Claim Missing Document
Check
Articles

Found 38 Documents
Search

MedProtect: Protecting Electronic Patient Data Using Interpolation-Based Medical Image Steganography Muhammad, Aditya Rizki; Ramadhan, Irsyad Fikriansyah; Croix, Ntivuguruzwa Jean De La; Ahmad, Tohari; Uwizeye, Dieudonne; Kantarama, Evelyne
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 7 No 4 (2025): October
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v7i4.977

Abstract

Electronic Patient Records (EPRS) represent critical elements of digital healthcare systems, as they contain confidential and sensitive medical information essential for patient care and clinical decision-making. Due to their sensitive nature, EPRs frequently face threats from unauthorized intrusions, security breaches and malicious attacks. Safeguarding such information has emerged as an urgent concern in medical data security. Steganography offers a compelling solution by hiding confidential data within conventional carrier objects like medical imagery. Unlike traditional cryptographic methods that merely alter the data representation, steganography conceals the existence of the information itself, thereby providing discretion, security, and resilience against unauthorized disclosure. However, embedding patient information inside medical images introduces a new challenge. The method must maintain the image's visual fidelity to prevent compromising diagnostic precision, while ensuring reversibility for complete restoration of both original imagery and concealed information. To address these challenges, this research proposes MedProtect, a reversible steganographic framework customized for medical applications. MedProtect procedure integrates pixel interpolation techniques and center-folding-based data transformation to insert sensitive records into medical imagery. This method combination ensures accurate data recovery of the original image while maintaining the image quality of the resulting image. To clarify the performance of MedProtect, this study evaluates two well-established image quality metrics, Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM). The discovery shows that the framework achieves PSNR values of 48.190 to 53.808 dB and SSIM scores between 0.9956 and 0.9980. These outcomes display the high level of visual fidelity and imperceptibility achieved by the proposed method, underscoring its effectiveness as a secure approach for protecting electronic patient records within medical imaging systems.
Pre-trained convolutional neural network-based algorithms: application for recognizing the age category Yamasari, Yuni; Anggraini, Lusiana; Qoiriah, Anita; Eka Putra, Ricky; Agustin Tjahyaningtijas, Hapsari Peni; Ahmad, Tohari
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i5.pp3576-3587

Abstract

Cybercrime is a major issue in the current digital era, with one of its branches-cyber pornography-notably affecting Indonesia. Various efforts have been made to suppress or prevent this problem. One alternative solution involves using technological advances to recognize age ranges based on facial recognition. This age range recognition can be implemented to prevent users from accessing content that is not appropriate for their age. An optimal age-range recognition system is essential for this purpose. However, limited research has focused on this domain. Therefore, our research aimed to develop the best possible system. The proposed method applies a trained convolutional neural network (CNN) as a feature extractor to the artificial neural network (ANN) and k-nearest neighbor (K-NN) methods for age recognition based on facial images. By incorporating computational learning techniques, the system's performance is significantly enhanced, leveraging advanced algorithms to improve accuracy. The test results show that the performance of the pre-trained CNN-based ANN model is superior. This is indicated by the model's accuracy and F1-score, which were 11% and 0.11 higher, than the pre-trained CNN-based K-NN model. The error rate of the pre-trained CNN-based ANN model was also reduced by 0.11.
A hybrid steganography scheme with reduced difference expansion and pixel-value ordering Putra, I Kadek Agus Ariesta; Croix, Ntivuguruzwa Jean De La; Ahmad, Tohari
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i5.pp3563-3575

Abstract

Steganography embeds secret messages into public media while ensuring the stego content remains visually indistinguishable from the original. The primary challenge lies in maximizing embedding capacity and image quality without introducing noticeable distortions. This research proposes a novel reversible data hiding (RDH) scheme that integrates reduced difference expansion (RDE) with four directional pixel-value ordering (PVO) schemes, horizontal, vertical, diagonal-right, and diagonal-left, to enhance embedding efficiency and visual fidelity. Unlike existing RDH methods that apply RDE with fixed or limited PVO directions, the proposed scheme dynamically selects the optimal PVO orientation based on pixel pair characteristics, effectively improving local prediction accuracy and reducing embedding-induced distortion. Previous studies have largely overlooked this relationship between pixel pair selection and embedding performance. Experimental evaluation on medical images with secret data sizes ranging from 5 kb to 100 kb demonstrates significant gains over recent PVO-based methods. The proposed method increases the average embedding capacity from 0.8315 to 0.9781 bit per pixel (bpp) (a 17.6% improvement) and raises the average peak signal-to-noise ratio (PSNR) from 49.44 to 53.40 dB, reducing distortion by approximately 3.96 dB.
Peningkatan Kualitas Citra Stego pada Adaptive Pixel Block Grouping Reduction Error Expansion dengan Variasi Model Scanning pada Pembentukan Kelompok Piksel Prabowo, Hendro Eko; Ahmad, Tohari
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 5 No 2: April 2018
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (143.12 KB) | DOI: 10.25126/jtiik.201852633

Abstract

Kebutuhan komunikasi yang terus bertambah dan ditandai dengan meningkatnya jumlah IP traffic dari 744 EB menjadi 1.164 EB menjadikan keamanan sebagai salah satu kebutuhan utama dalam menjaga kerahasiaan data. Adaptive Pixel Block Grouping Reduction Error Expansion (APBG-REE) sebagai salah satu metode data hiding dapat diterapkan untuk memenuhi kebutuhan tersebut. Metode ini akan membagi citra carrier menjadi blok-blok dan membentuknya menjadi kelompok-kelompok piksel. Hasil dari proses ini akan dimanfaatkan untuk menyembunyikan data rahasia. Namun, metode ini memiliki kekurangan, yaitu belum diketahuinya metode scanning terbaik dalam pembentukan kelompok piksel untuk menciptakan citra stego dengan kualitas tinggi. Untuk mengatasi masalah ini, kami mengusulkan 4 mode (cara) scanning berdasarkan arah scanning tersebut. Mode scanning tersebut memberikan hasil yang berbeda-beda untuk masing-masing citra stego yang diujikan. Namun berdasarkan hasil uji coba, setiap mode scanning mampu menjaga kualitas citra stego diatas 57,5 dB. Hasil ini akan meningkat seiring dengan berkurangnya jumlah shifted pixel yang terbentuk. AbstractThe need of communication has increased continously which is represented by the rise of number of IP traffic, from 744 EB to 1.164 EB. This has made data security one of the main requirements in terms of securing secret data. Adaptive Pixel Block Grouping Reduction Error Expansion (APBG-REE) as one of data hiding methods can be implemented to meet that requirement. It divides the carrier image into blocks which are then used as pixel groups. The result of this process is to be a space for secret data. However, this method has a problem in the scanning when creating pixel groups to generate a high quality stego image. To handle this problem, we propose four scanning models base on its direction. This means that the scanning can be done row-by-row or column-by-column. Base on the experiment, we find that those modes deliver various results and each of them is able to maintain the stego quality of more than 57,5 dB. This result increases along with the decreasing the number of shifted pixels.
DEVELOPMENT OF LOAD BALANCING MECHANISMS IN SDN DATA PLANE FAT TREE USING MODIFIED DIJKSTRA’S ALGORITHM Muhammad Fattahilah Rangkuty; Royyana Muslim Ijtihadie; Tohari Ahmad
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 18, No. 2, July 2020
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v18i2.a1008

Abstract

SDN is a computer network approach that allows network administrators to manage network services through the abstraction of functionality at a higher level, by separating systems that make decisions about where traffic is sent (control plane), then forwarding traffic to the chosen destination (data plane). SDN can have problems with network congestion, high latency, and decreased throughput due to unbalanced traffic allocation on available links, so a load-balancing load method is needed. This technique divides the entire load evenly on each component of the network on the path or path that connects the data plane and S-D (Source Destination) host. The Least Loaded Path (LLP) of our proposed concept, which is a Dijkstra development, selects the best path by finding the shortest path and the smallest traffic load, the smallest traffic load (minimum cost) obtained from the sum of tx and rx data in the switchport data plane involved in the test, this result which will then be determined as the best path in the load balancing process.
EFFICIENCY OF FLOODING BY DEVELOPING RELIABLE SUBNETWORK METHODS ON FIBBING ARCHITECTURE IN THE HYBRID ENVIRONMENT SDN Dino Budi Prakoso; Royyana Muslim Ijtihadie; Tohari Ahmad
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 19, No. 1, Januari 2021
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v19i1.a1009

Abstract

In the technology world especially in the field of current network of Autonomous Systems connectivity (AS) is indispensable. Especially against the dynamic routing protocols that are often used compared to static routing protocols. In supporting this current network, it takes efficient and effective routing protocols capable of covering a sizable scale. Software Defined Network (SDN) is a technological innovation in the network world that has a separate Control Plane and Data Plane that makes it easy to configure on the Control Plane side. Control Plane is the focal point on a process of bottleneck in SDN architecture. Performance is a critical issue in large-scale network implementations because of the large demand load occurring in the Control Plane by generating low throughput value. This research will be conducted testing on the Hybrid network of SDN by using OSPF routing protocol, based on the Fibbing architecture implemented on the system network Hybrid SDN also able to assist in improving performance, but there are constraints when sending flooding which is used as a fake node forming. Many nodes are not skipped as distribution lines in the formation of a fake node, in which case it will certainly affect the value of throughput to be unstable and decrease. This can be overcome by using the Isolation Domain method to manage the LSA Type-5 flooding efficiency.
IMPLEMENTATION OF JOHNSON'S SHORTEST PATH ALGORITHM FOR ROUTE DISCOVERY MECHANISM ON SOFTWARE DEFINED NETWORK Akbar Pandu Segara; Royyana Muslim Ijtihadie; Tohari Ahmad
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 19, No. 1, Januari 2021
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v19i1.a1011

Abstract

Software Defined Network is a network architecture with a new paradigm which consists of a control plane that is placed separately from the data plane. All forms of computer network behavior are controlled by the control plane. Meanwhile the data plane consisting of a router or switch becomes a device for packet forwarding. With a centralized control plane model, SDN is very vulnerable to congestion because of the one-to-many communication model. There are several mechanisms for congestion control on SDNs, one of which is modifying packets by reducing the size of packets sent. But this is considered less effective because the time required will be longer because the number of packets sent is less. This requires that network administrators must be able to configure a network with certain routing protocols and algorithms. Johnson's algorithm is used in determining the route for packet forwarding, with the nature of the all-pair shortest path that can be applied to SDN to determine through which route the packet will be forwarded by comparing all nodes that are on the network. The results of the Johnson algorithm's latency and throughput with the comparison algorithm show good results and the comparison of the Johnson algorithm's trial results is still superior. The response time results of the Johnson algorithm when first performing a route search are faster than the conventional OSPF algorithm due to the characteristics of the all pair shortest path algorithm which determines the shortest route by comparing all pairs of nodes on the network.
EPR-Stego: Quality-Preserving Steganographic Framework for Securing Electronic Patient Records Safitri, Wardatul Amalia; Arsyad, Hammuda; Croix, Ntivuguruzwa Jean De La; Ahmad, Tohari; Batamuliza, Jennifer; Basori, Ahmad Hoirul
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 8 No 1 (2026): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v8i1.1172

Abstract

Secure medical data transmission is a fundamental requirement in telemedicine, where information is often exchanged over public networks. Protecting patient confidentiality and ensuring data integrity are crucial, particularly when sensitive medical records are involved. Steganography, an information hiding technique, offers a promising solution by embedding confidential data within medical images. This approach not only safeguards privacy but also supports authentication processes, ensuring that patient information remains secure during transmission. This study introduces EPR-Stego, a novel steganographic framework designed specifically for embedding electronic patient record (EPR) data in medical images. The key innovation of EPR-Stego lies in its mathematical strategy to minimize pixel intensity differences between neighboring pixels. By reducing usable pixel variations, the framework generates a stego image that is visually indistinguishable from the original, thereby enhancing imperceptibility while preserving diagnostic quality. Additionally, the method produces a key table, required by the recipient to accurately extract the embedded data, which further strengthens security against unauthorized access. The design of EPR-Stego aims to prevent attackers from easily detecting the presence of hidden medical information, mitigating the risk of targeted breaches. Experimental evaluations demonstrate its effectiveness, with the proposed approach achieving Peak Signal to Noise Ratio (PSNR) values between 51.71 dB and 75.59 dB, and Structural Similarity Index Measure (SSIM) scores reaching up to 0.99. These metrics confirm that the stego images maintain high visual fidelity and diagnostic reliability. Overall, EPR-Stego outperforms several existing techniques, offering a robust and secure solution for medical data transmission. By combining imperceptibility, security, and quality preservation, the framework addresses the pressing need for reliable protection of patient information in telemedicine environments
Co-Authors Adhi Prasetyo R Aditya Prapanca Agus Prihanto Agustin Tjahyaningtijas, Hapsari Peni Ahmad Hoirul Basori Akbar Pandu Segara Al Kanza, Kalyana Putri Alfian Ma’arif Alzamzami, Moch. Nafkhan Anggraini, Lusiana ANITA QOIRIAH Arsyad, Hammuda Ary Mazharuddin Shiddiqi Bagus J Santoso Bagus Jati Santos Baskoro Adi Pratomo Batamuliza, Jennifer Chaidir Chalaf Islamy Croix, Ntivuguruzwa Jean De La Danang Adi Nugroho Dany Primanita Kartikasari Diani, Nabila A'idah Dicky Irwanto Dino Budi Prakoso Djuned Fernando Djusdek Doni S. Pambudi, Doni S. Eka Putra, Ricky Emerson Eridiansyah Z Ephrem Niyigaba Fadhila, Farah Dhia Fikriansyah, Irsyad Hendro Eko Prabowo Hendro Eko Prabowo, Hendro Eko Henning Titi Ciptaningtyas Hudan Studiawan Imam Riadi Kantarama, Evelyne Leki Jovial Mahoro Lidya Amalia Rahmania Maurice Ntahobari Mohammad Rijal Mohammed Hatem Ali Al-Hooti Muhammad Fattahilah Rangkuty Muhammad Holil Muhammad Rizka Muhammad, Aditya Rizki Pascal Maniriho Pramudya, Rafli Raihan Prinandika, Arya Gading Purwono, Purwono Putra, I Kadek Agus Ariesta Radityo Anggoro, Radityo Ramadhan, Irsyad Fikriansyah Riyanarto Sarno Rochmawati, Naim Royyana M Ijtihadie Royyana M. Ijtihadie Royyana Muslim Ijtihadie Royyana Muslim Ijtihadie Safitri, Wardatul Amalia Santoso, Bagus Jati Santoso, Bagus Jati Solichul Huda Suartana, I Made Supeno Djanali Tegar Palyus Fiqar Tegar Palyus Fiqar Teja, Andika Rahman Uwizeye, Dieudonne Vinorian, Muhammad Ersya Wahyu Suadi Waskhito Wibisono Waskitho Wibisono Waskitho Wibisono Yohanes I. Riskajaya Yohanes I. Riskajaya YUNI YAMASARI Zainal Syahlan Zaini, Alfa Fakhrur Rizal Zephanie Bizimana