| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 712 | 21 | 16 | 7 |
The objective of Eurasip Journal on Information Security is to combine knowledge in the areas of Computer security, Artificial intelligence, Encryption, Theoretical computer science and Algorithm. The Computer security research presented in Eurasip Journal on Information Security explores the relationship between Digital watermarking and the closely related topic of Data mining. It addresses concerns in Artificial intelligence which are intertwined with other disciplines, such as Machine learning, Computer vision and Pattern recognition.
The subject of Biometrics, which is connected to the field of Authentication, serves as the foundation of the Pattern recognition research featured in the journal. The study of Encryption, which falls within the realm of Computer network, was the main focus of the presentations. It features Theoretical computer science research that overlaps with concepts in Compression (functional analysis).
Issues in Algorithm were discussed, taking into consideration concepts from other disciplines like Embedding and Robustness (computer science). It focuses on Link encryption but sometimes tackles the closely related topic of 56-bit encryption which is concerned with Client-side encryption. It deals with Discrete cosine transform in conjunction with JPEG and similar fields in Quantization (image processing).
The journal publications tackle a plethora of topics, such as Encryption, Artificial intelligence, Computer security, Embedding and Computer vision. Artificial intelligence research in the journal articles connects with the study of Machine learning. The journal articles explore issues in Embedding which can be linked to other research areas like Algorithm, Theoretical computer science and Digital watermarking.
Eurasip Journal on Information Security investigates areas of study like Artificial intelligence, Pattern recognition, JPEG, Face (geometry) and Artificial neural network. Aside from investigating topics in Deep learning under Artificial intelligence, the journal also explores concepts in Task (project management). Topics in Pattern recognition explored in the journal were investigated in conjunction with research in Software, Estimator, Information leakage and Quantization (image processing).
The studies on JPEG discussed can also contribute to research in the domains of Domain (software engineering), Discrete cosine transform, Histogram, Compression (functional analysis) and Digital watermarking. Commutative property, Cover (telecommunications), Encryption, Algorithm and Robustness (computer science) are some topics wherein Discrete cosine transform research discussed in it have an impact. The presented research on Face (geometry) deals specifically with Pattern recognition (psychology) but it also addresses topics in Data science and Field (computer science).
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Eurasip Journal on Information Security (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Eurasip Journal on Information Security (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 10.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 22.22% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 55.56% of all publications and 22.22% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
The exploration of information security crosses several job roles and sectors. These roles often require a deep understanding of various topics such as computer security, artificial intelligence, and encryption, all of which are core areas of research in the Eurasip Journal on Information Security. For those contemplating a shift in career or already involved in this research area, a special teaching role can be considered. This would involve teaching high school students or at community colleges in Wisconsin about these core areas and more in an effort to groom the next generation of information security experts. For information on how to make this career shift, one can check out our guide on how to become a special education teacher in Wisconsin.
Besides academia, other roles that could benefit from the research areas of the Eurasip Journal on Information Security include data analysts, machine learning engineers, cyber security consultants, and network administrators. In these roles, the importance of encryption, algorithms, and data protection cannot be overstated. At a time when cyber threats are on the rise, professionals in the field of information security are increasingly in demand across various economic sectors, making this a viable and rewarding career path.
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