scholarly journals A Secured Public Auditing Protocol with Dynamic Structure for Cloud Data

2019 ◽  
Vol 9 (1S) ◽  
pp. 81-85
Keyword(s):  
Data Security ◽  
Information Hiding ◽  
Research Work ◽  
Dynamic Structure ◽  
Data Integrity ◽  
Third Party ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Sensitive Data ◽  
Cloud Data

At present Cloud computing is a very successful paradigm for data computing and storage. It Increases the concerns about data security and privacy in the cloud. Paper covers cloud security and privacy research, while focusing on the works that protect data confidentiality and privacy for sensitive data being stored and queried in the cloud. As Survey enlist all the research carried out related to data security and users privacy preserving techniques in detail. Data sharing can be achieved with sensitive information hiding with remote data integrity auditing, propose a new concept called identity based shared data integrity auditing with sensitive information hiding for secure cloud storage. Initially every data would be outsourced to the cloud only after authorized or activated by the proxy. The key would be generated to the file randomly by the key generation Centre. The transaction details such as key mismatch, file upload and download, hacking details would be shown to the proxy and cloud server. If the match occurs, automatically file would be recovered by the user even if hacker access or tamper the file. The main motive is to ensure that when the cloud properly stores the user’s sanitized data, the proof it generates can pass the verification of the third party auditor. And the paper provides various research work done in the field

scholarly journals Remote Data Integrity Check

2020 ◽  
Vol 9 (5) ◽  
pp. 661-664
Keyword(s):  
Data Integrity ◽  
Third Party ◽  
Sensitive Data ◽  
Text Data ◽  
Cloud Data ◽  
The Third ◽  
Cipher Text ◽  
Data Owner ◽  
Cloud Server ◽  
The Third Party

In Cloud Storage Server, data integrity plays an important role, given cloud clients might not be aware whether the data is safe or has been tampered with. This system introduces identity-based signature algorithms to protect data that belongs to the data owner and gets the status of cloud data by means of verification through signatures. Since it is practically not possible for the data owner to be available online all the time for checking cloud data integrity, Third party auditor is tasked with verifying the data integrity every time instead of data owner. The Third party auditors should not read the cipher text data while verifying and must authenticate itself to cloud server by performing Proof of Knowledge operation; then cloud server can reveal the sensitive data as block wise and the third party auditor can verify the signature without knowledge of cipher text data. Finally, an audit report is sent to the data owner. This work demonstrates data security and integrity in the cloud..

scholarly journals Enhancement of an Optimized Key for Database Sanitization to Ensure the Security and Privacy of an Autism Dataset

Symmetry ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1912
Author(s):  
Md. Mokhlesur Rahman ◽  
Ravie Chandren Muniyandi ◽  
Shahnorbanun Sahran ◽  
Suziyani Mohamed
Keyword(s):  
Data Security ◽  
Daily Basis ◽  
Data Encryption ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Sensitive Data ◽  
Data Sanitization ◽  
Algorithmic Framework ◽  
Computational Resources ◽  
Disk Encryption

Interrupting, altering, or stealing autism-related sensitive data by cyber attackers is a lucrative business which is increasing in prevalence on a daily basis. Enhancing the security and privacy of autism data while adhering to the symmetric encryption concept is a critical challenge in the field of information security. To identify autism perfectly and for its data protection, the security and privacy of these data are pivotal concerns when transmitting information over the Internet. Consequently, researchers utilize software or hardware disk encryption, data backup, Data Encryption Standard (DES), TripleDES, Advanced Encryption Standard (AES), Rivest Cipher 4 (RC4), and others. Moreover, several studies employ k-anonymity and query to address security concerns, but these necessitate a significant amount of time and computational resources. Here, we proposed the sanitization approach for autism data security and privacy. During this sanitization process, sensitive data are concealed, which avoids the leakage of sensitive information. An optimal key was generated based on our improved meta-heuristic algorithmic framework called Enhanced Combined PSO-GWO (Particle Swarm Optimization-Grey Wolf Optimization) framework. Finally, we compared our simulation results with traditional algorithms, and it achieved increased output effectively. Therefore, this finding shows that data security and privacy in autism can be improved by enhancing an optimal key used in the data sanitization process to prevent unauthorized access to and misuse of data.

scholarly journals Privacy Preserving for Sensitive Data using Data Masking Technique

2020 ◽  
Vol 8 (6) ◽  
pp. 5334-5337
Keyword(s):  
Information Hiding ◽  
Data Privacy ◽  
Banking Sector ◽  
Third Party ◽  
Sensitive Information ◽  
Sensitive Data ◽  
Memory Space ◽  
Space Organization ◽  
Data Masking ◽  
Using Data

In recent times, most the people are using internet where they are going to share sensitive information with other individual or with an organization like hospital, banking sector or business companies. So such huge amount of information will be stored on cloud. The attackers may try to hack the sensitive data and will try to misuse that data. So here the security for data comes first. There are numerous methods available to provide security for the data that is being shared among individuals or organizations. Most of the organizations take enough precautions to secure data that is shared with third party organizations. In recent times providing privacy for the sensitive data is high priority. The objective of this research is to discover the various data masking solutions for different applications for providing security to the data. Established data privacy method like AES or DES encryption technique proves to be proficient but time consuming. In order to avoid time consumption and to provide privacy for the data being shared, this paper proposes a information hiding method based on format-preserving encryption for sensitive data. This method will masquerade only sensitive data and make sure the encrypted data is still in the original format where it doesn’t consume much memory space. Organization like hospitals or banking sector or any business companies can use this format-preserving method to enhance the security of the data being shared. Tested the information on Spark illustrate that information hiding method based on format-preserving encryption can provide data privacy for sensitive data and preserve data format.

scholarly journals Practical Multi-Keyword Ranked Search with Time- Based Access Control over Encrypted Cloud Data

2021 ◽  
pp. 72-78
Keyword(s):  
Access Control ◽  
Time Window ◽  
Security Analysis ◽  
Third Party ◽  
Security And Privacy ◽  
Sensitive Data ◽  
K Nearest Neighbors ◽  
Cloud Data ◽  
Massive Growth ◽  
Ranked Search

The recent trends suggest that there is an increase in the inclination towards storing data in the cloud due to explosive and massive growth of the volume of the data in the cloud computing environment. It helps them to reduce their computational and storage costs but also undeniably brought in concerns about security and privacy as the owners of the highly sensitive data lose control of it directly. The sensitive data could include electronic-based medical records, confidential fiscal documents, etc. An increased distrust about storage of files in a third-party service provider of cloud resources would contradict the very same reason for which cloud storage facilities were introduced. That’s because we cannot deny the fact that cloud based storage systems offer on- demand and ubiquitous access to flexible storage and computational resources. The keyword ranked search methodologies used in the existing systems mainly focus on enhancing and enriching the efficiency of searching the files and their respective functionalities but a lack of straight forward analysis of security and issues with providing access control have not been addressed. To address these disadvantages, in this paper, we propose an efficient Multi-Keyword Ranked Search scheme with Fine-grained access control (MRSF).MRSF is a methodology which can combine matching of coordinates technique with Term Frequency-Inverse Document Frequency (TF-IDF) to thereby achieve a highly precise retrieval of any cipher text of interest. It also improves the secure k-nearest neighbors (kNN) method. By utilizing an access strategy which is polynomial based, it can effectively refine the search privileges of the users’. Professional security analysis proves that MRSF is secure with respect to safeguarding the secrecy of outsourced data and the privacy of tokens and indices. Along with this enhanced methodology of ranked search scheme, a time limit based access control feature has also been proposed to ensure that the adaptive attackers are stalled from giving prolonged access to the data files. Session expiry will ensure security of data and that is to be achieved by providing a time window for the file retrieval. Extensive experiments also show that MRSF reaches higher search precision and many more functionalities when compared to the existing systems.

scholarly journals Third Party Public Auditing Scheme for Cloud Storage

2021 ◽  
Vol 9 (11) ◽  
pp. 1087-1093
Author(s):  
Mr. Vaishnav P. Surwase
Keyword(s):  
Data Security ◽  
Cloud Storage ◽  
Research Work ◽  
Data Integrity ◽  
Third Party ◽  
Main Role ◽  
Fine Grained ◽  
Data Owner ◽  
Cloud Server ◽  
Integrity Check

Abstract: Thus the new auditing scheme has been developed by considering all these requirements. It consist of three entities: data owner, TPA and cloud server. The data owner performs various operations such as splitting the file to blocks, encrypting them, generating a hash value for each, concatenating it and generating a signature on it. The TPA performs the main role of data integrity check. It performs activities like generating hash value for encrypted blocks received from cloud server, concatenating them and generates signature on it. It later compares both the signatures to verify whether the data stored on cloud is tampered or not. It verifies the integrity of data on demand of the users. The cloud server is used only to save the encrypted blocks of data. This proposed auditing scheme make use of AES algorithm for encryption, SHA-2 for integrity check and RSA signature for digital signature calculation. In this philosophy, users of cloud storage services no longer physically maintain direct control over their data, which makes data security one of the major concerns of using cloud. Existing research work already allows data integrity to be verified without possession of the actual data file. When the verification is done by a trusted third party, this verification process is also called data auditing, and this third party is called an auditor. As a result, every small update will cause re-computation and updating of the authenticator for an entire file block, which in turn causes higher storage and communication overheads. In this paper, we provide a formal analysis for possible types of fine-grained data updates and propose a scheme that can fully support authorized auditing and fine-grained update requests. Basedon our scheme, we also propose an enhancement that can dramatically reduce communication overheads for verifying small updates Keywords: Cloud computing, big data, data security, authorized auditing, fine-grained dynamic data update

scholarly journals Comparable Encryption Scheme over Encrypted Cloud Data in Internet of Everything

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Qian Meng ◽  
Jianfeng Ma ◽  
Kefei Chen ◽  
Yinbin Miao ◽  
Tengfei Yang
Keyword(s):  
Model Performance ◽  
Data Integrity ◽  
Cloud Service ◽  
Third Party ◽  
Encryption Scheme ◽  
Cloud Data ◽  
Practical Applications ◽  
Internet Of Everything ◽  
Window Method ◽  
Comparable Encryption

User authentication has been widely deployed to prevent unauthorized access in the new era of Internet of Everything (IOE). When user passes the legal authentication, he/she can do series of operations in database. We mainly concern issues of data security and comparable queries over ciphertexts in IOE. In traditional database, a Short Comparable Encryption (SCE) scheme has been widely used by authorized users to conduct comparable queries over ciphertexts, but existing SCE schemes still incur high storage and computational overhead as well as economic burden. In this paper, we first propose a basic Short Comparable Encryption scheme based on sliding window method (SCESW), which can significantly reduce computational and storage burden as well as enhance work efficiency. Unfortunately, as the cloud service provider is a semitrusted third party, public auditing mechanism needs to be furnished to protect data integrity. To further protect data integrity and reduce management overhead, we present an enhanced SCESW scheme based on position-aware Merkle tree, namely, PT-SCESW. Security analysis proves that PT-SCESW and SCESW schemes can guarantee completeness and weak indistinguishability in standard model. Performance evaluation indicates that PT-SCESW scheme is efficient and feasible in practical applications, especially for smarter and smaller computing devices in IOE.

scholarly journals MACHINE LEARNING APPROACH FOR CRYPTOSYSTEM SUGGEST IN EDUCARE OVER CLOUDS

2021 ◽  
Vol 9 (6) ◽  
pp. 98-103
Author(s):  
Ravish G K ◽  
Thippeswamy K
Keyword(s):  
Machine Learning ◽  
Research Work ◽  
Cloud Services ◽  
Learning System ◽  
Security And Privacy ◽  
Great Promise ◽  
Sensitive Information ◽  
Online Systems ◽  
Machine Learning Approach ◽  
Time Requirements

In the current situation of the pandemic, global organizations are turning to online functionality to ensure survival and sustainability. The future, even though uncertain, holds great promise for the education system being online. Cloud services for education are the center of this research work as they require security and privacy. The sensitive information about the users and the institutions need to be protected from all interested third parties. since the data delivery on any of the online systems is always time sensitive, the have to be fast. In previous works some of the algorithms were explored and statistical inference based decision was presented. In this work a machine learning system is designed to make that decision based on data type and time requirements.

scholarly journals An novel architecture for information hiding using HMAC-MD5

2013 ◽  
Vol 2 (2) ◽  
pp. 134 ◽  
Author(s):  
Agilandeeswari Loganathan ◽  
Brindha Krishnamoorthy ◽  
Stiffy Sunny ◽  
Muralibabu Kumaravel
Keyword(s):  
Data Security ◽  
Information Hiding ◽  
Secret Message ◽  
Digital Form ◽  
Secret Data ◽  
Sensitive Data ◽  
Current Discussion ◽  
Payload Capacity ◽  
Lsb Technique ◽  
Embedded Image

Communication in digital form has become the part of day todays lifestyle, in certain moment communication is made secret to avoid others from knowing the information. By providing security to the sensitive data it is ensured that the users data is protected from viewing and accessing by others. In the current discussion about data security, Steganographic algorithm using two mediums has been discussed that involves image based encryption and converting to word file. The stage involving image based encryption uses HMAC-MD5 algorithm along with LSB steganography. LSB technique scatters the secret data which have to be protected over the entire image. Convert the embedded image in word file, so that the secret message is made unavailable to others who try to obtain the file. This method provides greater payload capacity along with higher image fidelity and thus make the proposed system is more robust against attacks.

scholarly journals Secure Smart Cameras by Aggregate-Signcryption with Decryption Fairness for Multi-Receiver IoT Applications

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 327 ◽  
Author(s):  
Subhan Ullah ◽  
Lucio Marcenaro ◽  
Bernhard Rinner
Keyword(s):  
Data Transfer ◽  
Single Step ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Smart Camera ◽  
Sensitive Data ◽  
Smart Cameras ◽  
Iot Applications ◽  
Public Verifiability ◽  
Single Receiver

Smart cameras are key sensors in Internet of Things (IoT) applications and often capture highly sensitive information. Therefore, security and privacy protection is a key concern. This paper introduces a lightweight security approach for smart camera IoT applications based on elliptic-curve (EC) signcryption that performs data signing and encryption in a single step. We deploy signcryption to efficiently protect sensitive data onboard the cameras and secure the data transfer from multiple cameras to multiple monitoring devices. Our multi-sender/multi-receiver approach provides integrity, authenticity, and confidentiality of data with decryption fairness for multiple receivers throughout the entire lifetime of the data. It further provides public verifiability and forward secrecy of data. Our certificateless multi-receiver aggregate-signcryption protection has been implemented for a smart camera IoT scenario, and the runtime and communication effort has been compared with single-sender/single-receiver and multi-sender/single-receiver setups.

scholarly journals Identification of Information Leakage and Guilt Agent by using MAC-IP Binding and Recursive Partitioning Algorithm to Modulate the Uncertainty in the Organization’s Network

2019 ◽  
Vol 9 (1) ◽  
pp. 4091-4096
Keyword(s):  
Decision Tree ◽  
Recursive Partitioning ◽  
Information Leakage ◽  
Third Party ◽  
Sensitive Information ◽  
Sensitive Data ◽  
The Third ◽  
Partitioning Algorithm ◽  
The Third Party ◽  
Modern Era

In this modern era, all organizations depend on internet and data so, maintaining of all data is done by the third party in large organizations. But in this present on-developing world, one have to share the data inside or outside the organization which incorporates the sensitive data of the venture moreover. Data of the organization have sensitive data which should not share with any others but unfortunately, that data was there in the third party hands so; we need to protect the data and also have to identify the guilt agent. For this, we propose a model that would evaluate and correctly identifies guilt agents, for which a recursive partitioning has been created which is a decision tree that spills data in to the sub partitions and does the easiest way to get alert and at least one specialist or it can autonomously accumulate by some different means. The main intention of the model is to secure sensitive information by recognizing the leakage and distinguish the guilt agent.

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