A comprehensive review of DDoS attack prevention, detection, and mitigation in IoT and SDN-IoT networks Sujit Sutradhar, Keya Chowdhury, Subhrajyoti Deb, Joy Lal Sarkar, Chandan Kumar, Aditya Kumar Sahu Discover Internet of Things, 2026 Distributed denial-of-service (DDoS) attacks pose a significant threat to software-defined networking with the Internet of Things (SDN-IoT) at present. Although SDN improves network agility and control, the restricted resources of IoT devices also expose new security flaws. This review provides a comprehensive analysis of DDoS attack types, taxonomies, and defense mechanisms in IoT and SDN-IoT networks. The study employs the PRISMA approach to analyze research papers published between 2020 and 2025 that focus on prevention, detection, and mitigation techniques. Unlike prior surveys that are mainly concerned with detection methods, this survey presents an in-depth and unified cross-layer comparison of prevention, detection, and mitigation techniques across the layers of IoT and SDN-IoT networks. Benchmark datasets and evaluation metrics are also compared to identify reproducibility and data imbalance issues. The review further provides a discussion on architectural elements influencing resilience, such as centralized and distributed controller architectures and controller placement in SDN-IoT systems. It also acknowledges the fact that full protection from DDoS attacks is unattainable and highlights resilience, risk mitigation, and response adaptability. Finally, key research gaps and future directions are identified to guide the development of scalable, intelligent, and collaborative DDoS defense frameworks for next-generation SDN-IoT systems.
Explainable and proactive fragile watermarking for medical Deepfake detection Amine Khaldi, Narima Zermi, Med Sayah Moad, Akram Boukhamla, Med Redouane Kafi, Aditya Kumar Sahu Intelligent Systems with Applications, 2026 Medical deepfakes and adversarial manipulations threaten AI-based diagnosis and telemedicine security. Existing watermarking methods for image authentication do not reliably distinguish clinically neutral transformations from semantic tampering, offer no interpretability of detected alterations, and often exceed latency constraints of clinical workflows. We propose Proactive Forensic Fragile Watermarking (PFF-WM), a framework that embeds two complementary watermarks: a fragile watermark in wavelet detail coefficients (pixel-level sensitivity) and a semi-robust watermark in the DCT domain whose embedding strength is modulated by a multi-scale attention map that prioritises diagnostically relevant regions. At the receiver side, a stacked autoencoder trained exclusively on authentic images detects manipulations via reconstruction error, a lightweight refinement network produces a tamper localisation mask, and a gradient-based explainability layer estimates the clinical impact of any alteration. Experiments on CheXpert (resampled to 512 × 512), LiTS, and ISIC 2019 show that PFF-WM achieves 97.6% detection accuracy and an AUC of 0.989, with tamper localisation IoU of 83.2%, with a false positive rate below 0.5% under each tested non‑geometric benign transformation (JPEG, resizing, contrast, blur) and below 0.7% under chained non‑geometric transformations. Geometric transformations (rotation, translation) are a recognised limitation, reaching 18.7% FPR at 15° rotation.The method shows competitive or superior performance against existing watermarking‑based forensic methods under the tested conditions, although direct comparability is limited for methods designed for different resolutions or modalities. Inference time is 44 ms per 512 × 512 image, making it computationally feasible for real‑time verification under the tested conditions.
A learned perceptual and neural detection framework for spread spectrum watermarking in medical images Ikram Hacini, Med Moad Sayah, Med Redouane Kafi, Narima Zermi, Amine Khaldi, Akram Boukhamla, Aditya Kumar Sahu Array, 2026 Medical image watermarking must ensure data authenticity and integrity without compromising diagnostic quality. Conventional spread spectrum methods suffer from key dependency, geometric vulnerability, hand-crafted perceptual models, and generative AI susceptibility. This paper presents a hybrid DWT-based spread spectrum framework for medical imaging with three innovations: a learned perceptual masking network (JND_net) that replaces analytical JND models, a lightweight CNN (SubBandSelector) that dynamically selects resilient wavelet sub-bands, and a neural detector (DetectorNet) that supplants fixed-threshold detection, all integrated with dual-key security (2 128 key space) and MAC authentication. Experiments on 1,200 medical images with radiologist validation (51.3% detection accuracy, chance level; diagnostic confidence unchanged, p = 0.34) show bit error rates below 0.03 under JPEG, noise, and filtering, outperforming seven baselines (p < 0.001). Under generative AI attacks, BER reaches 0.112 (diffusion) and 0.087 (inpainting). The framework operates in real time (3.7 ms on T4 GPU, 25 ms on CPU) under blind extraction.
Blind audio watermarking for medical data authentication using fractional Charlier transform and adaptive dithered quantization index modulation Salah Euschi, Narima Zermi, Sayah Med Moad, Amine Khaldi, Med Redouane Kafi, Aditya Kumar Sahu, Narimene Mimoune Systems and Soft Computing, 2026 Secure authentication and traceability of medical audio data remain critical challenges in modern telemedicine systems and digital health record management.. This paper proposes a novel blind and robust audio watermarking scheme for medical applications. The method combines the Fractional Charlier Transform (FrCT) for optimized time–frequency decomposition, local entropy analysis with critical-band masking for intelligent coefficient selection, and adaptive dithered quantization index modulation (ADQIM) for imperceptible watermark embedding. The proposed scheme provides comprehensive encryption of metadata including patient information and acquisition context through AES-based cryptographic mechanisms, while maintaining imperceptibility and embedding robustness. Comprehensive experimental validation on a diverse medical audio corpus demonstrates that the method achieves a practical payload capacity of 71.8 bits per second, high audio transparency with an SNR of 38.2 dB and a PESQ score of 4.15, and strong resilience against various signal processing attacks with an average BER of 3.2%. The approach provides a computationally efficient solution suitable for integration into operational telemedicine platforms and large-scale medical archiving systems, offering reliable authentication and integrity verification of medical audio records.
Biometric Embedded Non-Blind Color Image Watermarking with Geometric Tamper Resistance via SIFT-ORB Keypoint Matching Swapnaneel Dhar, Riyanka Manna, Khaldi Amine, Aditya Kumar Sahu Computers, 2026 This work introduces a non-blind watermarking framework for color images to address tamper detection, particularly under geometric transformations. The proposed scheme fuses two watermarks, a personal signature and a biometric fingerprint, into a unified composite watermark embedded into the chrominance component of the cover image using a multi-level transform domain approach, discrete wavelet transforms (DWTs), discrete cosine transforms (DCTs), and singular value decomposition (SVD). By leveraging the rotation-invariant properties of scale-invariant feature transform (SIFT) and oriented FAST and rotated BRIEF (ORB) descriptors, the framework ensures robust tamper detection without requiring alignment, thus mitigating the limitations of conventional detection techniques vulnerable to transformation-induced tamper obfuscation (TITO). Extensive experimentation demonstrates that the method maintains high perceptual fidelity, achieving PSNR values ranging from 50 to 55 dB for embedding strength factor μ (0.01–0.04) and SSIM indices near 1 across multiple benchmark images. Furthermore, the scheme exhibits notable resilience to a range of image processing attacks and geometric distortion. Comparative evaluation reveals its superiority over existing grayscale, color, SIFT-based and DWT-DCT-SVD-based watermarking techniques, affirming its applicability in scenarios demanding secure, imperceptible, and transformation-invariant image watermarking.
Hazardous Asteroid Prediction using Majority Voting Technique Ch. Venkata Rami Reddy, T. Naveen Sai, V. Sushanth, Suneetha Muvva, Deevi Radha Rani, Aditya Kumar Sahu Proceedings of the 7th International Conference on Intelligent Computing and Control Systems Iciccs 2023, 2023
A neural‑guided spread spectrum watermarking framework for diagnostic medical imaging I Hacini, MS Moad, MR Kafi, N Zermi, A Khaldi, A Boukhamla, AK Sahu Journal of Ambient Intelligence and Humanized Computing, 1-14 , 2026 2026
Secure and imperceptible medical image watermarking based on QR factorization in DT-CWT domain R Hamami, N Zermi, L Boubchir, A Khaldi, K Redouane, AK Sahu, ... Systems and Soft Computing, 200498 , 2026 2026
A Learned Perceptual and Neural Detection Framework for Spread Spectrum Watermarking in Medical Images H Ikram, MM Sayah, K Redouane, Z Narima, K Amine, A Boukhamla, ... Array, 100898 , 2026 2026
Audio watermarking for medical traceability based on local entropy and perceptual modeling S Euschi, N Zermi, MS Moad, A Khaldi, MR Kafi, AK Sahu, N Mimoune Multimedia Tools and Applications 85 (5), 502 , 2026 2026
A comprehensive review of DDoS attack prevention, detection, and mitigation in IoT and SDN-IoT networks S Sutradhar, K Chowdhury, S Deb, JL Sarkar, C Kumar, AK Sahu Discover Internet of Things , 2026 2026
Biometric Embedded Non-Blind Color Image Watermarking with Geometric Tamper Resistance via SIFT-ORB Keypoint Matching S Dhar, R Manna, K Amine, AK Sahu Computers 15 (5), 264 , 2026 2026
Comprehensive review of machine learning models for breast cancer diagnosis (2018–2023) SH Fathima, KK Palaparthi, P Patro, HK Rayapoodi, AK Dash, AK Sahu Big Data and Computing Visions 6 (1), 24-56 , 2026 2026
Frequency domain watermarking of medical images based on fractional discrete Cosine, Mellin, and Schur transforms N Saadaoui, B Akram Zine Eddine, N Zermi, A Khaldi, MR Kafi, AK Sahu Multimedia Tools and Applications 85 (3), 204 , 2026 2026 Citations: 2
Blind audio watermarking for medical data authentication using fractional Charlier transform and adaptive dithered quantization index modulation E Salah, Z Narima, MM Sayah, K Amine, K Redouane, AK Sahu, ... Systems and Soft Computing, 200464 , 2026 2026 Citations: 2
Securing Patient-Specific ECG Data in Telemedicine Through Adaptive Wavelet-Based Watermarking R Hamami, Z Narima, L Boubchir, K Amine, KM Redouane, AK Sahu, ... Intelligence-Based Medicine, 100357 , 2026 2026 Citations: 1
Hybrid fragile image watermarking for tamper detection, localization and dual self-recovery AK Sahu, M Sahu Engineering Science and Technology, an International Journal 73, 102266 , 2026 2026 Citations: 11
Cloud-based analysis with quantum cryptography-based cloud security model (QC-CSM) for enhanced data security in storage and access AK Chandanan, VK Sarathe, V Roy, AK Sahu Fortressing Pixels: Information security for images, videos, audio and … , 2026 2026
Privacy protection of medical data using NTRU-based post-quantum cryptography B Praneeth, R Ch, CN Manikanta, D Pavan Kumar, M Sahu, AK Sahu Fortressing Pixels: Information security for images, videos, audio and … , 2026 2026 Citations: 3
ECG signal protection using redundant discrete wavelet transform-based data hiding MM Sayah, Z Narima, K Amine, KM Redouane, AK Sahu Fortressing Pixels: Information security for images, videos, audio and … , 2026 2026 Citations: 4
Fortressing Pixels: Information security for images, videos, audio and beyond S Deb, AAA Gutub, AK Sahu The Institution of Engineering and Technology , 2026 2026 Citations: 1
Secure and imperceptible medical image watermarking via multiscale QR embedding and attention-based optimization AS Beggari, A Wali, A Khaldi, MR Kafi, AK Sahu Engineering Science and Technology, an International Journal 73, 102250 , 2026 2026 Citations: 10
A novel fiestal structured chromatic series-based data security approach R Ch, J Shaik, R Srikavya, M Sahu, AK Sahu Discover Internet of Things 5 (1), 1-20 , 2025 2025 Citations: 6
A novel pixel pair shuffling based image watermarking for tamper detection and self-recovery RR Murapaka, AVSP Kumar, AK Sahu Intelligence-Based Medicine, 100324 , 2025 2025 Citations: 1
Exploring AI in Steganography and Steganalysis: Trends, Clusters, and Sustainable Development Potential AK Sahu, C Kumar, S Kumar, S Solak arXiv preprint arXiv:2511.12052 , 2025 2025 Citations: 2
Robust and imperceptible medical image watermarking for telemedicine applications based on transform-domain and neural clustering techniques AS Beggari, A Wali, A Khaldi, MR Kafi, AK Sahu Journal of the Franklin Institute 362 (15), 108039 , 2025 2025 Citations: 20
MOST CITED SCHOLAR PUBLICATIONS
Performance evaluation parameters of image steganography techniques A Pradhan, AK Sahu, G Swain, KR Sekhar 2016 International conference on research advances in integrated navigation … , 2016 2016 Citations: 138
High Fidelity based Reversible Data Hiding using Modified LSB Matching and Pixel Difference AK Sahu, G Swain Journal of King Saud University - Computer and Information Sciences-Elsevier , 2019 2019 Citations: 137
An Optimal Information Hiding Approach Based on Pixel Value Differencing and Modulus Function AK Sahu, G Swain Wireless Personal Communications-Springer, 1-16 , 2019 2019 Citations: 128
Digital image steganography and steganalysis: A journey of the past three decades AK Sahu, M Sahu Open Computer Science 10 (1), 296–342 , 2020 2020 Citations: 126
Fake news research trends, linkages to generative artificial intelligence and sustainable development goals R Raman, VK Nair, P Nedungadi, AK Sahu, R Kowalski, S Ramanathan, ... Heliyon 10 (3) , 2024 2024 Citations: 119
Reversible Image Steganography Using Dual-Layer LSB Matching AK Sahu, G Swain Sensing and Imaging-Springer 21 (1), https://doi.org/10.1007/s11220-019-0262- , 2020 2020 Citations: 117
A logistic map based blind and fragile watermarking for tamper detection and localization in images AK Sahu Journal of Ambient Intelligence and Humanized Computing-Springer , 2021 2021 Citations: 90
Digital Image Steganography Using Bit Flipping AK Sahu, G Swain and E. Suresh Babu Cybernetics and Information Technologies 18 (1), 69-80 , 2018 2018 Citations: 88
Multi-directional block based PVD and modulus function image steganography to avoid FOBP and IEP AK Sahu, G Swain, M Sahu, J Hemalatha Journal of Information Security and Applications-Elsevier 58, 102808 , 2021 2021 Citations: 84
Towards improving the performance of blind image steganalyzer using third-order SPAM features and ensemble classifier J Hemalatha, M Sekar, C Kumar, A Gutub, AK Sahu Journal of Information Security and Applications 76, 103541 , 2023 2023 Citations: 76
Secure Reversible Data Hiding using Block-Wise Histogram Shifting S Kamil, M Sahu, KR Raghunandan, AK Sahu Electronics 12 (5), 1222 , 2023 2023 Citations: 74
Improving grayscale steganography to protect personal information disclosure within hotel services AK Sahu, A Gutub Multimedia Tools and Applications-Springer , 2022 2022 Citations: 72
Dual image-based reversible fragile watermarking scheme for tamper detection and localization AK Sahu, M Sahu, P Patro, G Sahu, SR Nayak Pattern Analysis and Applications 26 (2), 571-590 , 2023 2023 Citations: 71
Dual Stego-imaging Based Reversible Data Hiding Using Improved LSB Matching AK Sahu, G Swain International Journal of Intelligent Engineering and Systems 12 (5), 63-73 , 2019 2019 Citations: 69
A Novel n-Rightmost Bit Replacement Image Steganography Technique AK Sahu, G Swain 3D Research-Springer 10 (1), 2 , 2019 2019 Citations: 62
Digital to quantum watermarking: A journey from past to present and into the future S Dhar, AK Sahu Computer Science Review 54, 100679 , 2024 2024 Citations: 58
A study on content tampering in multimedia watermarking AK Sahu, K Umachandran, VD Biradar, O Comfort, V Sri Vigna Hema, ... SN Computer Science 4 (3), 222 , 2023 2023 Citations: 58
Local binary pattern based reversible data hiding M Sahu, N Padhy, SS Gantayat, AK Sahu CAAI Transactions on Intelligence Technology, 1-20 , 2022 2022 Citations: 56
Chaotic-Map Based Encryption for 3D Point and 3D Mesh Fog Data in Edge Computing KR Raghunandan, R Dodmane, K Bhavya, NSK Rao, AK Sahu IEEE Access 11, 3545-3554 , 2023 2023 Citations: 54
Multimodal imputation-based stacked ensemble for prediction and classification of air quality index in Indian cities RS Rao, LR Kalabarige, B Alankar, AK Sahu Computers and Electrical Engineering 114, 109098 , 2024 2024 Citations: 52
