIAH DI INDONESIA

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Risna Destiana
Keyword(s):  
Time Series ◽  
Economic Development ◽  
External Factors ◽  
The Other ◽  
Third Party ◽  
Business Unit ◽  
Limited Data ◽  
Internal Factors ◽  
Regression Test ◽  
Internal And External Factors

It is a fact that the UMKM’s are resistant due to monetary crisis in Indonesia. It proves UMKM’s significant and important roles of the economic development in establishing employment, improving National Gross Domestic Product and developing national industries. Because of these potentials of UMKM’s, banks should provide assistantships by providing their loan as financial aids. It is however, influenced by some factors such as internal and external factors. The aim of this research was to analyze the influence of internal factors which refers to internal bank condition such as third party funds (DPK), capitals, profitability, risk and liquidity toward UMKM’s at syaria banking in Indonesia. The data of the study were taken from general syaria bank (BUS) and syaria business unit (UUS) which were provided in the syaria banking statistic from Indonesian central bank (official website of BI) from 2008 up to Juni 2013. Due to the limited data provided in syaria banking statistic, the 2008 and 2009 data were three-monthly: March, June, September and December while the 2010 to Juni 2013 data were monthly. Thus, there were 50 time series of observation. The data were analyzed by using regression provided in 17.0 ver. SPSS. The result of regression test shows that internal factors which significantly influenced UMKM’s finance at syaria banking were the DPK and liquidity, whereas the other factors such as the capital, profit and risk had no significance on the financing UMKM’s. 

scholarly journals A Cloud Based Secure Voting System using Homomorphic Encryption for Android Platform

2016 ◽  
Vol 6 (6) ◽  
pp. 2994
Author(s):  
Manish Ranjan ◽  
Ayub Hussain Mondal ◽  
Monjul Saikia
Keyword(s):  
Service Provider ◽  
Cloud Storage ◽  
Homomorphic Encryption ◽  
Information Leakage ◽  
Third Party ◽  
Sensitive Information ◽  
Cipher Text ◽  
Cloud Storage Service ◽  
Android Platform ◽  
Voting System

<p>Cloud based service provider are at its top of its services for various applications, as their services are very much reachable from anywhere anytime in current days. It is responsibility of the company that the Cloud storage is owned and maintained by themselves keeping the data available and accessible, and the physical environment protected and running. Could storage provider seem to be uncertain of confidentiality in many cases, as we need to limit ourselves on trust to a third party. Keeping our sensitive data ready to access any time anywhere with preventing any information leakage is a challenging task. Cryptography in this scenario plays an important role, providing security for information to protect valuable information resources on intranets, Internet and the cloud. In addition, Homomorphic cryptosystem is a form of Cryptography where some specific computation can be performed over the cipher text producing a resultant cipher text which, when decrypted, equals the result of operations carry out on the plaintext. With help of this unique property of homomorphism cryptography we proposed a system to keep sensitive information in encrypted form in the cloud storage/service provider and used those data as whenever we require. The scheme proposed here is designed for a secure online voting system on Android platform and voted information is encrypted and stored those in the cloud.</p>

scholarly journals Multi-Keyword Ranked Search in Cloud Storage using Homomorphic Indexing

2018 ◽  
Vol 7 (2.24) ◽  
pp. 243
Author(s):  
K Renugha ◽  
P Shanthi ◽  
A Umamakeswari
Keyword(s):  
Search Algorithm ◽  
Homomorphic Encryption ◽  
Cloud Service ◽  
Security And Privacy ◽  
Cloud Service Provider ◽  
Secure Information ◽  
Data Owner ◽  
Ranked Search ◽  
The Given ◽  
Is Outsourcing

In the cloud environment, the main issue is outsourcing of the information to the cloud service provider and outsider. Consider this, the cloud tenant store data in an encrypted form to achieve data security and privacy. The data owner needs the secure information sharing from the cloud and without leak of access pattern to the eavesdroppers. XOR homomorphic encryption searchable algorithm along with ranking is proposed to provide the security over the network. In addition our scheme provides secure Multi-keyword ranked search over encrypted data. Efficient ranked search algorithm returns the relevant document based on the results for the given multiple keywords. The experimental results prove that the system is efficient. 

scholarly journals Homomorphic Cryptosystems for Data Security in Cloud Storage

2019 ◽  
Vol 9 (2) ◽  
pp. 3164-3166
Keyword(s):  
Cloud Storage ◽  
Homomorphic Encryption ◽  
Data Authentication ◽  
Outsourced Data ◽  
Integrity Checking ◽  
Data Owner ◽  
Encryption Schemes ◽  
Verification Process ◽  
And Performance ◽  
Local Storage

Cloud Computing enables users to use remote resources thus reduces the burden on local storage. However, the use of such services gives rise to new set of problems. The users have no control over the data which they have stored on those storages so to achieve data authentication with confidentiality is utmost important. As every user may not have that expertise so they can request for data verification task to Trusted Verifier (TV) which will be an authorized party to check the intactness of outsourced data. Since the data owner stores the data on the cloud in an encrypted format, it becomes difficult to check the integrity of the data without decrypting. But by using homomorphic encryption schemes the integrity checking can be made possible without original copy. In this paper, we have given implementation and performance details of two homomorphic encryption schemes, Rivest Shamir Adleman (RSA) and Paillier. The RSA is multiplicative homomorphic scheme where the Paillier is additive homomorphic scheme. Both the algorithms are partially homomorphic thus limited in their functions. Due to homomorphic property of these algorithms, original contents will not get revealed in the verification process. This framework will achieve authentication of data by maintaining confidentiality.

Trust, Privacy, Issues in Cloud-Based Healthcare Services

2016 ◽  
pp. 163-188
Author(s):  
Shweta Kaushik ◽  
Charu Gandhi
Keyword(s):  
Healthcare Services ◽  
Third Party ◽  
Cloud System ◽  
Cloud Provider ◽  
Security Issues ◽  
Computing Services ◽  
Data Owner ◽  
Cloud Computing Services ◽  
Patient’S Information ◽  
Privacy Issues

In recent era individuals and organizations are migrating towards the cloud computing services to store and retrieve the data or services. However, they have less confidence on cloud as all the task are handled by the service provider without any involvement of the data owner. Cloud system provides features to the owner, to store their data on some remote locations and allow only authorized users to access the data according to the role, access capability or attribute they possess. Storing the personal health records on cloud server (third party) is a promising model for healthcare services to exchange information with the help of cloud provider. In this chapter, we highlight the various security issues and concerns such as trust, privacy and access control in cloud based healthcare system that needs to be known while storing the patient's information over a cloud system.

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