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All Journal Register: Jurnal Ilmiah Teknologi Sistem Informasi Produktif : Jurnal Ilmiah Pendidikan Teknologi Informasi AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat IJIS - Indonesian Journal On Information System DINTEK Jurnal Teknik Informatika Mobile and Forensics Jurnal Sains Komputer dan Teknologi Informasi Jurnal Pengabdian Masyarakat (ABDIRA) Riwayat: Educational Journal of History and Humanities MERDEKA: Jurnal Ilmiah Multidisiplin
Mandar, Gamaria
Universitas Muhammadiyah Maluku Utara
Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Neuroscience Nursing Social Sciences Other

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Journal : Mobile and Forensics

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National Institute of Standard Technology Approach for Steganography Detection on WhatsApp Audio Files Muhammad, Abdul Haris; Mandar, Gamaria
Mobile and Forensics Vol. 6 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v6i2.11287

Abstract

Audio steganography in instant messaging applications such as WhatsApp poses new challenges in the field of digital security, especially due to the ability to hide data in frequently used formats. This research examines the effectiveness of steganography detection on WhatsApp audio files by applying a method developed by the National Institute of Standards and Technology (NIST). This approach was chosen due to its reputation in security testing standards, but its use in the context of audio steganography on instant messaging platforms has not been widely explored. The novelty of this research lies in the adaptation of the NIST method specifically for audio steganography analysis in WhatsApp, which includes testing against various compression and end-to-end encryption scenarios. The main findings of this research show that the NIST method successfully improves the accuracy of hidden message detection compared to conventional steganalysis techniques, especially under the condition of compressed audio files. In addition, this research also found that the integration of the NIST method enables more effective detection of steganographic data in encrypted audio files. These results confirm that the NIST method can be successfully adapted for instant messaging applications such as WhatsApp, making a significant contribution in the improvement of digital security. This research not only identifies weaknesses in existing steganography techniques, but also introduces a new framework for more accurate and efficient detection in encrypted environments.
Co-Authors Abdul Haris Muhammad Abdullah, Aswan Aswan Abdullah Bayu Ajisaputro Daniel Siloam Diawan, Julfikar Erwin Gunawam Erwin Gunawan Erwin Gunawan Erwin Gunawan Fitria Auliah Gunawan Gunawan hamid, mustamin hasan saban Hatari, Himawan Udin irfiana safitri irsan jafar Irwan, Risman Isnawati Saleh Junaidi Noh Junaidi Noh Koroy, Angga Masri S.M kris, Novel file La Jailo, Sumarni lagani, arjun M.Ikbal Hidayullah Muhammad Rangga Wardani Muhammad, Abdul Haris nasar, muslimin omo, Muthia untung priatma nandi Roman, Abdul safitri, irfiana Sahriar Hamza Sakina Sudin Salsabila, Salsabila samsul, nurul Santosa Santosa Santosa Santosa, M Sudin, Sakina Sukur Masiana Taib, Acan Tamrin, Fikram Udrus, Karina Zulpadli, Muhammad