An enhanced graph-based semi-supervised learning algorithm to detect fake users on Twitter

BalaAnand, M.; Karthikeyan, N.; Karthik, S.; Varatharajan, R.; Manogaran, Gunasekaran; Sivaparthipan, C. B.

doi:10.1007/s11227-019-02948-w

Cited by 79 publications

(20 citation statements)

References 23 publications

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“…The experiments show they were almost successful in identifying spammers from non-spammers. BalaAnand et al [19] developed a new system to detect fake users on the Twitter platform using a graph-based semi-supervised learning algorithm (EGSLA) and analyze and gathering behavioral and user-generated content (UGC) information. The model first collected users' information, analyzed them to extract useful features, and then performed classification on these features and made decisions.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Method for Detection of Fake Accounts on the Instagram Platform

Sheikhi¹

2020

RIA

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In recent years, social media platforms such as Instagram, Twitter, and Facebook have gradually become important ways to disseminate information. One of these social platforms that have attracted more attention in past years is Instagram. Instagram has widely used for sharing photos and videos and is profitable for celebrities, businesses, and people with a considerable number of followers. In the meantime, this high profit made this platform prone to be the potential place to be used for malicious activities. One of the essential malicious activities in the Instagram platform is fake accounts. However, in this paper, an efficient method for identifying Instagram fake accounts is proposed. In the presented model. First, a dataset of legitimate and fake accounts is created. Then, the collected dataset has been used as input of the bagging classifier to classify fake users on the dataset. Furthermore, the proposed method compared to the five well-known machine-learning classifiers in terms of classification accuracy to better evaluate effectiveness of the method. The experimental results show that the proposed method performs better than other considered algorithms and correctly classified over 98% of the accounts with a low error rate.

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Section: Related Workmentioning

confidence: 99%

An Efficient Method for Detection of Fake Accounts on the Instagram Platform

Sheikhi¹

2020

RIA

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“…The task force proposed a set of rules for transferring power system data stored in a database. 18 Even though the protocol provides a standard way of representing power system data, it does not provide a solution to the legacy issues associated with real-time power system monitoring in a distributed platform. Over a decade, the power system researchers concentrate on internet-based supervisory control and data acquisition system to control power system operations.…”

Section: Introductionmentioning

confidence: 99%

“…The Power System Analytical Data Task had developed dictionary of power system data containing definitions of power system terms. The task force proposed a set of rules for transferring power system data stored in a database 18 . Even though the protocol provides a standard way of representing power system data, it does not provide a solution to the legacy issues associated with real‐time power system monitoring in a distributed platform.…”

Section: Introductionmentioning

confidence: 99%

Enhanced data communication models for real‐time power system monitoring in a distributed platform

Kannan

Thomas

Mobarak

et al. 2020

Trans Emerging Tel Tech

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The novelty behind this research is to develop enhanced models for real-time power system monitoring in a platform-independent and distributed platform. Distributed models for power system applications have been implemented using Remote Method Invocation (RMI), Common object Request Broker Architecture and. NET remoting technologies. The interoperability among the heterogeneous power system clients in a distributed platform has been achieved through XMLization of power system data which provides meaningful solution to the legacy issues associated with power systems. A RMI-based model for real-time power system monitoring in a distributed platform had been implemented and discussed in detail. A component model for real-time power system monitoring has also been proposed and implemented to increase the reusability and scalability of the system. A location transparent model has been developed using Common object Request Broker Architecture with RMI-Internet Inter-Orb Protocol for load flow monitoring and the idea is extended to solve real-time economic load dispatch and dynamic security monitoring. The detailed monitoring on performance of the proposed models has been done with load flow monitoring, dynamic security monitoring and economic load dispatch problems. A. NET remoting architectural model has been developed for real-time economic load dispatch in a distributed platform. This research paper explores various issues in deploying power system applications in a distributed platform. It will serve the purpose of stimulating interest among power engineers and also will be extremely useful for electric power utilities.

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“…In common practice, the user could search or retrieve data of his/her interests utilizing any related keywords . The unavailability of preferred search with privacy preserved and flexible search query support is still a typical shortage in prevailing search engine (SE) strategies …”

Section: Introductionmentioning

confidence: 99%

“…14 The unavailability of preferred search with privacy preserved and flexible search query support is still a typical shortage in prevailing search engine (SE) strategies. 15,16 The draft structure for this paper is systematized as follows: Section 2 surveys the associated works regarding the method proposed. In Section 3, a brief discussion about the proposed methodology is proffered, Section 4 explores the investigational outcome, and Section 5 briefly concludes the paper.…”

Section: Introductionmentioning

confidence: 99%

Secure and privacy‐preserving keyword search retrieval over hashed encrypted cloud data

Sathyabalaji¹,

Komarasamy

S³

2019

Int J Communication

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Summary Cloud computing (CC) is the universal area in which the data owners will contract out their pertinent data to the untrusted public cloud that permits the data users to retrieve the data with complete integrity. To give data privacy along with integrity, majority of the research works were concentrated on single data owner for secure searching of encrypted data via the cloud. Also, searchable encryption supports data user to retrieve the particular encrypted document from encrypted cloud data via keyword search (KS). However, these researches are not efficient for keyword search retrieval. To trounce such drawbacks, this paper proposes efficient secure and privacy‐preserving keyword search retrieval (SPKSR) system, in which the user retrieves the hashed encrypted documents over hashed encrypted cloud data. The proposed system includes three entities explicitly, (a) data owner (DO), (b) cloud server (CS), and (c) data users (DU). The owner outsources hashed encrypted documents set, along with generated searchable index tree to the CS. The CS hoards the hashed encrypted document collection and index tree structure. DU performs the “search” over the hashed encrypted data. Experimental results of the proposed system are analyzed and contrasted with the other existent system to show the dominance of the proposed system.

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An enhanced graph-based semi-supervised learning algorithm to detect fake users on Twitter

Cited by 79 publications

References 23 publications

An Efficient Method for Detection of Fake Accounts on the Instagram Platform

An Efficient Method for Detection of Fake Accounts on the Instagram Platform

Enhanced data communication models for real‐time power system monitoring in a distributed platform

Secure and privacy‐preserving keyword search retrieval over hashed encrypted cloud data

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