• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.12
• /
• pp.4508-4530
• /
• 2021

Today distributed data storage service are being widely used. However lack of proper means of security makes the user data vulnerable. In this work, we propose a Randomized Block Size (RBS) model for secure data storage in distributed environments. The model work with multifold block sizes encrypted with the Chinese Remainder Theorem-based RSA (C-RSA) technique for end-to-end security of multimedia data. The proposed RBS model has a key generation phase (KGP) for constructing asymmetric keys, and a rand generation phase (RGP) for applying optimal asymmetric encryption padding (OAEP) to the original message. The experimental results obtained with text and image files show that the post encryption file size is not much affected, and data is efficiently encrypted while storing at the distributed storage server (DSS). The parameters such as ciphertext size, encryption time, and throughput have been considered for performance evaluation, whereas statistical analysis like similarity measurement, correlation coefficient, histogram, and entropy analysis uses to check image pixels deviation. The number of pixels change rate (NPCR) and unified averaged changed intensity (UACI) were used to check the strength of the proposed encryption technique. The proposed model is robust with high resilience against eavesdropping, insider attack, and chosen-plaintext attack.

• International Journal of Computer Science & Network Security
• /
• v.21 no.11
• /
• pp.73-80
• /
• 2021

Nowadays microblogs have become the most popular platforms to obtain and spread information. Twitter is one of the most used platforms to share everyday life event. However, rumors and misinformation on Arabic social media platforms has become pervasive which can create inestimable harm to society. Therefore, it is imperative to tackle and study this issue to distinguish the verified information from the unverified ones. There is an increasing interest in rumor detection on microblogs recently, however, it is mostly applied on English language while the work on Arabic language is still ongoing research topic and need more efforts. In this paper, we propose a combined Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) to detect rumors on Twitter dataset. Various experiments were conducted to choose the best hyper-parameters tuning to achieve the best results. Moreover, different neural network models are used to evaluate performance and compare results. Experiments show that the CNN-LSTM model achieved the best accuracy 0.95 and an F1-score of 0.94 which outperform the state-of-the-art methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.12
• /
• pp.4275-4291
• /
• 2021

With the unprecedented growth of textual information on the Internet, an efficient automatic summarization system has become an urgent need. Recently, the neural network models based on the encoder-decoder with an attention mechanism have demonstrated powerful capabilities in the sentence summarization task. However, for paragraphs or longer document summarization, these models fail to mine the core information in the input text, which leads to information loss and repetitions. In this paper, we propose an abstractive document summarization method by applying guidance signals of key sentences to the encoder based on the hierarchical encoder-decoder architecture, denoted as KI-HABS. Specifically, we first train an extractor to extract key sentences in the input document by the hierarchical bidirectional GRU. Then, we encode the key sentences to the key information representation in the sentence level. Finally, we adopt key information representation guided selective encoding strategies to filter source information, which establishes a connection between the key sentences and the document. We use the CNN/Daily Mail and Gigaword datasets to evaluate our model. The experimental results demonstrate that our method generates more informative and concise summaries, achieving better performance than the competitive models.

• International Journal of Computer Science & Network Security
• /
• v.22 no.11
• /
• pp.1-10
• /
• 2022

This study aims to build a model is capable of classifying the categories of hadith, according to the reliability of hadith' narrators (sahih, hassan, da'if, maudu) and according to what was attributed to the Prophet Muhammad (saying, doing, describing, reporting ) using the supervised learning algorithms, with a view to discover a relationship between these classifications, based on the outputs of this model, which might be useful to avoid the controversy and useless debate on automatic classifications of hadith, using some of the statistical methods such as chi-square, information gain and association rules. The experimental results showed that there is a relation between these classifications, most of Sahih hadiths are belong to saying class, and most of maudu hadiths are belong to reporting class. Also the best classifier had given high accuracy was MultinomialNB, it achieved higher accuracy reached up to 0.9708 %, for his ability to process high dimensional problems and identifying the most important features that are relevant to target data in training stage. Followed by LinearSVC classifier, reached up to 0.9655, and finally, KNeighborsClassifier reached up to 0.9644.

• The Journal of Information Systems
• /
• v.32 no.3
• /
• pp.183-203
• /
• 2023

Purpose The purpose of this study is to examine the current operational status and problems of the Public Warning System (PWS) in China, and to propose feasible solutions to improve the performance and efficiency of the PWS through a comparative analysis with the Cell Broadcast Service (CBS)-based disaster SMS system adopted by other developed countries in the world. Design/methodology/approach In this study, the characteristics of PWS using SMS, applications, and CBS, respectively, are analyzed in detail, and compared and analyzed in terms of convenience, standardization, data security, speed, and location accuracy. In addition, CBS-based PWS in developed countries, such as U.S., E.U., Korea and Japan, were studied and their performance on key criteria was evaluated. Findings Based on the results of the study, the problems of China's PWS are summarized and recommendations are made to improve the PWS through the introduction of CBS technology. To this end, specific improvement measures are proposed in terms of the application of CBS technology, system construction and operation, and improvement of data security. In addition, the comparative analysis of PWSs in other developed countries is conducted to provide reference for the direction of PWS's improvement.

• International Journal of Computer Science & Network Security
• /
• v.24 no.2
• /
• pp.89-94
• /
• 2024

Indian subcontinent is a birthplace of multilingual people where documents such as job application form, passport, number plate identification, and so forth is composed of text contents written in different languages/scripts. These scripts may be in the form of different indic numerals in a single document page. Due to this reason, building a generic recognizer that is capable of recognizing handwritten indic digits written by diverse writers is needed. Also, a lot of work has been done for various non-Indic numerals particularly, in case of Roman, but, in case of Indic digits, the research is limited. Moreover, most of the research focuses with only on MNIST datasets or with only single datasets, either because of time restraints or because the model is tailored to a specific task. In this work, a hybrid model is proposed to recognize all available indic handwritten digit images using the existing benchmark datasets. The proposed method bridges the automatically learnt features of Capsule Network with hand crafted Bag of Feature (BoF) extraction method. Along the way, we analyze (1) the successes (2) explore whether this method will perform well on more difficult conditions i.e. noise, color, affine transformations, intra-class variation, natural scenes. Experimental results show that the hybrid method gives better accuracy in comparison with Capsule Network.

• Asia pacific journal of information systems
• /
• v.29 no.4
• /
• pp.817-837
• /
• 2019

The medical industry is rapidly evolving into a combination of artificial intelligence (AI) and ICT technology, such as mobile health, wireless medical, telemedicine and precision medical care. Medical artificial intelligence can be diagnosed and treated, and autonomous surgical robots can be operated. For smart medical services, data such as medical information and personal medical information are needed. AI is being developed to integrate with companies such as Google, Facebook, IBM and others in the health care field. Telemedicine services are also becoming available. However, security issues of medical information for smart medical industry are becoming important. It can have a devastating impact on life through hacking of medical devices through vulnerable areas. Research on medical information is proceeding on the necessity of privacy and privacy protection. However, there is a lack of research on the practical measures for protecting medical information and the seriousness of security threats. Therefore, in this study, we want to confirm the research trend by collecting data related to medical information in recent 5 years. In this study, smart medical related papers from 2014 to 2018 were collected using smart medical topics, and the medical information papers were rearranged based on this. Research trend analysis uses topic modeling technique for topic information. The result constructs topic network based on relation of topics and grasps main trend through topic.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.24 no.4
• /
• pp.635-643
• /
• 2014

Most of the web-based services are provided by a web browser. A web browser receives a text-based web page from the server and translates the received data for the user to view. There are a myriad of add-ons to web browsers that extend browser features. The browser's add-ons may access web pages and make changes to the data. This makes web-services via web browsers are vulnerable to security threats. A web browser stores web page data in memory in the DOM structure. One method that prevents modifications to web page data applies hash values to certain parts in the DOM structure. However, a certain characteristic of web-pages renders this method ineffective at times. Specifically, the user-input data is not pre-determined, and the hash value cannot be calculated prior to user input. Thus the modification to the data cannot be prevented. This paper proposes a method that both detects and inhibits any attempt to change to user-input data. The proposed method stores user-input from the keyboard and makes a comparison with the data transmitted from the web browser to detect any anomalies.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.30 no.3
• /
• pp.465-479
• /
• 2020

Regardless of the domestic and foreign governments/companies, SOC (Security Operation Center) has operated 24 hours a day for the entire year to ensure the security for their IT infrastructures. However, almost all SOCs have a critical limitation by nature, caused from heavily depending on the manual analysis of human agents with the text-based monitoring architecture. Even though, in order to overcome the drawback, technologies for a comprehensive visualization against complex cyber threats have been studying, most of them are inappropriate for the security monitoring in large-scale networks. In this paper, to solve the problem, we propose a novel visual approach for intuitive threats monitoring b detecting suspicious IP address, which is an ultimate challenge in cyber security monitoring. The approach particularly makes it possible to detect, trace and analysis of suspicious IPs statistically in real-time manner. As a result, the system implemented by the proposed method is suitably applied and utilized to the real-would environment. Moreover, the usability of the approach is verified by successful detecting and analyzing various attack IPs.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.1B
• /
• pp.73-85
• /
• 2004

SIn this paper, we introduce our experience for designing and implementing new concept of a global XML-based Peer-to-Peer (P2P) engine to support various P2P applications, and interconnection among PC, Web and mobile computing environments. The proposed P2P engine can support to heterogeneous data exchanges and web interconnection by facilitating with the text-base XML while message exchange are necessary. It is also to provide multi-level security functions as well as to apply different types of security algorithms. The system consist of four modules; a message dispatcher to scheduling and filtering the message, a SecureNet to providing security services and data transmission, a Discovery Manager to constructing peer-to-peer networking, and a Repository Manager to processing data management including XML documents. As a feasibility test, we implement various P2P services such as chatting as a communication service, white-board as an authoring tool set during collaborative working, and a file system as a file sharing service. We also compared the proposed system to a Gnutella in order to measure performance of the systems.