A Bibliometric Analysis of Digital Image Forensics

Gokhale, Angelina; Mulay, Preeti; Pramod, Dhanya; Kulkarni, Rachana

doi:10.1080/0194262x.2020.1714529

Cited by 31 publications

(24 citation statements)

References 29 publications

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“…The presented literature review and the subsequent argumentation reveal a rather significant hysteresis between the massively deployed research on the implementation of DIF techniques and the associated cognitive studies, focusing on the perception and real use of such practically available services. This remark is rather evident in most related (and recent) review papers and surveys (Gokhale et al, 2020;Katsaounidou, 2020;Qureshi and El-Alfy, 2019;Tariq et al, 2018;Thakur and Rohilla, 2020;Zheng et al, 2019), in which, such featured works are seldom or entirely missing. Nevertheless, limited publications nearer to the current approach do exist, such as the work of Gloe et al (2007) that examined DIF tools to detect tampering traces associated with resampling and/or identification of sources patterns in the origin of the images, using a pull of 300 initial photos.…”

Section: Discussionmentioning

confidence: 93%

“…Based on the above, it is not coincidental that recent review papers, studying real-world photo tampering scenarios (and their detection), usually omit deep fake cases (Zheng et al, 2019), which are treated as a whole new approach in our view as well. The same applies for the latest GAN image generation techniques, that are not treated as standard DIF cases in related publications (Gokhale et al, 2020;Katsaounidou, Vrysis, Kotsakis, Dimoulas & Veglis, 2019a;Katsaounidou, Vryzas, Kotsakis & Dimoulas, 2019b;Zheng et al, 2019). Furthermore, fake and deep fake facial images are dealt as critical in various domains and multidisciplinary research activities (Hsu et al, 2018;Hulzebosch et al, 2020;Tariq et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…For similar reasons, most classical DIF tools cannot sufficiently contribute to the detection of such manipulation trails, because they exploit different inconsistency inspection mechanisms. Fortunately, the deployment of these practices requires technological knowhow that ordinary users do not pose, thus confining the production and dissemination of such misinformation streams to the experts (Gokhale et al, 2020;Hsu et al, 2018Hsu et al, , 2020Katsaounidou, 2020;Thakur and Rohilla, 2020). Based on the above, it is not coincidental that recent review papers, studying real-world photo tampering scenarios (and their detection), usually omit deep fake cases (Zheng et al, 2019), which are treated as a whole new approach in our view as well.…”

Section: Introductionmentioning

confidence: 99%

“…The latter approaches are practically available only to technologists and researchers involved in these fields. Based on conducted literature review, related papers are constantly produced and published, studying the different image tampering and manipulation detection techniques, both traditional and contemporary (Gokhale et al, 2020;Qureshi and El-Alfy, 2019;Tariq et al, 2018;Thakur and Rohilla, 2020;Zheng et al, 2019). However, little effort is given to the adoption and evaluation of the associated tools and services from users' perspectives.…”

Section: Introductionmentioning

confidence: 99%

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News authentication and tampered images: evaluating the photo-truth impact through image verification algorithms

Katsaounidou¹,

Gardikiotis²,

Tsipas³

et al. 2020

Heliyon

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Photos have been used as evident material in news reporting almost since the beginning of Journalism. In this context, manipulated or tampered pictures are very common as part of informing articles, in today's misinformation crisis. The current paper investigates the ability of people to distinguish real from fake images. The presented data derive from two studies. Firstly, an online cross-sectional survey (N = 120) was conducted to analyze ordinary human skills in recognizing forgery attacks. The target was to evaluate individuals' perception in identifying manipulated visual content, therefore, to investigate the feasibility of “crowdsourced validation”. This last term refers to the process of gathering fact-checking feedback from multiple users, thus collaborating towards assembling pieces of evidence on an event. Secondly, given that contemporary veracity solutions are coupled with both journalistic principles and technology developments, an experiment in two phases was employed: a) A repeated measures experiment was conducted to quantify the associated abilities of Media and Image Experts (N = 5 + 5) in detecting tampering artifacts. In this latter case, image verification algorithms were put into the core of the analysis procedure to examine their impact on the authenticity assessment task. b) Apart from conducting interview sessions with the selected experts and their proper guidance in using the tools, a second experiment was also deployed on a larger scale through an online survey (N = 301), aiming at validating some of the initial findings. The primary intent of the deployed analysis and their combined interpretation was to evaluate image forensic services, offered as real-world tools, regarding their comprehension and utilization by ordinary people, involved in the everyday battle against misinformation. The outcomes confirmed the suspicion that only a few subjects had prior knowledge of the implicated algorithmic solutions. Although these assistive tools often lead to controversial or even contradictory conclusions, their experimental treatment with the systematic training in their proper use boosted the participants' performance. Overall, the research findings indicate that the scores of successful detections, relying exclusively on human observations, cannot be disregarded. Hence, the ultimate challenge for the “verification industry” should be to balance between forensic automations and the human experience, aiming at defending the audience from inaccurate information propagation.

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Section: Discussionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

News authentication and tampered images: evaluating the photo-truth impact through image verification algorithms

Katsaounidou¹,

Gardikiotis²,

Tsipas³

et al. 2020

Heliyon

View full text Add to dashboard Cite

show abstract

“…In our opinion, the new service by Google Scholar is very informative and useful due to the fact that it identifies funded and non-funded publications. For example, three funded publications have been identified by Google Scholar and displayed for an author (see Figure 2) and it is found that all the three publications were not funded by any funding agency (Gokhale et al, 2020;Borhade;Mulay, 2015). However, we found some inconsistencies with the new service that should be considered when using it:…”

Section: Conflict Of Interestmentioning

confidence: 94%

Letter. New Google Scholar section with information on funded publications

Elango

Bornmann

2021

EPI

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Sustainable strategic management: A bibliometric analysis

Rao

Shukla

2022

Bus Strat Env

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Strategy for a firm is a long‐term plan that persists. The enduring viability of these strategies depends on the ecological and environmental aspects of the firm, termed as sustainability. To address this concept, sustainable strategic management (SSM) has been introduced in the management domain. Over the last 30 years of the introduction of SSM, very few studies have systematically reviewed the researches in this purview. Therefore, this study examines the extant structure and future scope of the research on SSM through an inclusive bibliometric analysis of 221 articles. The database of Scopus and Web of Science is used in this study to sample these documents. The crucial contributors of the comprehensive literature are identified through the analysis of bibliographic coupling, citation analysis, co‐authorship analysis, co‐word analysis, co‐citation analysis and country publications, affiliations and collaboration map. The co‐citation analysis classifies the key thematic research interests into cluster of four, based on the co‐cited documents. However, the co‐word analysis identifies the co‐occurrence of keywords in the sampled documents. The country publications, affiliations and collaboration map indexes UK and USA as the top most country on number of articles and collaboration pattern and Europe and Asia as the prime continent on dominating the studies on SSM. The study provides insights on the current studies on SSM, which can be useful for researchers.

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A Bibliometric Analysis of Digital Image Forensics

Cited by 31 publications

References 29 publications

News authentication and tampered images: evaluating the photo-truth impact through image verification algorithms

News authentication and tampered images: evaluating the photo-truth impact through image verification algorithms

Letter. New Google Scholar section with information on funded publications

Sustainable strategic management: A bibliometric analysis

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