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Future Internet
Special Issues
Cybersecurity and Cybercrime in the Age of Social Media
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Cybersecurity and Cybercrime in the Age of Social Media

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Cybersecurity".

Deadline for manuscript submissions: closed (21 April 2023) | Viewed by 11814

Special Issue Editors

Dr. Joel Scanlan

E-Mail Website
Guest Editor
Australian Institute of Health Service Management (AIHSM), University of Tasmania, Hobart, TAS 7005, Australia
Interests: cyber security; digital health; maritime
Prof. Dr. Paul A. Watters

E-Mail Website
Guest Editor
School of Engineering and Mathematical, Sciences La Trobe University Melbourne, Melbourne, VIC, Australia
Interests: cybercrime; cybersecurity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Social media has become a dominant platform for connecting users and sharing data, which in turn has resulted in it being a ‘place’ for bad actors to violate individuals’ privacy and commit crimes. The power of big data and artificial intelligence, coupled with the mass acceptance and usage of the platforms, has changed the attack surface of society. Social engineering, enabled by AI built into social media platforms, enables deep access into users’ lives, and can be leveraged by bad actors. This has increased the need for a focus on online safety, and for ensuring that the vulnerable are protected.

This Special Issue aims to share research which has examined various aspects of overlap between cybersecurity and cybercrime in relation to social media. The papers can explore the negative impacts, of which there are many, or indeed positive outcomes where research conducted via social media has enabled greater awareness and protection of individuals.

Please note that all submissions should fit the primary scope of Future Internet, which includes next-generation networking, related technologies, and associated applications.

Dr. Joel Scanlan
Prof. Dr. Paul A. Watters
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cybersecurity
  • cybercrime
  • social media
  • social engineering
  • artificial intelligence
  • machine learning
  • big data
  • human factors
  • attack scenarios
  • behavioral analytics

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Published Papers (3 papers)

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Research

19 pages, 1501 KiB  
Article
Role of Attention and Design Cues for Influencing Cyber-Sextortion Using Social Engineering and Phishing Attacks
by Brent Pethers and Abubakar Bello
Future Internet 2023, 15(1), 29; https://doi.org/10.3390/fi15010029 - 7 Jan 2023
Cited by 3 | Viewed by 3337
Abstract
Cyber sextortion attacks are security and privacy threats delivered to victims online, to distribute sexual material in order to force the victim to act against their will. This continues to be an under-addressed concern in society. This study investigated social engineering and phishing [...] Read more.
Cyber sextortion attacks are security and privacy threats delivered to victims online, to distribute sexual material in order to force the victim to act against their will. This continues to be an under-addressed concern in society. This study investigated social engineering and phishing email design and influence techniques in susceptibility to cyber sextortion attacks. Using a quantitative methodology, a survey measured susceptibility to cyber sextortion with a focus on four different email design cues. One-way repeated measures ANOVA, post hoc comparison tests, Friedman nonparametric test, and Spearman correlation tests were conducted with results indicating that attention to email source and title/subject line significantly increased individuals’ susceptibility, while attention to grammar and spelling, and urgency cues, had lesser influence. As such, the influence of these message-related factors should be considered when implementing effective security controls to mitigate the risks and vulnerabilities to cyber sextortion attacks. Full article
(This article belongs to the Special Issue Cybersecurity and Cybercrime in the Age of Social Media)
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15 pages, 4257 KiB  
Article
Multimodel Phishing URL Detection Using LSTM, Bidirectional LSTM, and GRU Models
by Sanjiban Sekhar Roy, Ali Ismail Awad, Lamesgen Adugnaw Amare, Mabrie Tesfaye Erkihun and Mohd Anas
Future Internet 2022, 14(11), 340; https://doi.org/10.3390/fi14110340 - 21 Nov 2022
Cited by 19 | Viewed by 4415
Abstract
In today’s world, phishing attacks are gradually increasing, resulting in individuals losing valuables, assets, personal information, etc., to unauthorized parties. In phishing, attackers craft malicious websites disguised as well-known, legitimate sites and send them to individuals to steal personal information and other related [...] Read more.
In today’s world, phishing attacks are gradually increasing, resulting in individuals losing valuables, assets, personal information, etc., to unauthorized parties. In phishing, attackers craft malicious websites disguised as well-known, legitimate sites and send them to individuals to steal personal information and other related private details. Therefore, an efficient and accurate method is required to determine whether a website is malicious. Numerous methods have been proposed for detecting malicious uniform resource locators (URLs) using deep learning, machine learning, and other approaches. In this study, we have used malicious and benign URLs datasets and have proposed a detection mechanism for detecting malicious URLs using recurrent neural network models such as long short-term memory (LSTM), bidirectional long short-term memory (Bi-LSTM), and the gated recurrent unit (GRU). Experimental results have shown that the proposed mechanism achieved an accuracy of 97.0% for LSTM, 99.0% for Bi-LSTM, and 97.5% for GRU, respectively. Full article
(This article belongs to the Special Issue Cybersecurity and Cybercrime in the Age of Social Media)
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33 pages, 2634 KiB  
Article
Browser Forensic Investigations of Instagram Utilizing IndexedDB Persistent Storage
by Furkan Paligu and Cihan Varol
Future Internet 2022, 14(6), 188; https://doi.org/10.3390/fi14060188 - 17 Jun 2022
Cited by 1 | Viewed by 3111
Abstract
Social media usage is increasing at a rapid rate. Everyday users are leaving a substantial amount of data as artifacts in these applications. As the size and velocity of data increase, innovative technologies such as Web Storage and IndexedDB are emerging. Consequently, forensic [...] Read more.
Social media usage is increasing at a rapid rate. Everyday users are leaving a substantial amount of data as artifacts in these applications. As the size and velocity of data increase, innovative technologies such as Web Storage and IndexedDB are emerging. Consequently, forensic investigators are facing challenges to adapt to the emerging technologies to establish reliable techniques for extracting and analyzing suspect information. This paper investigates the convenience and efficacy of performing forensic investigations with a time frame and social network connection analysis on IndexedDB technology. It focuses on artifacts from prevalently used social networking site Instagram on the Mozilla Firefox browser. A single case pretest–posttest quasi-experiment is designed and executed over Instagram web application to produce artifacts that are later extracted, processed, characterized, and presented in forms of information suited to forensic investigation. The artifacts obtained from Mozilla Firefox are crossed-checked with artifacts of Google Chrome for verification. In the end, the efficacy of using these artifacts in forensic investigations is shown with a demonstration through a proof-of-concept tool. The results indicate that Instagram artifacts stored in IndexedDB technology can be utilized efficiently for forensic investigations, with a large variety of information ranging from fully constructed user data to time and location indicators. Full article
(This article belongs to the Special Issue Cybersecurity and Cybercrime in the Age of Social Media)
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