scholarly journals Top-K search scheme on encrypted data in cloud

2020 ◽  
Vol 9 (1) ◽  
pp. 67
Author(s):  
Katari Pushpa Rani ◽  
L. Lakshmi ◽  
Ch. Sabitha ◽  
B. Dhana Lakshmi ◽  
S. Sreeja
Keyword(s):  
Index Structure ◽  
Search Problem ◽  
Sensitive Information ◽  
Sensitive Data ◽  
Cloud Data ◽  
Security Issues ◽  
The People ◽  
Important Concern ◽  
Ranked Search ◽  
Information Retrieval Methods

<span>A Secure and Effective Multi-keyword Ranked Search Scheme on Encrypted Cloud Data. Cloud computing is providing people a very good knowledge on all the popular and relevant domains which they need in their daily life. For this, all the people who act as Data Owners must possess some knowledge on Cloud should be provided with more information so that it will help them to make the cloud maintenance and administration easy. And most important concern these days is privacy. Some sensitive data exposed in the cloud these days have security issues. So, sensitive information ought to be encrypted earlier before making the data externalized for confidentiality, which makes some keyword-based information retrieval methods outdated. But this has some other problems like the usage of this information becomes difficult and also all the ancient algorithms developed for performing search on these data are not so efficient now because of the encryption done to help data from breaches. In this project, we try to investigate the multi- keyword top-k search problem for encryption against privacy breaks and to establish an economical and secure resolution to the present drawback. we have a tendency to construct a special tree-based index structure and style a random traversal formula, which makes even identical question to supply totally different visiting ways on the index, and may additionally maintain the accuracy of queries unchanged below stronger privacy. For this purpose, we take the help of vector area models and TFIDF. The KNN set of rules are used to develop this approach.</span>

scholarly journals Secure and Dynamic Multi-Keyword Ranked Search Scheme Over Encrypted Cloud Data Using K-Means Clustering

2019 ◽  
pp. 230-235
Author(s):  
Tarika P. Jawale ◽  
R. B. Mapari
Keyword(s):  
Cloud Computing ◽  
Information Needs ◽  
Document Retrieval ◽  
Index Structure ◽  
Sensitive Information ◽  
Cloud Data ◽  
Index Vector ◽  
Ranked Search ◽  
Information Dynamic ◽  
Cloud Servers

A Secure and Dynamic Multi-keyword graded Search theme over Encrypted Cloud information attributable to the increasing fame of cloud computing, a lot of information homeowners are spurred to source their information to cloud servers for unimaginable accommodation and diminished expense in information management can also perform information dynamic operations on files. On the opposite hand, sensitive information needs to be encrypted before outsourcing for security conditions, that obsoletes information use like keyword-based document retrieval. A protected multi-keyword graded search theme over encrypted cloud information, that all the whereas underpins part update operations like deletion and insertion of documents. Especially, the vector area model and therefore the usually utilised TF_IDF model are consolidated as a neighbourhood of the index development and question generation. A unique tree-based index structure employing a "K-means Clustering" formula to provide practiced multi-keyword graded search. The secure KNN formula is employed to cipher the index and question vectors, so guarantee precise importance score calculation between encrypted index and question vectors. With a selected finish goal to oppose measurable attacks, phantom terms are accessorial to the index vector for glaring search results. Due to the employment of our exceptional tree-based index structure. Keyword: Reduplication, Authorized duplicate check, public auditing, shared data, Cloud computing.

scholarly journals Enhanced Security for Dynamic Multi Keyword Ranked Search Using Greedy Best First Search

2019 ◽  
pp. 74-78
Author(s):  
Bibin Baby ◽  
Sharmila Banu
Keyword(s):  
Keyword Search ◽  
Search Algorithm ◽  
Security And Privacy ◽  
Index Structure ◽  
Sensitive Data ◽  
Cloud Data ◽  
Encryption Schemes ◽  
Query Generation ◽  
Ranked Search ◽  
Best First Search

Today, due to the enormous growth of data technology in cloud computing, the data owners are stimulated to outsource their data in data management to reduce cost and for the convenient. Data confidentiality, in general, can be obtained by encrypting the data before it is outsourced. The client stores the encrypted data to the cloud using Searchable encryption schemes and applies keyword search techniques over cipher text domain. But the main problem in outsourcing is the lack of security and privacy for the sensitive data. So, to overcome this, for privacy requirement, the sensitive data can be encrypted before it is outsourced. Various methods were proposed to preserve the privacy and to provide security to the cloud data which are encrypted. Here in this paper, we proposed a tree-based search method over the encrypted datain the cloud that supports dynamic operation and multi-keyword ranked search. Clearly, the commonly used “inverse document frequency (IDF) term frequency (TF)” model and the vector space method are joined in the query generation and index creation to give multi-keyword ranked search. To get high search efficiency, a tree-type index structure, “Greedy Best-first Search” algorithm is proposed based on the tree- index.

scholarly journals Securing Cloud Data using RSA Algorithm

2018 ◽  
Vol 6 (4) ◽  
pp. 96
Author(s):  
Md Equebal Hussain ◽  
Mohammad Rashid Hussain
Keyword(s):  
Storage Capacity ◽  
Internet Security ◽  
Third Party ◽  
Combined Method ◽  
Cloud Data ◽  
Security Issues ◽  
Rsa Algorithm ◽  
Private Key ◽  
Important Concern ◽  
Encryption Algorithms

security is one of the most important concern on cloud computing therefore institutions are hesitating to host their data over cloud. Not all data can be afforded to move on the cloud (example accounts data). The main purpose of moving data over cloud is to reduce cost (infrastructure and maintenance), faster performance, easy upgrade, storage capacity but at the same time security is major concern because cloud is not private but maintained by third party over the internet, security issues like privacy, confidentiality, authorization (what you are allowed to do), authentication (who you are) and accounting (what you actually do) will be encountered. Variety of encryption algorithms required for higher level of security. In this paper we try to provide solution for better security by proposing a combined method of key exchange algorithm with encryption technique. Data stored in cloud can be protected from hackers using proposed solution because even if transmitted key is hacked of no use without user’s private key.

Security Flaws and Design Issues in Cloud Infrastructure

2019 ◽  
pp. 52-61
Keyword(s):  
Cloud Computing ◽  
Cloud Service ◽  
Vital Role ◽  
Sensitive Information ◽  
Cloud Infrastructure ◽  
Cloud Data Center ◽  
Sensitive Data ◽  
Cloud Service Provider ◽  
Cloud Data ◽  
Malicious Intent

Information security plays a vital role in cloud computing. Sensitive information should be kept in secure mode for providing integrity and confidentiality from insiders and outsiders. An insider is an employee who has legitimate access to cloud resources which are hosted at cloud data center. They can perform malicious activities on consumer sensitive data with or without malicious intent. This security beach is obvious and the provider needs to protect from such attacks. In this chapter, insider attacks are demonstrated with empirical approach to breach consumer-sensitive data. In this chapter, the authors present the threat models where an insider can manipulate user VMs in the node controller of cloud platform. Here, they assume that cloud service provider is malicious and cloud consumer does not have any security constraints to access their cloud assets. The model described two locations in the cloud infrastructure.

scholarly journals Protecting sensitive information utilizing an efficient association representative rule concealing algorithm for imbalance dataset

2019 ◽  
Vol 15 (1) ◽  
pp. 527
Author(s):  
Mylam Chinnappan Babu ◽  
Sankaralingam Pushpa
Keyword(s):  
Data Mining ◽  
Privacy Protection ◽  
Sensitive Information ◽  
Human Society ◽  
Resonance Theory ◽  
Sensitive Data ◽  
Adaptive Resonance ◽  
The People ◽  
Direct Discrimination ◽  
Indirect Discrimination

<span>In data mining, discrimination is the detrimental behavior of the people which is extensively studied in human society and economical science. However, there are negative perceptions about the data mining. Discrimination has two categories; one is direct, and another is indirect. The decisions depend on sensitive information attributes are named as direct discrimination, and the decisions which depend on non-sensitive information attributes are called as indirect discrimination which is strongly related with biased sensitive ones. Privacy protection has become another one of the most important problems in data mining investigation.  To overcome the above issues, an Efficient Association Representative Rule Concealing (EARRC) algorithm is proposed to protect sensitive information or knowledge and offer privacy protection with the classification of the sensitive data. Representative rule concealing is one kind of the privacy-preserving mechanisms to hide sensitive association rules. The objective of this paper is to reduce the alternation of the original database and perceive that there is no sensitive association rule is obtained. The proposed method hides the sensitive information by altering the database without modifying the support of the sensitive item. The EARRC is a type of association classification approach which integrates the benefits of both associative classification and rule-based PART (Projective Adaptive Resonance Theory) classification. Based on Experimental computations, proposed EARRC+PART classifier improves 1.06 NMI and 5.66 Accuracy compared than existing methodologies.</span>

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 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 An Autonomous Cybersecurity Framework for Next-generation Digital Service Chains

2021 ◽  
Vol 29 (4) ◽  
Author(s):  
Matteo Repetto ◽  
Domenico Striccoli ◽  
Giuseppe Piro ◽  
Alessandro Carrega ◽  
Gennaro Boggia ◽  
...  
Keyword(s):  
Business Models ◽  
Identity Management ◽  
Methodological Approach ◽  
Value Chains ◽  
Sensitive Data ◽  
Digital Service ◽  
Security Issues ◽  
Security Services ◽  
New Business ◽  
Access Control Management

AbstractToday, the digital economy is pushing new business models, based on the creation of value chains for data processing, through the interconnection of processes, products, services, software, and things across different domains and organizations. Despite the growing availability of communication infrastructures, computing paradigms, and software architectures that already effectively support the implementation of distributed multi-domain value chains, a comprehensive architecture is still missing that effectively fulfills all related security issues: mutual trustworthiness of entities in partially unknown topologies, identification and mitigation of advanced multi-vector threats, identity management and access control, management and propagation of sensitive data. In order to fill this gap, this work proposes a new methodological approach to design and implement heterogeneous security services for distributed systems that combine together digital resources and components from multiple domains. The framework is designed to support both existing and new security services, and focuses on three novel aspects: (i) full automation of the processes that manage the whole system, i.e., threat detection, collection of information and reaction to attacks and system anomalies; (ii) dynamic adaptation of operations and security tasks to newest attack patterns, and (iii) real-time adjustment of the level of detail of inspection and monitoring processes. The overall architecture as well as the functions and relationships of its logical components are described in detail, presenting also a concrete use case as an example of application of the proposed framework.

scholarly journals Efficient Retrieval of Music Recordings Using Graph-Based Index Structures

Signals ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 336-352
Author(s):  
Frank Zalkow ◽  
Julian Brandner ◽  
Meinard Müller
Keyword(s):  
Nearest Neighbor ◽  
Response Times ◽  
Negative Impact ◽  
Nearest Neighbor Search ◽  
Index Structure ◽  
Search Problem ◽  
Index Structures ◽  
Music Retrieval ◽  
Retrieval Systems ◽  
Music Recordings

Flexible retrieval systems are required for conveniently browsing through large music collections. In a particular content-based music retrieval scenario, the user provides a query audio snippet, and the retrieval system returns music recordings from the collection that are similar to the query. In this scenario, a fast response from the system is essential for a positive user experience. For realizing low response times, one requires index structures that facilitate efficient search operations. One such index structure is the K-d tree, which has already been used in music retrieval systems. As an alternative, we propose to use a modern graph-based index, denoted as Hierarchical Navigable Small World (HNSW) graph. As our main contribution, we explore its potential in the context of a cross-version music retrieval application. In particular, we report on systematic experiments comparing graph- and tree-based index structures in terms of the retrieval quality, disk space requirements, and runtimes. Despite the fact that the HNSW index provides only an approximate solution to the nearest neighbor search problem, we demonstrate that it has almost no negative impact on the retrieval quality in our application. As our main result, we show that the HNSW-based retrieval is several orders of magnitude faster. Furthermore, the graph structure also works well with high-dimensional index items, unlike the tree-based structure. Given these merits, we highlight the practical relevance of the HNSW graph for music information retrieval (MIR) applications.

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