Privacy in Web Service Transactions: A Tale of More than a Decade of Work

Bahri, Leila; Carminati, Barbara; Ferrari, Elena

doi:10.1109/tsc.2017.2711019

Cited by 8 publications

(7 citation statements)

References 40 publications

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“…FP % and FN %, as shown in Table 9, express the false positive and false negative percentage values. Users' trust based on the prediction of instances within the users' trust level (FP %) was demonstrated in terms of selection cum ranking score, which is calculated by using equation (2). Furthermore, we computed untrusted users using equation (3).…”

Section: Resultsmentioning

confidence: 99%

“…Web services description language (WSDL) is another standard that is widely used as guidelines for web services. Moreover, 'single object access protocol' (SOAP) is an accepted standard for messages in web services [2].…”

Section: Introductionmentioning

confidence: 99%

“…Web services technology is becoming prevalent and popular due to numerous advantages, including, but not limited to, interoperability, composability, and reusability [2][3]. This has led the world's leading companies, such as Facebook and Google, to provide services and applications in the form of web services [3].…”

Section: Introductionmentioning

confidence: 99%

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Machine Learning Methods for Trust-based Selection of Web Services

2022

KSII TIIS

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Web services instances can be classified into two categories, namely trusted and untrusted from users. A web service with high throughput (TP) and low response time (RT) instance values is a trusted web service. Web services are not trustworthy due to the mismatch in the guaranteed instance values and the actual values achieved by users. To perform web services selection from users' attained TP and RT values, we need to verify the correct prediction of trusted and untrusted instances from invoked web services. This accurate prediction of web services instances is used to perform the selection of web services. We propose to construct fuzzy rules to label web services instances correctly. This paper presents web services selection using a well-known machine learning algorithm, namely REPTree, for the correct prediction of trusted and untrusted instances. Performance comparison of REPTree with five machine learning models is conducted on web services datasets. We have performed experiments on web services datasets using a ten k-fold cross-validation method. To evaluate the performance of the REPTree classifier, we used accuracy metrics (Sensitivity and Specificity). Experimental results showed that web service (WS1) gained top selection score with the (47.0588%) trusted instances, and web service (WS2) was selected the least with (25.00%) trusted instances. Evaluation results of the proposed web services selection approach were found as (asymptotic sig. = 0.019), demonstrating the relationship between final selection and recommended trust score of web services.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Machine Learning Methods for Trust-based Selection of Web Services

2022

KSII TIIS

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“…Smullen D et al [18] use eddy to analysts and express requirements over data practices, detect conflicting requirements and to trace data flows within and across specifications. Bahri L et al [19] explored the available literature on web services privacy during transactions, identified 20 works that address privacy related problems in web services consumption, and proposed evaluation framework.…”

Section: Related Work Description and Modeling Of Privacy Requirementmentioning

confidence: 99%

Composite Service-Oriented Minimum Privacy Disclosure Method

Ke¹,

Huang²,

Liu³

2018

dtcse

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Service composition has become a main application to satisfy user functional requirements. To assure user privacy information not being disclosed, using the user minimum privacy data set when providing application, is a research focus of privacy enhancement technology in the process of service composition. In this paper, first, we describe and discrete the continuous privacy data. Second, through privacy sensitive analysis and service availability analysis, we obtain the minimum privacy disclosure data set to protect user privacy information. In the end, we prove the feasibility and correctness of our method with case study.

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“…Semantic Web amenitiesare autonomous sectional applications that can be broadcasted, located and applicable to the entire Web with a searchable and inventive interface to provide a given consumable functionality over a given network using some standard protocols [1].…”

Section: Introductionmentioning

confidence: 99%

Semantic Web Services: An Empirical Methodology to Security

Nayak*,

Singh

2019

IJEAT

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In today's modern era, the Semantic Web is progressing at a tremendous speed. The Semantic Web services have opened new possibilities through which any one can avail various services. But if these technologies are not properly protected, then their use can put users in danger. Many people have to face difficulty in assessing the security hazards allied with Semantic Web services. Many Web services such as e-commerce stores various types of data on their database servers. These database servers are distributed across the globe. The e-commerce may use the unalike assortments of database for storing different information. Web services such as e-commerce have to handle assorted types of data. Unalike Web services like e-commerce have to handle assorted types of data. A single database program will not be suitable for storing and processing mixed types of data as it will increase the processing overhead and ultimately reduce the performance of the web service. So there is need arises to define an apposite subclass of databases for each document type.This paper insinuates a set of databases for each type of documents stored on an e-commerce platform. An exertion has been made to define a proper set of database programs for a web service such as e-commerce that adequately manages the requirements of a particular type of data. The tryouts have been steered for an e-commerce Web service for weighing the efficacy of the proposed approach. The results shows that if wellstructured database has been used for a Web service such as ecommerce then response can be very quick and chances of packet loss will also be very low. If network attacks such as DoS and man-in-the-middle attack exist within the request, the performance of the Web service severely affected. A network attack may lead to the more chances of packet loss. The paper also delineates the impact of network attacks on web service performance

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Privacy in Web Service Transactions: A Tale of More than a Decade of Work

Cited by 8 publications

References 40 publications

Machine Learning Methods for Trust-based Selection of Web Services

Machine Learning Methods for Trust-based Selection of Web Services

Composite Service-Oriented Minimum Privacy Disclosure Method

Semantic Web Services: An Empirical Methodology to Security

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