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Microsoft improves accessibility in their PDFs

Microsoft deepens its investment in Tagged PDF. We talked PDF with NISO. Both Android and iOS improve PDF handling. A major vulnerability was fixed in pdf.js.
About the author: The PDF Association staff delivers a vendor-neutral platform for PDF’s stakeholders, facilitating the development of open specifications and ISO standards for PDF technology. The staff are located in Germany, the … Read more

Microsoft continues investing in accessible PDF

On May 16 Microsoft announced a major investment in accessible PDF. The company has enhanced Word, Excel, and PowerPoint in Microsoft 365 with “...over 100 improvements to PDF/UA tags”. This timing is all very relevant given the recent publications of the PDF Association’s Well-Tagged PDF specification and ISO’s standardization of WTPDF’s Conformance Level for Accessibility via PDF/UA-2 for PDF 2.0.

Talking about PDF with NISO’s Unfettered Access

NISO (National Information Standards Organization) is where content publishers, libraries, and software developers go for information industry standards that support collaboration and interoperability.

NISO’s Unfettered Access webcast series touches on developments in related technologies and industries that affect NISO’s core constituencies. In their latest episode, NISO’s Executive Director, Todd Carpenter interviewed PDF Association CEO Duff Johnson about the industry engagement that goes into the ongoing enhancement of the PDF file format. Among other subjects, we discussed various functionalities that get overlooked and the best ways to encourage developers to improve the accessibility of the format.

Android and iOS improve their PDF handling

Wired reports that Android 15 (code name “Vanilla Ice Cream”) is currently in beta and will provide far better PDF handling: “PDFs should load more smoothly, and there is now support for password-protected files, annotations, form editing, and copy selection. Perhaps best of all, you can now search within PDF files.”

On the other side of the fence, Apple’s iOS 17.2 finally introduced the long-awaited improved AutoFill capabilities for PDF based on in-built machine learning algorithms. This was originally announced at Apple’s WWDC’23 event with other PDF capabilities touted to challenge Google Docs

A major vulnerability fixed in pdf.js

Codean Labs has discovered a significant vulnerability in pdf.js, Mozilla’s JavaScript-based PDF viewer (CVE-2024-4770). This bug allows attackers to execute arbitrary JavaScript code (not PDF JavaScript!) when a malicious PDF file is opened.

As Firefox uses pdf.js to display PDF files the vulnerability affects not only all Firefox users with versions less than 126, but also many other applications that use pdf.js (those before version 4.2.67). Firefox 126, Firefox ESR 115.11, and Thunderbird 115.11 have all been fixed and publicly released earlier in May.

If you develop a JavaScript application that handles PDF files you should check that you are not (indirectly) using a vulnerable version of pdf.js. Read more…

PDFacademicBot for May, 2024

Abbas, A. et al. (2022) ‘A simple PDF Converter using Android with built in editing features’, Journal of Computer Science, 15(09), p. 9. https://computersciencejournal.org/wp-content/uploads/2024/05/JCS-1324.pdf.

Aydin, E. (June 2023) ‘Specialisation Seminar: Adobe Postscript’. Universitat Innsbruck. http://cl-informatik.uibk.ac.at/teaching/ss23/bob2/ps/PS-r.pdf.

Devkate, V. et al. (2024) ‘Documentation management system and PDF Chat: An Integrated Approach’, ALOCHANA JOURNAL, 13(2231), p. pp.557-663. https://alochana.org/wp-content/uploads/56-AJ2294.pdf.

Ding, Y. et al. (2024) ‘PDF-MVQA: A Dataset for Multimodal Information Retrieval in PDF-based Visual Question Answering’. arXiv. Accepted by IJCAI 2024. https://doi.org/10.48550/arXiv.2404.12720.

Gajalakshmi, R. et al. (July 2023) ‘Wireless Sensor Network: Malicious Node Detection & Error Avoidance for PDF Files Using GLM’, International Journal Of Multidisciplinary Research in Science, Engineering and Technology, 6(7), p. 5. http://ijmrset.com/upload/14_Wireless].pdf.

Holubar, S.D. et al. (2024) ‘3-Dimensional Pouchography: A Proof-of-Concept Study of a Novel Technique for Visualizing Ileoanal Pouch Anatomy & Morphology in Normal and Mechanical Pouch Complication Patients’, Journal of Crohn’s and Colitis, p. jjae058. https://doi.org/10.1093/ecco-jcc/jjae058.

K R, S. and Mathew, S.K. (2024) ‘VISION BEYOND SIGHT: AFFORDANCES OF ASSISTIVE TECHNOLOGIES FOR THE VISUALLY IMPAIRED’, ECIS 2024 Proceedings. https://aisel.aisnet.org/ecis2024/track19_hci/track19_hci/6.

Klemm, R. and Chen, B. (2024) ‘Hiding Sensitive Information Using PDF Steganography’. arXiv. https://doi.org/10.48550/arXiv.2405.00865.

McLeod, M. (May 2024) ‘Chapter 05: Message Design: How to Communicate Visual Information to Learners Who are Visually Impaired’, Instructional Message Design, 3, p. 33. https://digitalcommons.odu.edu/instructional_message_design_vol3?utm_source=digitalcommons.odu.edu%2Finstructional_message_design_vol3%2F6&utm_medium=PDF&utm_campaign=PDFCoverPages.

Nichols, T. et al. (April 2024) ‘Image-based PDF Malware Detection Using Pre-trained Deep Neural Networks’, in 2024 12th International Symposium on Digital Forensics and Security (ISDFS). 2024 12th International Symposium on Digital Forensics and Security (ISDFS), IEEE, pp. 1–5. https://doi.org/10.1109/ISDFS60797.2024.10527343.

Procko, T.T. and Ochoa, O. (March 2024) ‘Semantic Science: Publication Beyond the PDF’, in SoutheastCon 2024. SoutheastCon 2024, Atlanta, GA, USA: IEEE, pp. 207–215. https://doi.org/10.1109/SoutheastCon52093.2024.10500258.

Shaikh, A., Shaikh, T. and Kazi, M. (March 2024) ‘Enabling Simultaneous PDF File Access on Android Mobile Device’, International Journal of Advanced Research in Science, Communication and Technology, pp. 455–457. https://doi.org/10.48175/IJARSCT-16693.

Swamy, A.K. et al. (May 2024) ‘PO-03-016 CREATION AND VALIDATION OF A NOVEL ALGORITHM TO DETECT LEFT VENTRICULAR DYSFUNCTION USING .PDF IMAGES OF ECGS AS INPUT DATA’, Heart Rhythm, 21(5), pp. S412–S413. https://doi.org/10.1016/j.hrthm.2024.03.1112.

Tang, Y., Chang, C.-M. and Yang, X. (2024) ‘PDFChatAnnotator: A Human-LLM Collaborative Multi-Modal Data Annotation Tool for PDF-Format Catalogs’, in Proceedings of the 29th International Conference on Intelligent User Interfaces. New York, NY, USA: Association for Computing Machinery (IUI ’24), pp. 419–430. https://doi.org/10.1145/3640543.3645174.

Toğaçar, M. and Ergen, B. (May 2024) ‘Processing 2D Barcode Data with Metaheuristic Based CNN Models and Detection of Malicious PDF Files’, Applied Soft Computing. https://doi.org/10.1016/j.asoc.2024.111722.

Varma, S. et al. (May 2024) ‘A Rule-Based Expert System for Automated Document Editing’, in P. Meesad et al. (eds) Proceedings of the 20th International Conference on Computing and Information Technology (IC2IT 2024). Cham: Springer Nature Switzerland, pp. 85–94. https://doi.org/10.1007/978-3-031-58561-6_9.

Zhu, M. (2022) Automatic data interpretation from scientific literatures in the portable document format with information-extraction tools for the advancement of materials discovery. PhD Thesis. Cambridge, UK. https://www.repository.cam.ac.uk/items/fe7a21b1-e6e1-4cfa-af43-05df8b6a2949

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