Milad Taleby Ahvanooey

Purpose Nowadays, public opinions during public emergencies involve not only textual contents but also contain images. However, the existing works mainly focus on textual contents and they do not provide a satisfactory accuracy of sentiment analysis, lacking the combination of multimodal contents. In this paper, we propose to combine texts and images generated in the social media to perform sentiment analysis. Design/methodology/approach We propose a Deep Multimodal Fusion Model (DMFM), which combines textual and visual sentiment analysis. We first train word2vec model on a large-scale public emergency corpus to obtain semantic-rich word vectors as the input of textual sentiment analysis. BiLSTM is employed to generate encoded textual embeddings. To fully excavate visual information from images, a modified pretrained VGG16-based sentiment analysis network is used with the best-performed fine-tuning strategy. A multimodal fusion method is implemented to fuse textual and visual embedd...

In this paper, a new method for copyright protection of digital texts using watermarking of encryption message in digital documents is provided. The method is based on the placement of hidden character before and after special writing characters and blank lines between paragraphs in the main text with subtle changes and high resistance. In the proposed approach, the input encrypted message is processed character to character when each character is separately converted to a 16- bit binary number. Before watermarking, at first, one of the two control characters without Unicode length (LRE, RLE) with a hex code (U+202A, U+202B) will be inserted to detect the beginning of the encrypted message than the type of main text (right to left, left to right) and then, the encrypted message that is a set of one or several 8-bit binary numbers is marked in the main text with four hidden characters that have the contract value of even bits of "00, 01, 10, 11" than the position of writing...

PurposeBlockchain technology is a distributed and decentralized public digital ledger, which is employed to save dynamic transaction data and static records across several computers so that each record could not be modified retroactively without the collusion of the network and alteration of all subsequent blocks. Recently, it has become immensely popular in digital resource sharing in different research areas such as healthcare, smart cities, cryptocurrency and libraries. Since the current eLibrary systems are vulnerable to issues such as unauthorized access, plagiarism, etc., there is a lack of access control system that can efficiently address these issues.Design/methodology/approachThe authors designed a conceptual model for evaluating the users' intention in the use of blockchain-based digital libraries, which can facilitate the resource organization and provide additional security to interactive processes between users. To conduct our survey, the authors devised and shared...

Digital Watermarking is required in digital media where access to sensitive information has to be protected against malicious attacks. Since the digital text is one of most widely used digital media on the Internet, the significant part of Web sites, social media, articles, eBooks, and so on is only plain text. Thus, copyrights protection of plaintexts is still a remaining issue that must be improved to provide proof of ownership and obtain desirable accuracy of digital texts. In this research, we propose an intelligent watermarking technique called ANiTH which conceals an invisible watermark through a digital text such that the hidden watermark can be extracted whenever there is an inquiry about the accuracy and reliability of digital texts shared on social media. Experiments demonstrate that the ANiTH can reveal the authenticity and originality of digital texts on social media, where there is a doubt about the text content, whether malicious users have been manipulated it to make ...

Abstract Digital Watermarking is required in multimedia applications where access to sensitive information has to be protected against malicious attacks. Since the digital text is one of the most widely used digital media on the Internet, the significant part of Web sites, social media, articles, eBooks, and so on is only plain text. Thus, copyrights protection of plain-texts is still a remaining issue that must be improved to provide proof of ownership and verify content integrity of vulnerable digital texts. In this research, we propose a novel intelligent text watermarking technique called ANiTW which utilizes an instance-based learning algorithm to hide an invisible watermark into Latin text-based information such that the hidden watermark can be extracted, even if a malicious user manipulates a portion of the watermarked information. Extensive experiments demonstrate the superior efficiency of the ANiTW with a significant improvement especially in the short text domain. To the best of our knowledge, this is the first intelligent text watermarking technique that provides an invisible signature for forensic identification of spurious information on social media by evaluating the manipulation rate of watermarked information, while the other existing approaches only consider the robust/fragile marking of signature into cover text. Copyright © Elsevier Ltd. All rights reserved.

With the ceaseless usage of web and other online services, it has turned out that copying, sharing, and transmitting digital media over the Internet are amazingly simple. Since the text is one of the main available data sources and most widely used digital media on the Internet, the significant part of websites, books, articles, daily papers, and so on is just the plain text. Therefore, copyrights protection of plain texts is still a remaining issue that must be improved in order to provide proof of ownership and obtain the desired accuracy. During the last decade, digital watermarking and steganography techniques have been used as alternatives to prevent tampering, distortion, and media forgery and also to protect both copyright and authentication. This paper presents a comparative analysis of information hiding techniques, especially on those ones which are focused on modifying the structure and content of digital texts. Herein, various text watermarking and text steganography tec...

Modern text hiding is an intelligent programming technique which embeds a secret message/watermark into a cover text message/file in a hidden way to protect confidential information. Recently, text hiding in the form of watermarking and steganography has found broad applications in, for instance, covert communication, copyright protection, content authentication, etc. In contrast to text hiding, text steganalysis is the process and science of identifying whether a given carrier text file/message has hidden information in it, and, if possible, extracting/detecting the embedded hidden information. This paper presents an overview of state of the art of the text hiding area, and provides a comparative analysis of recent techniques, especially those focused on marking structural characteristics of digital text message/file to hide secret bits. Also, we discuss different types of attacks and their effects to highlight the pros and cons of the recently introduced approaches. Finally, we re...

In statistics and machine learning, feature selection is the process of picking a subset of relevant attributes for utilizing in a predictive model. Recently, rough set-based feature selection techniques, that employ feature dependency to perform selection process, have been drawn attention. Classification of tumors based on gene expression is utilized to diagnose proper treatment and prognosis of the disease in bioinformatics applications. Microarray gene expression data includes superfluous feature genes of high dimensionality and smaller training instances. Since exact supervised classification of gene expression instances in such high-dimensional problems is very complex, the selection of appropriate genes is a crucial task for tumor classification. In this study, we present a new technique for gene selection using a discernibility matrix of fuzzy-rough sets. The proposed technique takes into account the similarity of those instances that have the same and different class labels...

Age estimation is a technique for predicting human ages from digital facial images, which analyzes a person's face image and estimates his/her age based on the year measure. Nowadays, intelligent age estimation and age synthesis have become particularly prevalent research topics in computer vision and face verification systems. Age synthesis is defined to render a facial image aesthetically with rejuvenating and natural aging effects on the person's face. Age estimation is defined to label a facial image automatically with the age group (year range) or the exact age (year) of the person's face. In this case study, we overview the existing models, popular techniques, system performances, and technical challenges related to the facial image-based age synthesis and estimation topics. The main goal of this review is to provide an easy understanding and promising future directions with systematic discussions.

Blockchain technology is the most trusted all-in-one cryptosystem that provides a framework for securing transactions over networks due to its irreversibility and immutability characteristics. Blockchain network, as a decentralized infrastructure, has drawn the attention of various startups, administrators, and developers. This system preserves transactions from tampering and provides a tracking tool for tracing past network operations. A personal health record (PHR) system permits patients to control and share data concerning their health conditions by particular peoples. In the case of an emergency, the patient is unable to approve the emergency staff access to the PHR. Furthermore, a history record management system of the patient’s PHR is required, which exhibits hugely private personal data (e.g., modification date, name of user, last health condition, etc.). In this paper, we suggest a healthcare management framework that employs blockchain technology to provide a tamper prote...

Digital Watermarking is required in multimedia applications where access to sensitive information has to be protected against malicious attacks. Since the digital text is one of the most widely used digital media on the Internet, the significant part of Web sites, social media, articles, eBooks, and so on is only plain text. Thus, copyrights protection of plain-texts is still a remaining issue that must be improved to provide proof of ownership and verify content integrity of vulnerable digital texts. In this research, we propose a novel intelligent text watermarking technique called ANiTW which utilizes an instance-based learning algorithm to hide an invisible watermark into Latin text-based information such that the hidden watermark can be extracted, even if a malicious user manipulates a portion of the watermarked information. Extensive experiments demonstrate the superior efficiency of the ANiTW with a significant improvement especially in the short text domain. To the best of our knowledge, this is the first intelligent text watermarking technique that provides an invisible signature for forensic identification of spurious information on social media by evaluating the manipulation rate of watermarked information, while the other existing approaches only consider the robust/fragile marking of signature into cover text.

Nowadays, the usage of smartphones and their applications have become rapidly popular in people's daily life. Over the last decade, availability of mobile money services such as mobile-payment systems and app markets have significantly increased due to the different forms of apps and connectivity provided by mobile devices, such as 3G, 4G, GPRS, and Wi-Fi, etc. In the same trend, the number of vulnerabilities targeting these services and communication networks has raised as well. Therefore, smartphones have become ideal target devices for malicious programmers. With increasing the number of vulnerabilities and attacks, there has been a corresponding ascent of the security countermeasures presented by the researchers. Due to these reasons, security of the payment systems is one of the most important issues in mobile payment systems. In this survey, we aim to provide a comprehensive and structured overview of the research on security solutions for smartphone devices. This survey reviews the state of the art on security solutions, threats, and vulnerabilities during the period of 2011-2017, by focusing on software attacks, such those to smartphone applications. We outline some countermeasures aimed at protecting smartphones against these groups of attacks, based on the detection rules, data collections and operating systems, especially focusing on open source applications. With this categorization, we want to provide an easy understanding for users and researchers to improve their knowledge about the security and privacy of smartphones.

With the popularity of smartphones and widespread use of high-speed Internet, social media has become a vital part of people's daily life. Currently, text messages are used in many applications, such as mobile chatting, mobile banking, and mobile commerce. However, when we send a text message via short message service (SMS) or social media, the information contained in the text message transmits as a plain text, which exposes it to attacks. In some cases, this information may be confidential, such as banking credentials, secret missions, and confidential appointments; moreover, it is a major drawback to send such information via SMS or social media, as neither provides security before transmission. In this paper, we propose a novel text steganography technique called AITSteg, which provides end-to-end security during the transmission of text messages via SMS or social media between end users. The AITSteg technique is evaluated by considering a trusted scenario. We then evaluate the efficiency of the proposed technique in terms of embedding capacity, invisibility, robustness, and security. The experiments confirm that the AITSteg is able to prevent various attacks, including man-in-the-middle attacks, message disclosure, and manipulation by readers. Moreover, we compare the experimental results with the existing techniques to show the superiority of the proposed technique. To the best of our knowledge, this is the first text steganography technique that provides end-to-end secure transmission of the text message using symmetric keys via social media.

With the ceaseless usage of web and other online services, it has turned out that copying, sharing, and transmitting digital media over the Internet are amazingly simple. Since the text is one of the main available data sources and most widely used digital media on the Internet, the significant part of websites, books, articles, daily papers, and so on is just the plain text. Therefore, copyrights protection of plain texts is still a remaining issue that must be improved in order to provide proof of ownership and obtain the desired accuracy. During the last decade, digital watermarking and steganography techniques have been used as alternatives to prevent tampering, distortion, and media forgery and also to protect both copyright and authentication. This paper presents a comparative analysis of information hiding techniques, especially on those ones which are focused on modifying the structure and content of digital texts. Herein, various text watermarking and text steganography techniques characteristics are highlighted along with their applications. In addition, various types of attacks are described and their effects are analyzed in order to highlight the advantages and weaknesses of current techniques. Finally, some guidelines and directions are suggested for future works.

Nowadays, a huge number of images are available. However, retrieving a required image for an ordinary user is a challenging task in computer vision systems. During the past two decades, many types of research have been introduced to improve the performance of the automatic annotation of images, which are traditionally focused on content-based image retrieval. Although, recent research demonstrates that there is a semantic gap between content-based image retrieval and image semantics understandable by humans. As a result, existing research in this area has caused to bridge the semantic gap between low-level image features and high-level semantics. The conventional method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, we propose a novel AIA model based on the deep learning feature extraction method. The proposed model has three phases, including a feature extractor, a tag generator, and an image annotator. First, the proposed model extracts automatically the high and low-level features based on dual tree continues wavelet transform (DT-CWT), singular value decomposition, distribution of color ton, and the deep neural network. Moreover, the tag generator balances the dictionary of the annotated keywords by a new log-entropy auto-encoder (LEAE) and then describes these keywords by word embedding. Finally, the annotator works based on the long-short-term memory (LSTM) network in order to obtain the importance degree of specific features of the image. The experiments conducted on two benchmark datasets confirm that the superiority of proposed model compared to the previous models in terms of performance criteria.

Genetic Programming (GP) is an intelligence technique whereby computer programs are encoded as a set of genes which are evolved utilizing a Genetic Algorithm (GA). In other words, the GP employs novel optimization techniques to modify computer programs; imitating the way humans develop programs by progressively rewriting them for solving problems automatically. Trial programs are frequently altered in the search for obtaining superior solutions due to the base is GA. These are evolutionary search techniques inspired by biological evolution such as mutation, reproduction, natural selection, recombination, and survival of the fittest. The power of GAs is being represented by an advancing range of applications; vector processing, quantum computing, VLSI circuit layout, and so on. But one of the most significant uses of GAs is the automatic generation of programs. Technically, the GP solves problems automatically without having to tell the computer specifically how to process it. To meet this requirement, the GP utilizes GAs to a "population" of trial programs, traditionally encoded in memory as tree-structures. Trial programs are estimated using a "fitness function" and the suited solutions picked for re-evaluation and modification such that this sequence is replicated until a "correct" program is generated. GP has represented its power by modifying a simple program for categorizing news stories, executing optical character recognition, medical signal filters, and for target identification, etc. This paper reviews existing literature regarding the GPs and their applications in different scientific fields and aims to provide an easy understanding of various types of GPs for beginners.

Modern text hiding is an intelligent programming technique which embeds a secret message/watermark into a cover text message/file in a hidden way to protect confidential information. Recently, text hiding in the form of watermarking and steganography has found broad applications in, for instance, covert communication, copyright protection, content authentication, etc. In contrast to text hiding, text steganalysis is the process and science of identifying whether a given carrier text file/message has hidden information in it, and, if possible, extracting/detecting the embedded hidden information. This paper presents an overview of state of the art of the text hiding area, and provides a comparative analysis of recent techniques, especially those focused on marking structural characteristics of digital text message/file to hide secret bits. Also, we discuss different types of attacks and their effects to highlight the pros and cons of the recently introduced approaches. Finally, we recommend some directions and guidelines for future works.

Personal health records (PHRs) are private and vital assets for every patient. There have been introduced many works on various aspects of managing and organizing the PHR so far. However, there is an uncertain remaining issue for the role of PHR in emergencies. In a traditional emergency access system, the patient cannot give consent to emergency staff for accessing his/her PHR. Moreover, there is no secured record management of patient's PHR, which reveals highly confidential personal information, such as what happened, when, and who has access to such information. This paper proposes an emergency access control management system (EACMS) based on permissioned blockchain hyperledger fabric and hyperledger composer. In the proposed system, we defined some rules using the smart contracts for emergency condition and time duration for the emergency access PHR data items that patient can assign some limitations for controlling the PHR permissions. We analyzed the performance of our proposed framework by implementing it through the hyperledger composer based on the response time, privacy, security, and accessibility. The experiments confirm that our framework provides better efficiency compared with the traditional emergency access system. INDEX TERMS Personal health record, emergency access, access authorization, blockchain, hyperledger fabric, hyperledger composer, privacy & security.

The traditional security risk monitoring technology cannot adapt to cyber-physical power systems (CPPS) concerning evaluation criteria, real-time monitoring, and technical reliability. The aim of this paper is to propose and implement a log analysis architecture for CPPS to detect the log anomalies, which introduces the distributed streaming processing mechanism. The processing mechanism can train the network protocol feature database precisely over the big data platform, which improves the efficiency of the network in terms of log anomaly detection. Moreover, we propose an ensemble prediction algorithm based on time series (EPABT) considering the characteristics of the statistical log analysis to predict abnormal features during the network traffic analysis. We then present a new asymmetric error cost (AEC) evaluation criterion to meet the characteristics of CPPS. The experimental results demonstrate that the EPABT provides an efficient tool for detecting the accuracy and reliability of abnormal situation prediction as compared with the several state-of-the-art algorithms. Meanwhile, the AEC can effectively evaluate the differences in the cost between the high and low prediction results. To the best of our knowledge, these two algorithms provide strong support for the practical application of power industrial network security risk monitoring.

In this paper, a new method for copyright protection of digital texts using watermarking of encryption message in digital documents is provided. The method is based on the placement of hidden character before and after special writing characters and blank lines between paragraphs in the main text with subtle changes and high resistance. In the proposed approach, the input encrypted message is processed character to character when each character is separately converted to a 16-bit binary number. Before watermarking, at first, one of the two control characters without Unicode length (LRE, RLE) with a hex code (U+202A, U+202B) will be inserted to detect the beginning of the encrypted message than the type of main text (right to left, left to right) and then, the encrypted message that is a set of one or several 8-bit binary numbers is marked in the main text with four hidden characters that have the contract value of even bits of " 00, 01, 10, 11 " than the position of writing special characters, the beginning of paragraphs and blank lines between paragraphs with two hidden characters. In other words, after each index position in the text, two hidden character is inserted and this process as much as a whole bites of message in the text is watermarking, will be repeated and at the end of each message, the length of encrypted message is also watermarking until the accuracy of message is investigated during message detection. 1. INTRODUCTION In the modern world, digitization of documents and increasing extension of the internet caused extensive changes in the life and professional activities of individual, organizations and institutions. Secure distribution in digital communication substrates is one of the common issues of legal and real personalities. Assurance of lack of access of unauthorized persons to sensitive information is the major security concerns in relations to the distribution of information on the internet. Important information that documents owners is unwilling to see and manipulate them by others, include many items that digital texts form a massive volume, over 90 percent of this information. Due to the extensive volume of text data in the today world and share it on the internet, the need to conduct research works in this area isn't hidden for anyone, watermarking of digital documents as a secret technique in the digital texts can be used for many cases. For example, one of the cases that are now seriously taken into consideration is prevention of document manipulation and acts of copyright as it lies in its effect. Text watermarking can be used in many applications such as authentication, prevention of unauthorized copying, confidential and secret communication, manipulation detection and etc [1,2,3,4]. Whereas, given all the benefits of digital texts watermarking that only part of it noted, until today, according to many efforts, existed methods in watermarking of different texts with different Orthography doesn't have the same performance and this area still needs attention and research to reach full maturity in this direction. In recent years, many studies have been proposed for watermarking by using Unicode hidden characters but the work presented in this work, as far as we are aware, is the first attempts that were made to digital texts watermarking in different languages with different orthography.

In this paper, a new method to protect digital content from unauthorized copying
using watermarking message in digital documents like (MS Word, MS Excel) is
presented which this work is done using hidden Unicode characters insertion
toward positions of special punctuation characters (e.g., commas, dots, commas,
double quotation, etc.) in the main text, with subtle changes.
In the method presented, character message processed into characters and each
character separately converted into an 8-bit binary number. Before
watermarking, the message length that is an 8-bit binary complex, is first marked
in main context as pair-bit "00, 01, 10, 11" toward the special character positions.
To do this, for every character, Four hidden characters (without Unicode length)
is intended, in other words, after a specific character in the context of four couple
bits are marked with four signs and the process will be repeated to watermark all
message bits in context.
In this method, due to the possibility of attacks of varied shifts, the message will
be watermarked several times to the end of the file. This method increases the
resistant against attacks of character change.

Embedding a hidden stream of bits in a cover file to prevent illegal use is called digital watermarking. The cover file could be a text, image, video, or audio. In this study, we propose invisible watermarking based on the text included in a webpage. Watermarks are based on predefined structural and syntactic rules, which are encrypted and then converted into zero-width control characters using binary model classification before embedding into a webpage. This concept means that HTML (Hyper Text Markup Language) is used as a cover file to embed the hashed and transparent zero-width watermarks. We have implemented the proposed invisible watermarking against various attacks to reach optimum robustness.