Example of IEEE Transactions on Information Forensics and Security format
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Example of IEEE Transactions on Information Forensics and Security format Example of IEEE Transactions on Information Forensics and Security format Example of IEEE Transactions on Information Forensics and Security format Example of IEEE Transactions on Information Forensics and Security format Example of IEEE Transactions on Information Forensics and Security format Example of IEEE Transactions on Information Forensics and Security format Example of IEEE Transactions on Information Forensics and Security format
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Example of IEEE Transactions on Information Forensics and Security format Example of IEEE Transactions on Information Forensics and Security format Example of IEEE Transactions on Information Forensics and Security format Example of IEEE Transactions on Information Forensics and Security format Example of IEEE Transactions on Information Forensics and Security format Example of IEEE Transactions on Information Forensics and Security format Example of IEEE Transactions on Information Forensics and Security format
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This content is only for preview purposes. The original open access content can be found here.
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IEEE Transactions on Information Forensics and Security — Template for authors

Publisher: IEEE
Categories Rank Trend in last 3 yrs
Safety, Risk, Reliability and Quality #2 of 165 down down by 1 rank
Computer Networks and Communications #6 of 334 up up by 3 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 977 Published Papers | 14792 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 03/06/2020
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Related Journals

open access Open Access

Inderscience Publishers

Quality:  
High
CiteRatio: 2.2
SJR: 0.177
SNIP: 0.562
open access Open Access

Elsevier

Quality:  
High
CiteRatio: 5.7
SJR: 0.61
SNIP: 1.727
open access Open Access

Inderscience Publishers

Quality:  
Medium
CiteRatio: 0.9
SJR: 0.153
SNIP: 0.532

Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

6.013

3% from 2018

Impact factor for IEEE Transactions on Information Forensics and Security from 2016 - 2019
Year Value
2019 6.013
2018 6.211
2017 5.824
2016 4.332
graph view Graph view
table view Table view

15.1

3% from 2019

CiteRatio for IEEE Transactions on Information Forensics and Security from 2016 - 2020
Year Value
2020 15.1
2019 14.7
2018 13.0
2017 10.4
2016 8.8
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has decreased by 3% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 3% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

1.613

15% from 2019

SJR for IEEE Transactions on Information Forensics and Security from 2016 - 2020
Year Value
2020 1.613
2019 1.897
2018 1.364
2017 1.274
2016 1.194
graph view Graph view
table view Table view

3.373

7% from 2019

SNIP for IEEE Transactions on Information Forensics and Security from 2016 - 2020
Year Value
2020 3.373
2019 3.617
2018 3.741
2017 3.322
2016 3.251
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 15% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 7% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

IEEE Transactions on Information Forensics and Security

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IEEE

IEEE Transactions on Information Forensics and Security

The IEEE Transactions on Information Forensics and Security covers the sciences, technologies, and applications relating to information forensics, information security, biometrics, surveillance and systems applications that incorporate these features.... Read More

Safety, Risk, Reliability and Quality

Computer Networks and Communications

Engineering

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Last updated on
03 Jun 2020
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ISSN
1556-6013
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Impact Factor
Very High - 3.312
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Open Access
No
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Sherpa RoMEO Archiving Policy
Green faq
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Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
IEEEtran
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Citation Type
Numbered
[25]
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Bibliography Example
G. E. Blonder, M. Tinkham, and T. M. Klapwijk, “Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion,” Phys. Rev. B, vol. 25, no. 7, pp. 4515–4532, 1982. [Online]. Available: 10.1103/PhysRevB.25.4515

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1109/TIFS.2012.2190402
Rich Models for Steganalysis of Digital Images
Jessica Fridrich1, Jan Kodovsky1

Abstract:

We describe a novel general strategy for building steganography detectors for digital images. The process starts with assembling a rich model of the noise component as a union of many diverse submodels formed by joint distributions of neighboring samples from quantized image noise residuals obtained using linear and nonlinear... We describe a novel general strategy for building steganography detectors for digital images. The process starts with assembling a rich model of the noise component as a union of many diverse submodels formed by joint distributions of neighboring samples from quantized image noise residuals obtained using linear and nonlinear high-pass filters. In contrast to previous approaches, we make the model assembly a part of the training process driven by samples drawn from the corresponding cover- and stego-sources. Ensemble classifiers are used to assemble the model as well as the final steganalyzer due to their low computational complexity and ability to efficiently work with high-dimensional feature spaces and large training sets. We demonstrate the proposed framework on three steganographic algorithms designed to hide messages in images represented in the spatial domain: HUGO, edge-adaptive algorithm by Luo , and optimally coded ternary ±1 embedding. For each algorithm, we apply a simple submodel-selection technique to increase the detection accuracy per model dimensionality and show how the detection saturates with increasing complexity of the rich model. By observing the differences between how different submodels engage in detection, an interesting interplay between the embedding and detection is revealed. Steganalysis built around rich image models combined with ensemble classifiers is a promising direction towards automatizing steganalysis for a wide spectrum of steganographic schemes. read more read less

Topics:

Steganalysis (62%)62% related to the paper, Steganography (54%)54% related to the paper, Feature extraction (52%)52% related to the paper, Digital image (50%)50% related to the paper
View PDF
1,553 Citations
Journal Article DOI: 10.1109/TIFS.2006.873602
Digital camera identification from sensor pattern noise
Jan Lukás1, Jessica Fridrich1, Miroslav Goljan1

Abstract:

In this paper, we propose a new method for the problem of digital camera identification from its images based on the sensor's pattern noise. For each camera under investigation, we first determine its reference pattern noise, which serves as a unique identification fingerprint. This is achieved by averaging the noise obtained... In this paper, we propose a new method for the problem of digital camera identification from its images based on the sensor's pattern noise. For each camera under investigation, we first determine its reference pattern noise, which serves as a unique identification fingerprint. This is achieved by averaging the noise obtained from multiple images using a denoising filter. To identify the camera from a given image, we consider the reference pattern noise as a spread-spectrum watermark, whose presence in the image is established by using a correlation detector. Experiments on approximately 320 images taken with nine consumer digital cameras are used to estimate false alarm rates and false rejection rates. Additionally, we study how the error rates change with common image processing, such as JPEG compression or gamma correction. read more read less

Topics:

Image noise (67%)67% related to the paper, Dark-frame subtraction (64%)64% related to the paper, Fixed-pattern noise (63%)63% related to the paper, Camera auto-calibration (62%)62% related to the paper, Image resolution (61%)61% related to the paper
View PDF
1,195 Citations
open accessOpen access Journal Article DOI: 10.1109/TIFS.2006.873653
Biometrics: a tool for information security
Anil K. Jain1, Arun Ross2, Sharathchandra U. Pankanti3

Abstract:

Establishing identity is becoming critical in our vastly interconnected society. Questions such as "Is she really who she claims to be?," "Is this person authorized to use this facility?," or "Is he in the watchlist posted by the government?" are routinely being posed in a variety of scenarios ranging from issuing a driver's ... Establishing identity is becoming critical in our vastly interconnected society. Questions such as "Is she really who she claims to be?," "Is this person authorized to use this facility?," or "Is he in the watchlist posted by the government?" are routinely being posed in a variety of scenarios ranging from issuing a driver's license to gaining entry into a country. The need for reliable user authentication techniques has increased in the wake of heightened concerns about security and rapid advancements in networking, communication, and mobility. Biometrics, described as the science of recognizing an individual based on his or her physical or behavioral traits, is beginning to gain acceptance as a legitimate method for determining an individual's identity. Biometric systems have now been deployed in various commercial, civilian, and forensic applications as a means of establishing identity. In this paper, we provide an overview of biometrics and discuss some of the salient research issues that need to be addressed for making biometric technology an effective tool for providing information security. The primary contribution of this overview includes: 1) examining applications where biometric scan solve issues pertaining to information security; 2) enumerating the fundamental challenges encountered by biometric systems in real-world applications; and 3) discussing solutions to address the problems of scalability and security in large-scale authentication systems. read more read less

Topics:

Information security standards (62%)62% related to the paper, Information security (57%)57% related to the paper, Authentication (53%)53% related to the paper, Biometrics (52%)52% related to the paper
View PDF
1,067 Citations
open accessOpen access Journal Article DOI: 10.1109/TIFS.2011.2175919
Ensemble Classifiers for Steganalysis of Digital Media
Jan Kodovsky1, Jessica Fridrich1, Vojtech Holub1

Abstract:

Today, the most accurate steganalysis methods for digital media are built as supervised classifiers on feature vectors extracted from the media. The tool of choice for the machine learning seems to be the support vector machine (SVM). In this paper, we propose an alternative and well-known machine learning tool-ensemble class... Today, the most accurate steganalysis methods for digital media are built as supervised classifiers on feature vectors extracted from the media. The tool of choice for the machine learning seems to be the support vector machine (SVM). In this paper, we propose an alternative and well-known machine learning tool-ensemble classifiers implemented as random forests-and argue that they are ideally suited for steganalysis. Ensemble classifiers scale much more favorably w.r.t. the number of training examples and the feature dimensionality with performance comparable to the much more complex SVMs. The significantly lower training complexity opens up the possibility for the steganalyst to work with rich (high-dimensional) cover models and train on larger training sets-two key elements that appear necessary to reliably detect modern steganographic algorithms. Ensemble classification is portrayed here as a powerful developer tool that allows fast construction of steganography detectors with markedly improved detection accuracy across a wide range of embedding methods. The power of the proposed framework is demonstrated on three steganographic methods that hide messages in JPEG images. read more read less

Topics:

Steganalysis (63%)63% related to the paper, Random subspace method (62%)62% related to the paper, Feature vector (56%)56% related to the paper, Support vector machine (55%)55% related to the paper, Feature extraction (53%)53% related to the paper
View PDF
967 Citations
open accessOpen access Journal Article DOI: 10.1109/TIFS.2010.2045842
Steganalysis by Subtractive Pixel Adjacency Matrix
Tomas Pevny, Patrick Bas, Jessica Fridrich1

Abstract:

This paper presents a method for detection of steganographic methods that embed in the spatial domain by adding a low-amplitude independent stego signal, an example of which is least significant bit (LSB) matching. First, arguments are provided for modeling the differences between adjacent pixels using first-order and second-... This paper presents a method for detection of steganographic methods that embed in the spatial domain by adding a low-amplitude independent stego signal, an example of which is least significant bit (LSB) matching. First, arguments are provided for modeling the differences between adjacent pixels using first-order and second-order Markov chains. Subsets of sample transition probability matrices are then used as features for a steganalyzer implemented by support vector machines. The major part of experiments, performed on four diverse image databases, focuses on evaluation of detection of LSB matching. The comparison to prior art reveals that the presented feature set offers superior accuracy in detecting LSB matching. Even though the feature set was developed specifically for spatial domain steganalysis, by constructing steganalyzers for ten algorithms for JPEG images, it is demonstrated that the features detect steganography in the transform domain as well. read more read less

Topics:

Steganalysis (63%)63% related to the paper, Steganography (55%)55% related to the paper, Least significant bit (55%)55% related to the paper, JPEG (52%)52% related to the paper, Feature extraction (52%)52% related to the paper
View PDF
940 Citations
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IEEE Transactions on Information Forensics and Security format uses IEEEtran citation style.

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Frequently asked questions

1. Can I write IEEE Transactions on Information Forensics and Security in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the IEEE Transactions on Information Forensics and Security guidelines and auto format it.

2. Do you follow the IEEE Transactions on Information Forensics and Security guidelines?

Yes, the template is compliant with the IEEE Transactions on Information Forensics and Security guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in IEEE Transactions on Information Forensics and Security?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the IEEE Transactions on Information Forensics and Security citation style.

4. Can I use the IEEE Transactions on Information Forensics and Security templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for IEEE Transactions on Information Forensics and Security.

5. Can I use a manuscript in IEEE Transactions on Information Forensics and Security that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper IEEE Transactions on Information Forensics and Security that you can download at the end.

6. How long does it usually take you to format my papers in IEEE Transactions on Information Forensics and Security?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in IEEE Transactions on Information Forensics and Security.

7. Where can I find the template for the IEEE Transactions on Information Forensics and Security?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per IEEE Transactions on Information Forensics and Security's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the IEEE Transactions on Information Forensics and Security's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. IEEE Transactions on Information Forensics and Security an online tool or is there a desktop version?

SciSpace's IEEE Transactions on Information Forensics and Security is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

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After writing your paper autoformatting in IEEE Transactions on Information Forensics and Security, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is IEEE Transactions on Information Forensics and Security's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for IEEE Transactions on Information Forensics and Security?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for IEEE Transactions on Information Forensics and Security. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In IEEE Transactions on Information Forensics and Security?

The 5 most common citation types in order of usage for IEEE Transactions on Information Forensics and Security are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the IEEE Transactions on Information Forensics and Security?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per IEEE Transactions on Information Forensics and Security's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download IEEE Transactions on Information Forensics and Security in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in IEEE Transactions on Information Forensics and Security Endnote style according to Elsevier guidelines.

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