scholarly journals Illuminating the Dark or how to recover what should not be seen in FE-based classifiers

2020 ◽  
Vol 2020 (2) ◽  
pp. 5-23
Author(s):  
Sergiu Carpov ◽  
Caroline Fontaine ◽  
Damien Ligier ◽  
Renaud Sirdey
Keyword(s):  
Data Privacy ◽  
Information Leakage ◽  
Use Cases ◽  
Security And Privacy ◽  
Functional Encryption ◽  
Cryptographic Primitives ◽  
Encrypted Data ◽  
Current State ◽  
Encryption Schemes ◽  
Privacy Issues

AbstractClassification algorithms/tools become more and more powerful and pervasive. Yet, for some use cases, it is necessary to be able to protect data privacy while benefiting from the functionalities they provide. Among the tools that may be used to ensure such privacy, we are focusing in this paper on functional encryption. These relatively new cryptographic primitives enable the evaluation of functions over encrypted inputs, outputting cleartext results. Theoretically, this property makes them well-suited to process classification over encrypted data in a privacy by design’ rationale, enabling to perform the classification algorithm over encrypted inputs (i.e. without knowing the inputs) while only getting the input classes as a result in the clear.In this paper, we study the security and privacy issues of classifiers using today practical functional encryption schemes. We provide an analysis of the information leakage about the input data that are processed in the encrypted domain with state-of-the-art functional encryption schemes. This study, based on experiments ran on MNIST and Census Income datasets, shows that neural networks are able to partially recover information that should have been kept secret. Hence, great care should be taken when using the currently available functional encryption schemes to build privacy-preserving classification services. It should be emphasized that this work does not attack the cryptographic security of functional encryption schemes, it rather warns the community against the fact that they should be used with caution for some use cases and that the current state-ofthe-art may lead to some operational weaknesses that could be mitigated in the future once more powerful functional encryption schemes are available.

scholarly journals Reducing Metadata Leakage from Encrypted Files and Communication with PURBs

2019 ◽  
Vol 2019 (4) ◽  
pp. 6-33 ◽  
Author(s):  
Kirill Nikitin ◽  
Ludovic Barman ◽  
Wouter Lueks ◽  
Matthew Underwood ◽  
Jean-Pierre Hubaux ◽  
...  
Keyword(s):  
Information Leakage ◽  
Maximum Length ◽  
Security And Privacy ◽  
Full Membership ◽  
Encrypted Data ◽  
Data Formats ◽  
Public Keys ◽  
Encryption Schemes ◽  
Privacy Risks ◽  
E Mail

Abstract Most encrypted data formats leak metadata via their plaintext headers, such as format version, encryption schemes used, number of recipients who can decrypt the data, and even the recipients’ identities. This leakage can pose security and privacy risks to users, e.g., by revealing the full membership of a group of collaborators from a single encrypted e-mail, or by enabling an eavesdropper to fingerprint the precise encryption software version and configuration the sender used. We propose that future encrypted data formats improve security and privacy hygiene by producing Padded Uniform Random Blobs or PURBs: ciphertexts indistinguishable from random bit strings to anyone without a decryption key. A PURB’s content leaks nothing at all, even the application that created it, and is padded such that even its length leaks as little as possible. Encoding and decoding ciphertexts with no cleartext markers presents efficiency challenges, however. We present cryptographically agile encodings enabling legitimate recipients to decrypt a PURB efficiently, even when encrypted for any number of recipients’ public keys and/or passwords, and when these public keys are from different cryptographic suites. PURBs employ Padmé, a novel padding scheme that limits information leakage via ciphertexts of maximum length M to a practical optimum of O(log log M) bits, comparable to padding to a power of two, but with lower overhead of at most 12% and decreasing with larger payloads.

scholarly journals ACCOUNTING OUTSOURCING: CURRENT STATE AND PROBLEMS OF PRACTICAL IMPLEMENTATION

2021 ◽  
Author(s):  
Olena Koba ◽  
Keyword(s):  
Data Privacy ◽  
Information Leakage ◽  
Practical Implementation ◽  
Additional Time ◽  
Extra Effort ◽  
Current State ◽  
Analysis And Synthesis ◽  
Business Entities ◽  
Reasonable Choice ◽  
Main Activity

The purpose of the article is to determine the theoretical and organizational principles of application of accounting outsourcing by business entities. Methodology. Methods of analysis and synthesis were used to determine the characteristics and features of the organization of accounting outsourcing. The generalization of the existing experience of application of accounting outsourcing is carried out by a monographic method. On the basis of economic analysis and comparison, trends in the development of accounting outsourcing are identified. Methodology. The development of outsourcing is explained by its ability to increase the competitiveness of products, to promote the introduction of the latest advances in scientific and technological progress, to optimize costs. The application of knowledge and experience of specialists specializing in solving certain issues allows to focus the resources of companies on the development of strengths and promising areas and not to spend extra effort and money on the development of new non-core activities. The generalization of statistics on the current state of outsourcing in Ukraine shows that its effective application is hampered by the lack of free financial resources to invest in new management technologies, lack of awareness of business entities about the experience of outsourcing and the market of outsourcing services, lack of legal mechanisms. Generalization of functionally-oriented, cooperative, managerial, instrumental, integrated, situational, complex approaches gives grounds for outsourcing to understand the management tool, which allows to concentrate the resources of the business entity on the main activity, provides profit growth and increase competitiveness through contractual transfer, non-core functions of specialists or companies that specialize in their implementation and perform more efficiently than the entity. Among the advantages of outsourcing there are reducing the cost of accounting, improving service quality, accountability, confidentiality, tax optimization, reducing the likelihood of fraud by employees, ensuring impartiality and objectivity of accounting, access to additional resources in the field of finance, accounting and tax calculations. However, outsourcing has certain disadvantages, namely the risk of information leakage, possible lack of efficiency, formal performance of duties, liquidation of the outsourcing company, loss of control over own resources and part of the case may be lost, additional time to agree on the terms of the contract. Minimize the disadvantages of outsourcing allows careful and reasonable choice of outsourcing company, which should take into account: data privacy guarantee, staff qualifications, cost of services, reputation, popularity, experience of the outsourcer in the market, flexibility in organizing services, application of the latest technical solutions, outsourcing it has standards of interaction and internal procedures.

scholarly journals Hy-Bridge: A Hybrid Blockchain for Privacy-Preserving and Trustful Energy Transactions in Internet-of-Things Platforms

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 928 ◽  
Author(s):  
Mahdi Daghmehchi Firoozjaei ◽  
Ali Ghorbani ◽  
Hyoungshick Kim ◽  
JaeSeung Song
Keyword(s):  
Service Management ◽  
Energy Use ◽  
Information Leakage ◽  
Security And Privacy ◽  
User Privacy ◽  
Case Scenario ◽  
Iot Platform ◽  
Financial Transactions ◽  
Privacy Issues ◽  
Local Block

In the current centralized IoT ecosystems, all financial transactions are routed through IoT platform providers. The security and privacy issues are inevitable with an untrusted or compromised IoT platform provider. To address these issues, we propose Hy-Bridge, a hybrid blockchain-based billing and charging framework. In Hy-Bridge, the IoT platform provider plays no proxy role, and IoT users can securely and efficiently share a credit with other users. The trustful end-to-end functionality of blockchain helps us to provide accountability and reliability features in IoT transactions. Furthermore, with the blockchain-distributed consensus, we provide a credit-sharing feature for IoT users in the energy and utility market. To provide this feature, we introduce a local block framework for service management in the credit-sharing group. To preserve the IoT users’ privacy and avoid any information leakage to the main blockchain, an interconnection position, called bridge, is introduced to isolate IoT users’ peer-to-peer transactions and link the main blockchain to its subnetwork blockchain(s) in a hybrid model. To this end, a k-anonymity protection is performed on the bridge. To evaluate the performance of the introduced hybrid blockchain-based billing and charging, we simulated the energy use case scenario using Hy-Bridge. Our simulation results show that Hy-Bridge could protect user privacy with an acceptable level of information loss and CPU and memory usage.

Privacy Dangers of Wearables and the Internet of Things

2016 ◽  
pp. 379-402 ◽  
Author(s):  
Scott Amyx
Keyword(s):  
Data Protection ◽  
Data Privacy ◽  
Security And Privacy ◽  
Employee Privacy ◽  
Privacy Concerns ◽  
Business Operations ◽  
Managerial Implications ◽  
Iot Devices ◽  
Privacy Issues ◽  
The Internet Of Things

This chapter identifies concerns about, and the managerial implications of, data privacy issues related to wearables and the IoT; it also offers some enterprise solutions to the complex concerns arising from the aggregation of the massive amounts of data derived from wearables and IoT devices. Consumer and employee privacy concerns are elucidated, as are the problems facing managers as data management and security become an important part of business operations. The author provides insight into how companies are currently managing data as well as some issues related to data security and privacy. A number of suggestions for improving the approach to data protection and addressing concerns about privacy are included. This chapter also examines trending issues in the areas of data protection and the IoT, and contains thought-provoking discussion questions pertaining to business, wearables/IoT data, and privacy issues.

Data confidentiality and computations hiding in cloud services for public administration

2018 ◽  
Vol 0 (7/2018) ◽  
pp. 11-18
Author(s):  
Aleksandra Horubała ◽  
Daniel Waszkiewicz ◽  
Michał Andrzejczak ◽  
Piotr Sapiecha
Keyword(s):  
Public Administration ◽  
Data Privacy ◽  
Homomorphic Encryption ◽  
Personal Data ◽  
Cloud Services ◽  
Security And Privacy ◽  
Data Confidentiality ◽  
Encryption Schemes

Cloud services are gaining interest and are very interesting option for public administration. Although, there is a lot of concern about security and privacy of storing personal data in cloud. In this work mathematical tools for securing data and hiding computations are presented. Data privacy is obtained by using homomorphic encryption schemes. Computation hiding is done by algorithm cryptographic obfuscation. Both primitives are presented and their application for public administration is discussed.

Efficient top representative for multi-authorship encrypted cloud data to assist cognitive search

2020 ◽  
Vol 39 (6) ◽  
pp. 8079-8089
Author(s):  
P. Shanthi ◽  
A. Umamakeswari
Keyword(s):  
Cloud Storage ◽  
Data Privacy ◽  
New Technologies ◽  
Keyword Search ◽  
Information Leakage ◽  
Cloud Services ◽  
Security And Privacy ◽  
Business World ◽  
Cloud Data ◽  
Privacy And Confidentiality

Cloud computing is gaining ground in the digital and business world. It delivers storage service for user access using Internet as a medium. Besides the numerous benefits of cloud services, migrating to public cloud storage leads to security and privacy concerns. Encryption method protects data privacy and confidentiality. However, encrypted data stored in cloud storage reduces the flexibility in processing data. Therefore, the development of new technologies to search top representatives from encrypted public storage is the current requirement. This paper presents a similarity-based keyword search for multi-author encrypted documents. The proposed Authorship Attribute-Based Ranked Keyword Search (AARKS) encrypts documents using user attributes, and returns ranked results to authorized users. The scheme assigns weight to index vectors by finding the dominant keywords of the specific authority document collection. Search using the proposed indexing prunes away branches and processes only fewer nodes. Re-weighting documents using the relevant feedback also improves user experience. The proposed scheme ensures the privacy and confidentiality of data supporting the cognitive search for encrypted cloud data. Experiments are performed using the Enron dataset and simulated using a set of queries. The precision obtained for the proposed ranked retrieval is 0.7262. Furthermore, information leakage to a cloud server is prevented, thereby proving its suitability for public storage.

scholarly journals An Efficient Pairing-Free Certificateless Searchable Public Key Encryption for Cloud-Based IIoT

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Mimi Ma ◽  
Min Luo ◽  
Shuqin Fan ◽  
Dengguo Feng
Keyword(s):  
Internet Of Things ◽  
Data Privacy ◽  
Security And Privacy ◽  
Public Key ◽  
Public Key Encryption ◽  
Privacy Concerns ◽  
Industrial Internet ◽  
Encryption Schemes ◽  
Searchable Public Key Encryption ◽  
Industrial Resource

The Industrial Internet of Things (IIoT), as a special form of Internet of Things (IoT), has great potential in realizing intelligent transformation and industrial resource utilization. However, there are security and privacy concerns about industrial data, which is shared on an open channel via sensor devices. To address these issues, many searchable encryption schemes have been presented to provide both data privacy-protection and data searchability. However, due to the use of expensive pairing operations, most previous schemes were inefficient. Recently, a certificateless searchable public-key encryption (CLSPE) scheme was designed by Lu et al. to remove the pairing operation. Unfortunately, we find that Lu et al.’s scheme is vulnerable to user impersonation attacks. To enhance the security, a new pairing-free dual-server CLSPE (DS-CLSPE) scheme for cloud-based IIoT deployment is designed in this paper. In addition, we provide security and efficiency analysis for DS-CLSPE. The analysis results show that DS-CLSPE can resist chosen keyword attacks (CKA) and has better efficiency than other related schemes.

scholarly journals Analyzing and Evaluating Smart Cities for IoT Based on Use Cases Using the Analytic Network Process

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Chao Huang ◽  
Shah Nazir
Keyword(s):  
Smart City ◽  
Smart Cities ◽  
Information Leakage ◽  
Analytic Network Process ◽  
Use Cases ◽  
Security And Privacy ◽  
World Population ◽  
Network Process ◽  
Iot Devices ◽  
And Control

With the passage of time, the world population is growing. Proper utilization of resources and other devices is tremendously playing an important role to easily examine, manage, and control the resources of the Internet of Things (IoT) in the smart city. Research in the field of IoT has revolutionized the services mostly in smart cities. In the smart city, the applications of IoT are utilized without human involvement. Diverse IoT devices are connected with each other and communicate for different tasks. With the existence of a huge number of IoT devices in the forthcoming years, the chances of privacy breach and information leakage are increasing. Billions of devices connected on IoT producing huge volume of data bound to cloud for processing, management, and storage. Sending of whole data to the cloud might create risk of security and privacy. Various needs of the smart city should be considered for both urgent and effective solutions to support requirements of the growing population. On the other side of rising technology, the IoT evolution has massively produced diverse research directions for the smart city. Keeping in view the use cases of the smart city, the proposed study presents the analytic network process (ANP) for evaluating smart cities. The approach of ANP works well in the situation of complexity, and vagueness exists among the available alternatives. The experimental results of the planned approach show that the approach is effective for evaluating the smart cities for IoT based on the use cases.

Security and Privacy in RFID Based Wireless Networks

2010 ◽  
pp. 1386-1395
Author(s):  
Denis Trcek
Keyword(s):  
Radio Frequency Identification ◽  
Production Costs ◽  
Security And Privacy ◽  
Rfid Technology ◽  
Current State ◽  
Frequency Identification ◽  
Limited Power ◽  
High Production ◽  
Computational Resources ◽  
Privacy Issues

Mass deployment of radio-frequency identification (RFID) technology is now becoming feasible for a wide variety of applications ranging from medical to supply chain and retail environments. Its main draw-back until recently was high production costs, which are now becoming lower and acceptable. But due to inherent constraints of RFID technology (in terms of limited power and computational resources) these devices are the subject of intensive research on how to support and improve increasing demands for security and privacy. This chapter therefore focuses on security and privacy issues by giving a general overview of the field, the principles, the current state of the art, and future trends. An improvement in the field of security and privacy solutions for this kind of wireless communications is described as well.

Blockchain-Based Data Market (BCBDM) Framework for Security and Privacy

2021 ◽  
pp. 186-205
Author(s):  
Shailesh Pancham Khapre ◽  
Chandramohan Dhasarathan ◽  
Puviyarasi T. ◽  
Sam Goundar
Keyword(s):  
Big Data ◽  
Data Sharing ◽  
Data Storage ◽  
Data Privacy ◽  
Security And Privacy ◽  
Research Progress ◽  
Distributed Data ◽  
Distributed Data Storage ◽  
Data Market ◽  
Privacy Issues

In the internet era, incalculable data is generated every day. In the process of data sharing, complex issues such as data privacy and ownership are emerging. Blockchain is a decentralized distributed data storage technology. The introduction of blockchain can eliminate the disadvantages of the centralized data market, but at the same time, distributed data markets have created security and privacy issues. It summarizes the industry status and research progress of the domestic and foreign big data trading markets and refines the nature of the blockchain-based big data sharing and circulation platform. Based on these properties, a blockchain-based data market (BCBDM) framework is proposed, and the security and privacy issues as well as corresponding solutions in this framework are analyzed and discussed. Based on this framework, a data market testing system was implemented, and the feasibility and security of the framework were confirmed.

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