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 AN EFFICIENT SECURITY FRAMEWORK FOR DATA MIGRATION IN A CLOUD COMPUTING ENVIRONMENT

2019 ◽  
Vol 01 (01) ◽  
pp. 45-53 ◽  
Author(s):  
Subarna Shakya
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Privacy Protection ◽  
Credit Card ◽  
Security Analysis ◽  
Data Encryption ◽  
Security And Privacy ◽  
Data Migration ◽  
Secure Socket Layer ◽  
Sensitive Data

Cloud computing is advantageous in several applications. Data migration is constantly carried out to hybrid or public cloud. Certain large enterprises will not move their business-critical data and applications to the cloud. This is due to the concerns regarding data security and privacy protection. In this paper, we provide a data security analysis and solution for privacy protection framework during data migration. A Secure Socket Layer (SSL) is established and migration tickets with minimum privilege is introduced. Further, data encryption is done using Prediction Based Encryption (PBE). This system will be of use for healthcare systems and e-commerce systems that can store data regarding credit card details. We provide a strict separation between sensitive and non-sensitive data and provide encryption for the sensitive data.

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 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 Security and Privacy Issues of IoT at Fog Layer Architecture

2021 ◽  
Author(s):  
Vinay Michael
Keyword(s):  
Data Encryption ◽  
Security And Privacy ◽  
Delivery Ratio ◽  
User Privacy ◽  
Sensitive Data ◽  
Limited Bandwidth ◽  
Cipher Text ◽  
Computational Overhead ◽  
Encryption And Decryption ◽  
Encryption Decryption

Abstract Internet of Things (IoT) based applications and systems are gaining attention in the recent days because of their vast benefits such as efficient utilization of resources, enhanced data collection, improved security, lesser human efforts and reduced time. Security of sensitive data in IoT based fog environments is inevitable to prevent those data to be misused by the attackers. In this study, we present an improved hybrid algorithm termed as HQCP-ABE (Hybrid Quantum key Cipher text Policy Attribute based Encryption with Cipher text update) that integrates highly effective algorithms such as CP-ABE, Quantum key cryptography and cipher text update. The proposed algorithm eliminates the need of costly pairing during decryptions and efficiently performs data encryption, decryption and user authorization. The proposed protocol is demonstrated to be highly efficient in terms of encryption and decryption while compared to other existing methods. It also achieves lesser packet loss, reduced control overheads, reduced computational overhead during encryption and decryption processes, lesser delay, improved security, packet delivery ratio, throughput, network lifetime with limited bandwidth and user privacy. We further considered energy consumption in this study. The proposed HQCP-ABE method is demonstrated using ns3 simulation and compared with existing CP-ABE and PA-CPABE methods.

scholarly journals Authorization of Data In Hadoop Using Apache Sentry

2018 ◽  
Vol 7 (3.6) ◽  
pp. 234 ◽  
Author(s):  
N Sirisha ◽  
K V.D. Kiran
Keyword(s):  
Big Data ◽  
Data Security ◽  
Data Encryption ◽  
Security Model ◽  
Huge Amount ◽  
Sensitive Data ◽  
Major Drawback ◽  
Security Issues ◽  
On Demand ◽  
Increasing Trend

Big Data has become more popular, as it can provide on-demand, reliable and flexible services to users such as storage and its processing. The data security has become a major issue in the Big data. The open source HDFS software is used to store huge amount of data with high throughput and fault tolerance and Map Reduce is used for its computations and processing. However, it is a significant target in the Hadoop system, security model was not designed and became the major drawback of Hadoop software. In terms of storage, meta data security, sensitive data  and also the data security will be an serious issue in HDFS. With the importance of Hadoop in today's enterprises, there is also an increasing trend in providing a high security features in enterprises. Over recent years, only some level of security in Hadoop such as Kerberos and Transparent Data Encryption(TDE),Encryption techniques, hash techniques are shown for Hadoop. This paper, shows the efforts that are made to present Hadoop Authorization security issues using Apache Sentry in HDFS. 

scholarly journals Securing Personal Health Records using Advanced Multi-Factor Authentication in Cloud Computing

2020 ◽  
Vol 8 (6) ◽  
pp. 5133-5140
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Data Access ◽  
Data Encryption ◽  
Personal Health Records ◽  
Security And Privacy ◽  
Healthcare Sector ◽  
Personal Health ◽  
Health Records ◽  
Wrong Decision

Cloud computing is a novel prototype to provide services via the internet. Most of the fields like banking, industries, educational institutions, and healthcare are storing their applications, data and accessing it through cloud because of its versatility and affordable price. Even though cloud has a many special feature, data security and privacy are the most important issues in a cloud background. Especially in healthcare sector, according to recent report numerous amount of healthcare data breached by unknown websites and hackers, and much healthcare information breaches are occurring around the world for different purposes and still it is vulnerable on account of storing and accessing data through third party cloud servers. Due to many attacks on personal health records data security and privacy in cloud environment, it is a primary task to concentrate on solving this issue because such health information are really sensitive, and playing vital role in decision-making of patients health which wrong decision may spoil patient’s health, life along with health institution’s reputation. To ensure security and privacy, data encryption and authentication are the key technologies which are a technique to secure data and create proof identities to obtain access of data in the system. Conventional password authentication does not provide sufficient security for information to the new means of attacks. So, this paper introduces a framework for data encryption using standard RSA and Hash function and advanced multi factor authentication technique to cloud data access which authenticates the user based on different factors such as contextual, signcryption and iris bio-metric features. This prototype to cloud computing is implemented using open source technology. The proposed advanced system minimizes intermediate data access due to the complexity of key access and strong authentication. The performance of the system has been evaluated using experimental results such as encryption and decryption time, authentication accuracy, execution time.

scholarly journals Integration of Blockchain with Connected and Autonomous Vehicles: Vision and Challenge

2022 ◽  
Vol 14 (1) ◽  
pp. 1-10
Author(s):  
Tooska Dargahi ◽  
Hossein Ahmadvand ◽  
Mansour Naser Alraja ◽  
Chia-Mu Yu
Keyword(s):  
Data Protection ◽  
Intelligent Transportation Systems ◽  
Data Security ◽  
Autonomous Vehicles ◽  
Personal Data ◽  
Transportation Systems ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Blockchain Technology ◽  
Wide Range

Connected and Autonomous Vehicles (CAVs) are introduced to improve individuals’ quality of life by offering a wide range of services. They collect a huge amount of data and exchange them with each other and the infrastructure. The collected data usually includes sensitive information about the users and the surrounding environment. Therefore, data security and privacy are among the main challenges in this industry. Blockchain, an emerging distributed ledger, has been considered by the research community as a potential solution for enhancing data security, integrity, and transparency in Intelligent Transportation Systems (ITS). However, despite the emphasis of governments on the transparency of personal data protection practices, CAV stakeholders have not been successful in communicating appropriate information with the end users regarding the procedure of collecting, storing, and processing their personal data, as well as the data ownership. This article provides a vision of the opportunities and challenges of adopting blockchain in ITS from the “data transparency” and “privacy” perspective. The main aim is to answer the following questions: (1) Considering the amount of personal data collected by the CAVs, such as location, how would the integration of blockchain technology affect transparency , fairness , and lawfulness of personal data processing concerning the data subjects (as this is one of the main principles in the existing data protection regulations)? (2) How can the trade-off between transparency and privacy be addressed in blockchain-based ITS use cases?

Analysis of the Join Performance in Vertically Distributed Cloud Databases

2015 ◽  
Vol 6 (2) ◽  
pp. 65-87 ◽  
Author(s):  
Jens Kohler ◽  
Kiril Simov ◽  
Thomas Specht
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Security And Privacy ◽  
Sensitive Data ◽  
Public And Private ◽  
Huge Data ◽  
Cloud Databases ◽  
Accounting Model ◽  
Privacy Constraints ◽  
Distributed Cloud

Cloud Computing becomes interesting for enterprises across all branches. Renting computing capabilities from external providers avoids initial investments, as only those resources have to be paid that were used eventually. Especially in the context of “Big Data” this pay-as-you-go accounting model is particularly important. The dynamically scalable resources from the Cloud enable enterprises to store or analyze these huge amounts of unstructured data without using their own hardware infrastructure. However, Cloud Computing is currently facing severe data security and protection issues. These challenges require new ways to store and analyze data, especially when huge data volumes with sensitive data are stored at external locations. The presented approach separates data on database table level into independent chunks and distributes them across several clouds. Hence, this work is a contribution to a more secure and resilient cloud architecture as multiple public and private cloud providers can be used independently to store data without losing data security and privacy constraints.

Optimal Key Generation for Data Sanitization and Restoration of Cloud Data: Future of Financial Cyber Security

2020 ◽  
Vol 19 (04) ◽  
pp. 987-1013
Author(s):  
B. Balashunmugaraja ◽  
T. R. Ganeshbabu
Keyword(s):  
Cyber Security ◽  
Privacy Preservation ◽  
Service Sector ◽  
Scale Up ◽  
Cloud Security ◽  
Sensitive Information ◽  
Key Generation ◽  
Sensitive Data ◽  
Data Sanitization ◽  
Data Restoration

Cloud security in finance is considered as the key importance, taking account of the aspect of critical data stored over cloud spaces within organizations all around the globe. They are chiefly relying on cloud computing to accelerate their business profitability and scale up their business processes with enhanced productivity coming through flexible work environments offered in cloud-run working systems. Hence, there is a prerequisite to contemplate cloud security in the entire financial service sector. Moreover, the main issue challenged by privacy and security is the presence of diverse chances to attack the sensitive data by cloud operators, which leads to double the user’s anxiety on the stored data. For solving this problem, the main intent of this paper is to develop an intelligent privacy preservation approach for data stored in the cloud sector, mainly the financial data. The proposed privacy preservation model involves two main phases: (a) data sanitization and (b) data restoration. In the sanitization process, the sensitive data is hidden, which prevents sensitive information from leaking on the cloud side. Further, the normal as well as the sensitive data is stored in a cloud environment. For the sanitization process, a key should be generated that depends on the new meta-heuristic algorithm called crossover improved-lion algorithm (CI-LA), which is inspired by the lion’s unique social behavior. During data restoration, the same key should be used for effectively restoring the original data. Here, the optimal key generation is done in such a way that the objective model involves the degree of modification, hiding rate, and information preservation rate, which effectively enhance the cyber security performance in the cloud.

scholarly journals Data Security in Cloud Computing Using Elliptic Curve Cryptography

2020 ◽  
Author(s):  
Rosheen Qazi ◽  
Imran A. Khan
Keyword(s):  
Cloud Computing ◽  
Elliptic Curve ◽  
Data Security ◽  
Elliptic Curve Cryptography ◽  
Large Data ◽  
Data Encryption ◽  
Computational Power ◽  
Sensitive Data ◽  
Encrypt Data ◽  
Asymmetric Encryption

Encryption helps in transmitting sensitive data over an insecure channel without any danger of data being lost or being manipulated by some unauthorized entity. Different Encryption schemes have been applied for Data security in a different environment. Many cryptosystems worked during different eras and evolved accordingly with time. This paper mainly focuses on asymmetric encryption which is also known as Public key encryption scheme or Holomorphic encryption. However, due to large key size asymmetric encryption is mostly used for Key exchange rather than data Encryption. Nowadays, Data security is the main issue in large data centers and Cloud computing. This paper uses Elliptic Curve Cryptography to encrypt data in the cloud environment because the size of the key used in Elliptic Curve Cryptography is very small. Due to the small key size of Elliptic Curve, computational power is reduced and this results into least energy consumption. This paper shows that elliptic curve cryptography is fast and more efficient for data protection in a cloud computing environment and reduces the computational power and also increases the efficiency.

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