WITHDRAWN: Privacy and security issues in the future: A social media

Sushama, C.; Kumar, Manoj; Neelima, P.

doi:10.1016/j.matpr.2020.11.105

Cited by 29 publications

(19 citation statements)

References 2 publications

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“…At this point referenced underneath are segments of the pattern that are hugely movingCyber Security [8].…”

Section: Trends Changing Cyber Securitymentioning

confidence: 99%

“…In the nearbyexactingsituationa variety ofmost recentprogressionischange the embodiment of mankind. Despite, outstanding to these creating advancements, we can't ensure the privatedata in an incredibly efficientapproach and thusly, these days computerized bad behaviors areraising bit by bit [5][6][7][8]. These days more than 60% of outright business trade isthrough on the web [1], so this block necessarya high type of security for directsalong withfinest trades.…”

Section: Introductionmentioning

confidence: 99%

“…Nowadaysall nations and governments beforceful demanding laws on computerized insurances in order to maintain a strategic distance from the deficiency of some critical information. Every individual ought to moreover be set up on this cyber security and extra themselves [8] from these extending advanced bad behaviors. and cyber security due to the great demand of security reasons in civilian applications.…”

Section: Introductionmentioning

confidence: 99%

“…These application security arrangements include:• The vulnerability the executives: Manage the vulnerabilities related to in house created applications and online applications by means of checking devices, firewalls, and verifies code improvement[21]. • Mobile application the executives: User boycotting and white posting, conveyance the executives of utilizations to cell phones, and versatile application helplessness testing[8].Security Management: Raw information alone isn't sufficient to settle on educated digital security choices. The security of the board arrangements transforms unstructured information into significant knowledge.…”

mentioning

confidence: 99%

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Cyber Security and Privacy Internal Attacks Measurements Through Block Chain

Manoj¹,

Aithal²

2021

ITII

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Cyber Security plays critical role in privacy and now a day’s its assumesanimportanttask in the field of data security. Security concern Block chain gives best fruitful results to overcome unauthorized access and internal counter attacks operations| we propose new technique to reduce and identify internal privacy leaks and attack to measure with efficient manner. These technique very useful to cyber internal avoid attacks with accountability way and real-time environment operations.

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“…At this point referenced underneath are segments of the pattern that are hugely movingCyber Security [8].…”

Section: Trends Changing Cyber Securitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Cyber Security and Privacy Internal Attacks Measurements Through Block Chain

Manoj¹,

Aithal²

2021

ITII

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“…Thinking about how to detect duplicate profiles has leaded to implementing a methodology for comparing Twitter users, considering three aspects: behavioral similarity, audience similarity, and context similarity. Having the information derived from the users' comparison enables to detection of duplicate profiles, eliminates these frauds, and protects users' policies and privacy, leading to a secure virtual society to make life more comfortable, secure, and updated [13].…”

Section: Introductionmentioning

confidence: 99%

Similarity approximation of Twitter Profiles

Shoeibi¹,

Chamoso²,

Alizadehsani³

et al. 2021

Preprint

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Social media platforms are entirely an undeniable part of the lifestyle from the past decade. Analyzing the information being shared is a crucial step to understand humans behavior. Social media analysis is aiming to guarantee a better experience for the user and risen user satisfaction. But first, it is necessary to know how and from which aspects to compare users with each other. In this paper, an intelligent system has been proposed to measure the similarity of Twitter profiles. For this, firstly, the timeline of each profile has been extracted using the official Twitter API. Then, all information is given to the proposed system. Next, in parallel, three aspects of a profile are derived. Behavioral ratios are time-series-related information showing the consistency and habits of the user. Dynamic time warping has been utilized for comparison of the behavioral ratios of two profiles. Next, Graph Network Analysis is used for monitoring the interactions of the user and its audience; for estimating the similarity of graphs, Jaccard similarity is used. Finally, for the Content similarity measurement, natural language processing techniques for preprocessing and TF-IDF for feature extraction are employed and then compared using the cosine similarity method. Results have presented the similarity level of different profiles. As the case study, people with the same interest show higher similarity. This way of comparison is helpful in many other areas. Also, it enables to find duplicate profiles; those are profiles with almost the same behavior and content.

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Social Networks as Communities: Thinking the Social Fabric Against Algorithms

Gómez-Estern

Rosemberg

2021

New Waves in Social Psychology

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WITHDRAWN: Privacy and security issues in the future: A social media

Cited by 29 publications

References 2 publications

Cyber Security and Privacy Internal Attacks Measurements Through Block Chain

Cyber Security and Privacy Internal Attacks Measurements Through Block Chain

Similarity approximation of Twitter Profiles

Social Networks as Communities: Thinking the Social Fabric Against Algorithms

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