scholarly journals Steganographic Analysis of Blockchains

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4078
Author(s):  
Alexandre Augusto Giron ◽  
Jean Everson Martina ◽  
Ricardo Custódio
Keyword(s):  
Clustering Analysis ◽  
Sequential Analysis ◽  
Real Case ◽  
Essential Aspect ◽  
Actual Use ◽  
Hide Data ◽  
Hidden Data

Steganography is one of the ways to hide data between parties. Its use can be worrisome, e.g., to hide illegal communications. Researchers found that public blockchains can be an attractive place to hide communications; however, there is not much evidence of actual use in blockchains. Besides, previous work showed a lack of steganalysis methods for blockchains. In this context, we present a steganalysis approach for blockchains, evaluating it in Bitcoin and Ethereum, both popular cryptocurrencies. The main objective is to answer if one can find steganography in real case scenarios, focusing on LSB of addresses and nonces. Our sequential analysis included 253 GiB and 107 GiB of bitcoin and ethereum, respectively. We also analyzed up to 98 million bitcoin clusters. We found that bitcoin clusters could carry up to 360 KiB of hidden data if used for such a purpose. We have not found any concrete evidence of hidden data in the blockchains. The sequential analysis may not capture the perspective of the users of the blockchain network. In this case, we recommend clustering analysis, but it depends on the clustering method’s accuracy. Steganalysis is an essential aspect of blockchain security.

scholarly journals INFUSE: Invisible plausibly-deniable file system for NAND flash

2020 ◽  
Vol 2020 (4) ◽  
pp. 239-254
Author(s):  
Chen Chen ◽  
Anrin Chakraborti ◽  
Radu Sion
Keyword(s):  
File System ◽  
Nand Flash ◽  
Data Loss ◽  
Storage Medium ◽  
Sensitive Data ◽  
Storage Devices ◽  
Public Data ◽  
Hide Data ◽  
Hidden Data ◽  
Local Storage

AbstractProtecting sensitive data stored on local storage devices e.g., laptops, tablets etc. is essential for privacy. When adversaries are powerful enough to coerce users to reveal encryption keys/passwords, encryption alone becomes insufficient for data protection. Additional mechanisms are required to hide the very presence of sensitive data.Plausibly deniable storage systems (PDS) are designed to defend against such powerful adversaries. Plausible deniability allows a user to deny the existence of certain stored data even when an adversary has access to the storage medium. However, existing plausible deniability solutions leave users at the mercy of adversaries suspicious of their very use. Indeed, it may be difficult to justify the use of a plausible deniability system while claiming that no sensitive data is being hidden.This work introduces INFUSE, a plausibly-deniable file system that hides not only contents but also the evidence that a particular system is being used to hide data. INFUSE is “invisible” (identical layout with standard file system), provides redundancy, handles overwrites, survives data loss, and is secure in the presence of multi-snapshot adversaries. INFUSE is efficient. Public data operations are orders of magnitude faster than existing multi-snapshot resilient PD systems, and only 15% slower than a standard non-PD baseline, and hidden data operations perform comparably to existing systems.

scholarly journals Understanding the Behavioural Patterns of University Teachers Toward Using a Learning Management System

2021 ◽  
Vol 16 (14) ◽  
pp. 129
Author(s):  
Chien-Yuan Su ◽  
Yu-Hang Li ◽  
Cheng-Huan Chen
Keyword(s):  
Clustering Analysis ◽  
Sequential Analysis ◽  
Public University ◽  
University Teachers ◽  
Analysis Techniques ◽  
Behavioural Patterns ◽  
University Instructors ◽  
Behavioural Types ◽  
Learning Management ◽  
The University

Recent research has been very attentive to the examination of learners’ behavioural patterns of using learning management systems (LMS), but these studies seldom address the diversity in the LMS usage behaviours of teachers. This study aimed to discover the behavioural patterns of university instructors regarding the use of an LMS by using sequential and clustering analysis techniques. The usage behaviours of 268 teachers at a public university in China were extracted from the Blackboard platform over the course of one-semester. These behaviours were classified according to five different LMS behavioural types: (1) course and content; (2) assignment; (3) communication and collaboration; (4) assessment; and (5) administration. The results indicated that the most frequent teachers’ LMS usage behaviour was course and content followed by assessment and administration. The results of the sequential analysis indicated that most of the instructors are used to adopting communication and collaboration and assignment when they finish using course and content. In addition, three distinct usage behavioural pattern subgroups were named as teachers preferred assessment, teachers of regular use, and teachers of less use. Implications of these findings are discussed in the light of the university teachers’ behavioural patterns toward using the LMS.

scholarly journals Corners-based Image Information Hiding Method

2017 ◽  
Vol 43 (1) ◽  
pp. 1-5
Author(s):  
Ahmed Talib
Keyword(s):  
World Wide Web ◽  
Information Security ◽  
Statistical Methods ◽  
Information Hiding ◽  
World Wide ◽  
Svm Classifier ◽  
Data Embedding ◽  
Stego Image ◽  
Hide Data ◽  
Hidden Data

The huge explosion of information over World Wide Web forces us to use information security methods to keep it away fromintruders. One of these security methods is information hiding method. Advantage of this method over other security methods is hidingexistence of data using carrier to hold this data embedding inside it. Image-based information hiding represents one of widely usedhiding methods due to the image capability of holding large amount of data as well as its resistance to detectable distortion. In lastdecades, statistical methods (types of stego-analysis methods) are used to detect existing of hidden data. Therefore, areas that have colorvariation (edges area) are used to hide data instead of smooth areas. In this paper, Corners points are proposed to hide data instead ofedges, this to avoid statistical attacks that are used to expose hidden message. Additionally, this paper proposes clearing least significantbit (CLSB) method to retrieve data from stego-image without sending pixels' map; this will increase security of the proposed cornerbasedhiding method. Experimental results show that the proposed method is robust against statistical attacks compared with edge-and sequential-based hiding methods. SVM classifier also confirms the outperformance of the proposed method over the previous methods by using Corel-1000image dataset.

scholarly journals A Novel and Robust Hybrid Blockchain and Steganography Scheme

2021 ◽  
Vol 11 (22) ◽  
pp. 10698
Author(s):  
Mustafa Takaoğlu ◽  
Adem Özyavaş ◽  
Naim Ajlouni ◽  
Ali Alsahrani ◽  
Basil Alkasasbeh
Keyword(s):  
Data Hiding ◽  
High Resistance ◽  
Data Security ◽  
Histogram Analysis ◽  
Test Results ◽  
Low Resistance ◽  
Hide Data ◽  
Hidden Data

Data security and data hiding have been studied throughout history. Studies show that steganography and encryption methods are used together to hide data and avoid detection. Large amounts of data hidden in the cover multimedia distort the image, which can be detected in visual and histogram analysis. The proposed method will solve two major drawbacks of the current methods: the limitation imposed on the size of the data to be hidden in the cover multimedia and low resistance to steganalysis after stego-operation. In the proposed method, plaintext data are divided into fixed-sized bits whose corresponding matching bits’ indices in the cover multimedia are accumulated. Thus, the hidden data are composed of the indices in the cover multimedia, causing no change in it, thus enabling considerable amounts of plaintext to be hidden. The proposed method also has high resistance to known steganalysis methods because it does not cause any distortion to the cover multimedia. The test results show that the performance of the proposed method outperforms similar conventional stenographic techniques. The proposed Ozyavas–Takaoglu–Ajlouni (OTA) method relieves the limitation on the size of the hidden data, and hidden data is undetectable by steganalysis because it is no longer embedded in the cover multimedia.

Detecting and Distinguishing Adaptive and Non-Adaptive Steganography by Image Segmentation

2019 ◽  
Vol 11 (1) ◽  
pp. 62-77 ◽  
Author(s):  
Jie Zhu ◽  
Xianfeng Zhao ◽  
Qingxiao Guan
Keyword(s):  
Image Segmentation ◽  
Adaptive Algorithms ◽  
Adaptive Steganography ◽  
Spatial Image ◽  
Different Types ◽  
Hide Data ◽  
Hidden Data ◽  
The Impact ◽  
Blind Steganalysis ◽  
Different Levels

This article describes how blind steganalysis aiming at uncovering the existence of hidden data in digital images remains an open problem. Conventional spatial image steganographic algorithms hide data into pixels spreading evenly in the entire cover image, while the content-adaptive algorithms prefer the textural areas and edge regions. In this article, the impact of image content on blind steganalysis is discussed and a practical and extensible approach to distinguish the different types of steganography and construct blind steganalytic detector is proposed. Through the technique of image segmentation, the images are segmented into sub-images with different levels of texture. The classifier only cares for the sub-images which can help modeling the statistical detectability and is trained on sub-images instead of the entire image. Experimental results show the authors' scheme can recognize the type of steganographic methods reliably. The further steps to improve capacity of blind steganalysis based on image segmentation are also mentioned and achieve better performance than ordinary blind steganalysis.

scholarly journals A computational forensic framework for detection of hidden applications on android

2020 ◽  
Vol 20 (1) ◽  
pp. 353
Author(s):  
Tahira Rasul ◽  
Rabia Latif ◽  
Nor Shahida Mohd Jamail
Keyword(s):  
Criminal Court ◽  
Security And Privacy ◽  
Court Case ◽  
Sensitive Information ◽  
Efficient Manner ◽  
Case File ◽  
Privacy Threats ◽  
Hide Data ◽  
Hidden Data ◽  
Google Play

<span>Smartphones, since their emergence has become a significant part of our lives and Android is popular of all. They are successful due to the increasing availability of user applications to answer every possible need, so it is of great importance to ensure security and privacy when handling personal and sensitive information of the user. To secure the data on mobile devices, users use applications available on the Google Play store, which help to hide data on their devices known as Hidden Applications. Hidden applications are categorized as one of the major applications used for data hiding and storing. These applications can be used to hide date from snooping, intrusion and against the data theft. Therefore, the proposed framework in this research helps to find either they store and hide data in efficient manner or not and if they do so either it is encrypted or not. In this paper, main objective is to identify the privacy threats which end users face by using such applications, analyse these application’s behaviour, working, their code to understand how data is hidden and if the information is encrypted, it can be retrieved or not. The work not only focuses on the identification of hidden data/apps; it also provides a mechanism to recover and reconstruct the data from these hidden parts of the memory. In the end, present the results obtained by using the proposed framework in a case file so that it can be used in a criminal court case.</span>

Trust in Management Information Systems (MIS)

2020 ◽  
Vol 64 (1) ◽  
pp. 6-16 ◽  
Author(s):  
Sarah M. Meeßen ◽  
Meinald T. Thielsch ◽  
Guido Hertel
Keyword(s):  
Information Systems ◽  
Information Overload ◽  
Management Information Systems ◽  
Empirical Work ◽  
Future Research ◽  
Management Information ◽  
Trust In Management ◽  
Actual Use ◽  
Trust In Technology ◽  
The Internet Of Things

Abstract. Digitalization, enhanced storage capacities, and the Internet of Things increase the volume of data in modern organizations. To process and make use of these data and to avoid information overload, management information systems (MIS) are introduced that collect, process, and analyze relevant data. However, a precondition for the application of MIS is that users trust them. Extending accounts of trust in automation and trust in technology, we introduce a new model of trust in MIS that addresses the conceptual ambiguities of existing conceptualizations of trust and integrates initial empirical work in this field. In doing so, we differentiate between perceived trustworthiness of an MIS, experienced trust in an MIS, intentions to use an MIS, and actual use of an MIS. Moreover, we consider users’ perceived risks and contextual factors (e. g., autonomy at work) as moderators. The introduced model offers guidelines for future research and initial suggestions to foster trust-based MIS use.

Applicants’ Self-Presentational Behavior

2012 ◽  
Vol 11 (2) ◽  
pp. 77-85 ◽  
Author(s):  
Anne Jansen ◽  
Cornelius J. König ◽  
Eveline H. Stadelmann ◽  
Martin Kleinmann
Keyword(s):  
Personnel Selection ◽  
Randomized Response Technique ◽  
Randomized Response ◽  
Self Presentation ◽  
Actual Use

This study contributes to the literature on self-presentation by comparing recruiters’ expectations about applicants’ self-presentational behaviors in personnel selection settings to applicants’ actual use of these behaviors. Recruiters (N = 51) rated the perceived appropriateness of 24 self-presentational behaviors. In addition, the prevalence of these behaviors was separately assessed in two subsamples of applicants (N1 = 416 and N2 = 88) with the randomized response technique. In line with the script concept, the results revealed that recruiters similarly evaluated the appropriateness of specific self-presentational behaviors and that applicants’ general use of these behaviors corresponded to recruiters’ shared expectations. The findings indicate that applicants who use strategic self-presentational behaviors may just be trying to fulfill situational requirements.

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