DeepSteg: Integerating new paradigms of cascaded deep video steganography for securing digital data

Alexandria Engineering Journal, Год журнала: 2025, Номер 116, С. 483 - 501

Опубликована: Янв. 6, 2025

Язык: Английский

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Contrast-Invariant Edge Detection: A Methodological Advance in Medical Image Analysis

Applied Sciences, Год журнала: 2025, Номер 15(2), С. 963 - 963

Опубликована: Янв. 19, 2025

Edge detection methods are significant in medical imaging-assisted diagnosis. However, existing based on grayscale gradient computation still need to be optimized practicality, especially terms of actual visual quality and sensitivity image contrast. To optimize the visualization enhance robustness contrast changes, we propose Contrast Invariant Detection (CIED) method. CIED combines Gaussian filtering morphological processing preprocess images. It utilizes three Most Significant Bit (MSB) planes binary images detect extract edge information. Each bit plane is used edges 3 × blocks by proposed algorithm, then information from each fused obtain an image. This method generalized common types Since eliminates complex pixel operations, it faster more efficient. In addition, insensitive changes contrast, making flexible its application. comprehensively evaluate performance CIED, develop a dataset conduct evaluation experiments these The results show that average precision 0.408, recall 0.917, F1-score 0.550. indicate not only practical effects but also robust invariance. comparison with other confirm advantages CIED. study provides novel approach for within

Язык: Английский

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A Hybrid-Transformer-Based Cyber-Attack Detection in IoT Networks

International Journal of Interactive Mobile Technologies (iJIM), Год журнала: 2024, Номер 18(14), С. 90 - 102

Опубликована: Авг. 2, 2024

The concept of the Internet Things (IoT) is significant in today’s world and opens up new opportunities for several organizations. IoT solutions are proliferating fields such as self-driving cars, smart homes, transportation, healthcare, services constantly being created. Over previous decade, society has seen a expansion connectivity. In reality, connectivity will expand variety domains over next few years. Various problems must be overcome to permit effective secure operations. However, growing connections increase potential cyber-attacks since attackers can exploit broad network linked devices. Artificial intelligence (AI) detects prevents cyber assaults by developing adjusting threats weaknesses. this study, we offer novel cyber-detection model networks based on convolutional neural (CNN) transformers. study aims enhance system’s ability identify detect cyberattacks, sophisticated assaults, its performance. experimental findings, using cybersecurity CICIoT2023 dataset, show that CNN-Transformer hazards with an overall accuracy 99.49%. identifying hazardous activity, MLP 99.39%, while XGBoost-pipeline 99.40%.

Язык: Английский

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Passwordless Authentication Using a Combination of Cryptography, Steganography, and Biometrics

Опубликована: Янв. 19, 2024

User-generated passwords often pose a security risk in authentication systems. However, providing comparative substitute poses challenge, given the common tradeoff between and user experience. This paper integrates cryptographic methods (both asymmetric symmetric), steganography, combination of physiological behavioral biometrics to construct prototype for passwordless system. We demonstrate feasibility scalable while maintaining balance usability security. employed threat modeling techniques pinpoint prerequisites system, along with choosing appropriate protocols. In addition, analysis is conducted, examining impacts proposed system contrast that traditional password-based Results from indicate possible within timeframe similar (within 2 seconds), without imposing additional hardware costs on users enhance or compromising usability. Given nature design elimination shared secrets, financial efficiency burdens associated password resets are alleviated. Furthermore, breaches mitigated, as there no longer need store and/or their hashes. Differing prior research, our study presents pragmatic deserves consideration viable alternative both

Язык: Английский

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Advancement on Steganography: A Review

Lecture notes in networks and systems, Год журнала: 2024, Номер unknown, С. 51 - 65

Опубликована: Янв. 1, 2024

Язык: Английский

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A survey about deep learning and federated Learning in cyberse-curity

Periodicals of Engineering and Natural Sciences (PEN), Год журнала: 2024, Номер 12(1), С. 75 - 75

Опубликована: Фев. 10, 2024

Advances in Artificial Intelligence (AI) technology have led to the strengthening of traditional systems' cybersecurity capabilities a variety applications. However, these embedded machine learning models exposed systems new set vulnerabilities known as AI assaults. These are now attractive targets for cyberattacks, jeopardizing security and safety bigger that include them. As result, DL approaches critical transitioning network system protection from providing safe communication between intelligence security. Federated (FL) is kind based on heterogeneous datasets decentralized training. FL unique research topic currently its early phases. It has not yet gained wide acceptance community, owing mostly privacy considerations. In this research, we first shed light risks must be discovered, analyzed, recorded. favored scenarios where paramount is-sues. An extensive understanding risk factors allows an adopter implementer construct environment successfully while giving researchers clear perspective possible study domains. The survey paper intends analysis modern advances improve enhanced methods. proposes complete examination FL's issues assist bridging gap current level federated future which broad adoption achievable. We also propose range most recently used rating standards.

Язык: Английский

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Passwordless Authentication Using a Combination of Cryptography, Steganography, and Biometrics

Journal of Cybersecurity and Privacy, Год журнала: 2024, Номер 4(2), С. 278 - 297

Опубликована: Май 1, 2024

User-generated passwords often pose a security risk in authentication systems. However, providing comparative substitute poses challenge, given the common tradeoff between and user experience. This paper integrates cryptographic methods (both asymmetric symmetric), steganography, combination of physiological behavioural biometrics to construct prototype for passwordless system. We demonstrate feasibility scalable while maintaining balance usability security. employ threat modeling techniques pinpoint prerequisites system, along with choosing appropriate protocols. In addition, analysis is conducted, examining impacts proposed system contrast that traditional password-based The results from indicate possible within timeframe similar (within 2 s), without imposing additional hardware costs on users enhance or compromising usability. Given nature design elimination shared secrets, financial efficiency burdens associated password resets are alleviated. Furthermore, breaches mitigated as there no longer need store and/or their hashes. Differing prior research, our study presents pragmatic deserves consideration viable alternative both

Язык: Английский

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Enhancing Artwork Resilience Through Variable Embedding Technique

Опубликована: Фев. 22, 2024

In the rapidly evolving digital world, safeguarding creative works against unapproved modifications has emerged as a critical issue. Because of shortcomings traditional procedures, stronger solutions are being studied. The study uses novel application variable embedding technology to address important problem maintaining copyright integrity for artwork. This paper provides systematic analysis method's effectiveness and detailed understanding how appropriate it is certain image characteristics. And, illustrated resistance possible attacks by in-depth experimental investigations, offering viable path protecting copyrighted art. intends add discussion about enhancing authenticity data protection in field artistic expression world media expands further.

Язык: Английский

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Introduction of Steganography to Improve the Security of Transmitted Data

Lecture notes in networks and systems, Год журнала: 2024, Номер unknown, С. 351 - 364

Опубликована: Янв. 1, 2024

Язык: Английский

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Enhancing Communication Security with a Telegram Bot for Encrypted Image Communication Using F5-LSB Steganography

Опубликована: Апрель 18, 2024

Язык: Английский

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