Encryption and Fragmentation for Data Confidentiality in the Cloud

2014 ◽  
pp. 212-243 ◽  
Author(s):  
Sabrina De Capitani di Vimercati ◽  
Robert F. Erbacher ◽  
Sara Foresti ◽  
Sushil Jajodia ◽  
Giovanni Livraga ◽  
...  
Keyword(s):  
Data Confidentiality

An Empirical Analysis of the Obtrusiveness of and Participants' Compliance with the Electronically Activated Recorder (EAR)

2007 ◽  
Vol 23 (4) ◽  
pp. 248-257 ◽  
Author(s):  
Matthias R. Mehl ◽  
Shannon E. Holleran
Keyword(s):  
Empirical Analysis ◽  
Sampling Method ◽  
Daily Life ◽  
Assessment Method ◽  
Data Confidentiality ◽  
Short Term ◽  
Naturally Occurring ◽  
Two Samples ◽  
Audio Recorder ◽  
Term Monitoring

Abstract. In this article, the authors provide an empirical analysis of the obtrusiveness of and participants' compliance with a relatively new psychological ambulatory assessment method, called the electronically activated recorder or EAR. The EAR is a modified portable audio-recorder that periodically records snippets of ambient sounds from participants' daily environments. In tracking moment-to-moment ambient sounds, the EAR yields an acoustic log of a person's day as it unfolds. As a naturalistic observation sampling method, it provides an observer's account of daily life and is optimized for the assessment of audible aspects of participants' naturally-occurring social behaviors and interactions. Measures of self-reported and behaviorally-assessed EAR obtrusiveness and compliance were analyzed in two samples. After an initial 2-h period of relative obtrusiveness, participants habituated to wearing the EAR and perceived it as fairly unobtrusive both in a short-term (2 days, N = 96) and a longer-term (10-11 days, N = 11) monitoring. Compliance with the method was high both during the short-term and longer-term monitoring. Somewhat reduced compliance was identified over the weekend; this effect appears to be specific to student populations. Important privacy and data confidentiality considerations around the EAR method are discussed.

Preserving Data Confidentiality in Internet of Things

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Poornima M. Chanal ◽  
Mahabaleshwar S. Kakkasageri
Keyword(s):  
Internet Of Things ◽  
Data Confidentiality

scholarly journals A Complete Key Management Scheme for LoRaWAN v1.1

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2962
Author(s):  
Xingda Chen ◽  
Margaret Lech ◽  
Liuping Wang
Keyword(s):  
Low Power ◽  
Key Management ◽  
Wide Area Networks ◽  
Key Generation ◽  
Security Framework ◽  
Data Confidentiality ◽  
Backward Compatibility ◽  
Management Scheme ◽  
The Internet Of Things ◽  
Key Management Scheme

Security is one of the major concerns of the Internet of Things (IoT) wireless technologies. LoRaWAN is one of the emerging Low Power Wide Area Networks being developed for IoT applications. The latest LoRaWAN release v.1.1 has provided a security framework that includes data confidentiality protection, data integrity check, device authentication and key management. However, its key management part is only ambiguously defined. In this paper, a complete key management scheme is proposed for LoRaWAN. The scheme addresses key updating, key generation, key backup, and key backward compatibility. The proposed scheme was shown not only to enhance the current LoRaWAN standard, but also to meet the primary design consideration of LoRaWAN, i.e., low power consumption.

A New Approach to Preserving Data Confidentiality in the Cloud

2016 ◽  
Author(s):  
Eliseu C. Branco ◽  
Jose Maria Monteiro ◽  
Roney Reis de C. e Silva ◽  
Javam C. Machado
Keyword(s):  
Data Confidentiality ◽  
New Approach

scholarly journals Cloud computing security: a survey

2018 ◽  
Vol 7 (2.21) ◽  
pp. 355
Author(s):  
P Sheela Gowr ◽  
N Kumar
Keyword(s):  
Cloud Computing ◽  
Information Flow ◽  
Data Encryption ◽  
Information Services ◽  
Ease Of Use ◽  
Cloud Services ◽  
Authentication Scheme ◽  
Data Confidentiality ◽  
Cloud Computing Security ◽  
Security Issues

Cloud computing was a hasting expertise which has innovated to a collection of new explores. A sub-ordinate device for Information services, it has an ability towards encourage development by feeding convenient environments for a choice of forms of development is different sequence. Clouds usually consider being eco-friendly, however keep it has open to the diversity of some security issues to can change together the feeder as well as users of these cloud services. In this issue are principally associated to the protection of the information flow throughout also being store in the cloud, with simple problems along with data ease of use, data right to use and data confidentiality. Data encryption and service authentication scheme has been initiated by the industries to deal with them. In this paper analyse and examine different issues on security beside with the different procedure worn by the industries to solve these effects. 

scholarly journals Accomplishing Data Integrity and Confidentiality in Data Markets

2019 ◽  
Vol 8 (11) ◽  
pp. 49-52
Keyword(s):  
Service Provider ◽  
Privacy Protection ◽  
Explicit Learning ◽  
Data Confidentiality ◽  
Raw Data ◽  
Data Services ◽  
On Line ◽  
Identity Based ◽  
Identity Protection ◽  
Size Data

As a noteworthy business worldview, a few on-line information stages have developed to fulfill society's wants for individual explicit learning, any place a service provider assembles raw data from data givers, at that point offers data services to data clients. Notwithstanding, inside the data exchanging level, the data customers face a squeezing issue, i.e., an approach to confirm whether the service provider has actually gathered and handled data. During this paper, we propose TPDM, that effectively compose truthfulness and Privacy protection in data Markets. TPDM is structured inside in partner degree Encrypt-then-Sign way; utilize mostly homomorphism encryption and identity-based signature. It along encourage bunch confirmation, processing, and result check, though giving identity protection and data confidentiality. We used dataset and 2015 RECS dataset, severally. Our examination and investigation results that TPDM accomplishes numerous alluring properties, though obtaining low calculation and correspondence overheads once sustaining huge size data markets

scholarly journals Federated Reinforcement Distillation with Proxy Experience Memory

2020 ◽  
Author(s):  
Han Cha ◽  
Jihong Park ◽  
Hyesung Kim ◽  
Seong-Lyun Kim ◽  
Mehdi Bennis
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Confidentiality ◽  
User Privacy ◽  
Joint Conference ◽  
International Joint

This paper is presented at 28th International Joint Conference on Artificial Intelligence (IJCAI-19) 1st Wksp. Federated Machine Learning for User Privacy and Data Confidentiality (FML'19), Macau, August 2019.

scholarly journals Optimization of Advanced Encryption Standard (AES) Using Vivado High Level Synthesis (HLS)

10.29007/x3tx ◽  
2019 ◽  
Author(s):  
Luka Daoud ◽  
Fady Hussein ◽  
Nader Rafla
Keyword(s):  
High Level Synthesis ◽  
Advanced Encryption Standard ◽  
Data Confidentiality ◽  
Maximum Throughput ◽  
Loop Unrolling ◽  
Aes Algorithm ◽  
Hardware Implementations ◽  
High Level ◽  
Dedicated Hardware ◽  
Vivado Hls

Advanced Encryption Standard (AES) represents a fundamental building module of many network security protocols to ensure data confidentiality in various applications ranging from data servers to low-power hardware embedded systems. In order to optimize such hardware implementations, High-Level Synthesis (HLS) provides flexibility in designing and rapid optimization of dedicated hardware to meet the design constraints. In this paper, we present the implementation of AES encryption processor on FPGA using Xilinx Vivado HLS. The AES architecture was analyzed and designed by loop unrolling, and inner-round and outer-round pipelining techniques to achieve a maximum throughput of the AES algorithm up to 1290 Mbps (Mega bit per second) with very significant low resources of 3.24% slices of the FPGA, achieving 3 Mbps per slice area.

scholarly journals Ensuring Improved Security in Medical Data Using ECC and Blockchain Technology with Edge Devices

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Mary Subaja Christo ◽  
V. Elizabeth Jesi ◽  
Uma Priyadarsini ◽  
V. Anbarasu ◽  
Hridya Venugopal ◽  
...  
Keyword(s):  
Medical Data ◽  
Security Measures ◽  
Data Confidentiality ◽  
Hospital Data ◽  
Healthcare Data ◽  
Security Issues ◽  
Blockchain Technology ◽  
Data Authentication ◽  
Efficient Retrieval ◽  
Lightweight Authentication

Hospital data management is one of the functional parts of operations to store and access healthcare data. Nowadays, protecting these from hacking is one of the most difficult tasks in the healthcare system. As the user’s data collected in the field of healthcare is very sensitive, adequate security measures have to be taken in this field to protect the networks. To maintain security, an effective encryption technology must be utilised. This paper focuses on implementing the elliptic curve cryptography (ECC) technique, a lightweight authentication approach to share the data effectively. Many researches are in place to share the data wirelessly, among which this work uses Electronic Medical Card (EMC) to store the healthcare data. The work discusses two important data security issues: data authentication and data confidentiality. To ensure data authentication, the proposed system employs a secure mechanism to encrypt and decrypt the data with a 512-bit key. Data confidentiality is ensured by using the Blockchain ledger technique which allows ethical users to access the data. Finally, the encrypted data is stored on the edge device. The edge computing technology is used to store the medical reports within the edge network to access the data in a very fast manner. An authenticated user can decrypt the data and process the data at optimum speed. After processing, the updated data is stored in the Blockchain and in the cloud server. This proposed method ensures secure maintenance and efficient retrieval of medical data and reports.

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