• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.366-381
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• 2020

Steganography has been successfully employed in various applications, e.g., copyright control of materials, smart identity cards, video error correction during transmission, etc. Deep learning-based steganography models can hide information adaptively through network learning, and they draw much more attention. However, the capacity, security, and robustness of the existing deep learning-based steganography models are still not fully satisfactory. In this paper, three models for different cases, i.e., a basic model, a secure model, a secure and robust model, have been proposed for different cases. In the basic model, the functions of high-capacity secret information hiding and extraction have been realized through an encoding network and a decoding network respectively. The high-capacity steganography is implemented by hiding a secret image into a carrier image having the same resolution with the help of concat operations, InceptionBlock and convolutional layers. Moreover, the secret image is hidden into the channel B of carrier image only to resolve the problem of color distortion. In the secure model, to enhance the security of the basic model, a steganalysis network has been added into the basic model to form an adversarial network. In the secure and robust model, an attack network has been inserted into the secure model to improve its robustness further. The experimental results have demonstrated that the proposed secure model and the secure and robust model have an overall better performance than some existing high-capacity deep learning-based steganography models. The secure model performs best in invisibility and security. The secure and robust model is the most robust against some attacks.

• Convergence Security Journal
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• v.11 no.1
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• pp.33-38
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• 2011

Current IEEE 802.11 standard is very vulnerable that between the AP and STA authentication and security mechanisms is widely known. Therefore, IEEE has proposed security architecture RSN (Robust Security Network) for 802.11. RSN is used the access control, authentication, and key management based on the IEEE 802.1X standard. In this paper, IEEE 802.1X or 802.11 a combination of several models proposed for the vulnerability, and session hijacking or MiM (Man-in the-Middle) attacks to respond, the authentication mechanism Was designed to the access control between the STA and the AP.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.93-100
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• 2024

In this paper, we propose a novel robust blind crypto-watermarking method for medical images security based on hiding of DICOM patient information (patient name, age...) in the medical imaging. The DICOM patient information is encrypted using the AES standard algorithm before its insertion in the medical image. The cover image is divided in blocks of 8x8, in each we insert 1-bit of the encrypted watermark in the hybrid transform domain by applying respectively the 2D-LWT (Lifting wavelet transforms), the 2D-DCT (discrete cosine transforms), and the SVD (singular value decomposition). The scheme is tested by applying various attacks such as noise, filtering and compression. Experimental results show that no visible difference between the watermarked images and the original images and the test against attack shows the good robustness of the proposed algorithm.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1271-1278
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• 2020

Deep learning-based profiling side-channel analysis is a powerful analysis method that utilizes the neural network to profile the relationship between the side-channel information and the intermediate value. Since the neural network interprets each point of the signal in a different dimension, jitter makes it much hard that the neural network with dimension-wise weights learns the relationship. This paper shows that replacing the fully-connected layer of the traditional CNN (Convolutional Neural Network) with global average pooling (GAP) allows us to design the inherently robust neural network inherently for jitter. We experimented with the ChipWhisperer-Lite board to demonstrate the proposed method: as a result, the validation accuracy of the CNN with a fully-connected layer was only up to 1.4%; contrastively, the validation accuracy of the CNN with GAP was very high at up to 41.7%.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.1
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• pp.25-34
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• 2010

The IEEE 802.16-2004 standard has a security sub-layer in the MAC layer called, Privacy Key Management (PKM). However, several researches have been published to address the security vulnerabilities of IEEE 802.16-2004. After the IEEE 802.16-2004 standard, a new advanced and revised standard was released as the IEEE 802.16e-2005 amendment which is foundation of Mobile WiMAX network supporting handoffs and roaming capabilities. PKMv2 in Mobile WiMAX includes EAP authentication, AES-based authenticated encryption, and CMAC or HMAC message protection. However, Mobile WiMAX still has a problem of security architecture such as a disclosure of security context in network entry, a lack of secure communication in network domain, and a necessity of efficient handover supporting mutual authentication because Mobile WiMAX security has mainly concentrated on between SS and BS communication. Based on the investigation results, we propose a novel mobile WiMAX security architecture, called RObust and Secure MobilE WiMAX (ROSMEX), to prevent the new security vulnerabilities.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.45-54
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• 2022

In this study, a multi-objective robust job-shop scheduling (JSS) model was developed. The model considered multi-jobs and multi-machines. The model also considered uncertain processing times for all tasks. Each job was assigned a specific due date and a tardiness penalty to be paid if the job was not delivered on time. If any job was completed early, holding expenses would be assigned. In addition, the model added idling penalties to accommodate the idling of machines while waiting for jobs. The problem assigned was to determine the optimal start times for each task that would minimize the expected penalties. A numerical problem was solved to minimize both the makespan and the total penalties, and a comparison was made between the results. Analysis of the results produced a prescription for optimizing penalties that is important to be accounted for in conjunction with uncertainties in the job-shop scheduling problem (JSSP).

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.1-10
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• 2024

In the era of big data, the growth of e-commerce transactions brings forth both opportunities and risks, including the threat of data theft and fraud. To address these challenges, an automated real-time fraud detection system leveraging machine learning was developed. Four algorithms (Decision Tree, Naïve Bayes, XGBoost, and Neural Network) underwent comparison using a dataset from a clothing website that encompassed both legitimate and fraudulent transactions. The dataset exhibited an imbalance, with 9.3% representing fraud and 90.07% legitimate transactions. Performance evaluation metrics, including Recall, Precision, F1 Score, and AUC ROC, were employed to assess the effectiveness of each algorithm. XGBoost emerged as the top-performing model, achieving an impressive accuracy score of 95.85%. The proposed system proves to be a robust defense mechanism against fraudulent activities in e-commerce, thereby enhancing security and instilling trust in online transactions.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1284-1292
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• 2015

As visual surveillance systems become more and more common in human lives, approaches based on these systems to solve security problems in practice are boosted, especially in railway applications. In this paper, we first propose a robust snag detection algorithm and then present a railway security system by using a combination of multiple sensors and the vision based snag detection algorithm. The system aims safety at several repeatedly occurred situations including slope protection, inspection of the falling-object from bridges, and the detection of snags and foreign objects on the rail. Experiments demonstrate that the snag detection is relatively robust and the system could guarantee the security of the railway through these real-time protections and detections.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.95-102
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• 2024

In distributed computing, accessible encryption strategy over Auditable data is a hot research field. Be that as it may, most existing system on encoded look and auditable over outsourced cloud information and disregard customized seek goal. Distributed storage space get to manage is imperative for the security of given information, where information security is executed just for the encoded content. It is a smaller amount secure in light of the fact that the Intruder has been endeavored to separate the scrambled records or Information. To determine this issue we have actualize (CBC) figure piece fastening. It is tied in with adding XOR each plaintext piece to the figure content square that was already delivered. We propose a novel heterogeneous structure to evaluate the issue of single-point execution bottleneck and give a more proficient access control plot with a reviewing component. In the interim, in our plan, a CA (Central Authority) is acquainted with create mystery keys for authenticity confirmed clients. Not at all like other multi specialist get to control plots, each of the experts in our plan deals with the entire trait set independently. Keywords: Cloud storage, Access control, Auditing, CBC.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.317-322
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• 2021

The modern technological era has brought about the Semantic Web. Ontologies are essential to achieve the vision of the Semantic Web. Ontologies enable machines to understand data. The Arabic Language currently does not have a significant presence on the Web. To achieve a comparable level of Arabic access to other important languages, further work is needed to build Arabic ontologies. A goal is to design and create a robust Arabic ontology that represents the concepts from a large and significant subset of Arabic. We use a source of Hadiths (prophet saying and deeds) from Riyadh As-Saliheen. Preliminary results are very promising.