scholarly journals A Novel Secure Data Hiding Technique into Video Sequences Using RVIHS

2021 ◽  
Vol 13 (2) ◽  
pp. 53-65
Author(s):  
Vinay D R ◽  
◽  
Ananda Babu J
Keyword(s):  
Scale Up ◽  
Video Sequences ◽  
Support Vector ◽  
Embedding Capacity ◽  
Secret Key ◽  
Machine Grouping ◽  
The Public ◽  
Video Information ◽  
Information Embedding ◽  
Multiple Chaotic Maps

Most of the present hiding techniques on video are considered over plaintext domain and plain video sequences are used to embed information bits. The work presented here reveals the novelty for information embedding in a video sequence over the ciphered domain. The carrier video signal is encrypted using chaos technique which uses multiple chaotic maps for encryption. The proposed reversible video information hiding scheme (RVIHS) exhibits an innovative property that, at the decoding side we can perfectly extract the information along with carrier video without any distortion. The public key modulation is a mechanism used to achieve data embedding, where as in secret key encryption is not required. The proposed approach is used to differentiate encoded and non-encoded picture patches at decoder end by implementing 2 class Support Vector Machine grouping. This helps for us to retrieve the original visual sequence with embedded message and to scale up embedding capacity. The experiment is conducted using real time videos for embedding the information. The outcome of proposed work bring about best embedding capacity, compared to existing techniques.

Detecting “DeepFakes” in H.264 Video Data Using Compression Ghost Artifacts

2020 ◽  
Vol 2020 (4) ◽  
pp. 116-1-116-7
Author(s):  
Raphael Antonius Frick ◽  
Sascha Zmudzinski ◽  
Martin Steinebach
Keyword(s):  
Image Forensics ◽  
Video Data ◽  
Experimental Results ◽  
Video Sequences ◽  
The Internet ◽  
Video Content ◽  
High Quality ◽  
The Public

In recent years, the number of forged videos circulating on the Internet has immensely increased. Software and services to create such forgeries have become more and more accessible to the public. In this regard, the risk of malicious use of forged videos has risen. This work proposes an approach based on the Ghost effect knwon from image forensics for detecting forgeries in videos that can replace faces in video sequences or change the mimic of a face. The experimental results show that the proposed approach is able to identify forgery in high-quality encoded video content.

Algorithm Comparation of Naive Bayes and Support Vector Machine based on Particle Swarm Optimization in Sentiment Analysis of Freight Forwarding Services

2020 ◽  
Vol 4 (2) ◽  
pp. 362-369
Author(s):  
Sharazita Dyah Anggita ◽  
Ikmah
Keyword(s):  
Support Vector Machine ◽  
Sentiment Analysis ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Support Vector ◽  
The Public ◽  
Svm Algorithm ◽  
Bayes Algorithm ◽  
Freight Forwarding ◽  
Improved Accuracy

The needs of the community for freight forwarding are now starting to increase with the marketplace. User opinion about freight forwarding services is currently carried out by the public through many things one of them is social media Twitter. By sentiment analysis, the tendency of an opinion will be able to be seen whether it has a positive or negative tendency. The methods that can be applied to sentiment analysis are the Naive Bayes Algorithm and Support Vector Machine (SVM). This research will implement the two algorithms that are optimized using the PSO algorithms in sentiment analysis. Testing will be done by setting parameters on the PSO in each classifier algorithm. The results of the research that have been done can produce an increase in the accreditation of 15.11% on the optimization of the PSO-based Naive Bayes algorithm. Improved accuracy on the PSO-based SVM algorithm worth 1.74% in the sigmoid kernel.

scholarly journals Strategies for involving patients and the public in scaling-up initiatives in health and social services: protocol for a scoping review and Delphi survey

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Ali Ben Charif ◽  
◽  
Karine V. Plourde ◽  
Sabrina Guay-Bélanger ◽  
Hervé Tchala Vignon Zomahoun ◽  
...  
Keyword(s):  
Social Services ◽  
Scoping Review ◽  
Delphi Study ◽  
Public Involvement ◽  
Scale Up ◽  
Scaling Up ◽  
Delphi Survey ◽  
The Public ◽  
Health And Social Services ◽  
Scoping Reviews

Abstract Background The scale-up of evidence-based innovations is required to reduce waste and inequities in health and social services (HSS). However, it often tends to be a top-down process initiated by policy makers, and the values of the intended beneficiaries are forgotten. Involving multiple stakeholders including patients and the public in the scaling-up process is thus essential but highly complex. We propose to identify relevant strategies for meaningfully and equitably involving patients and the public in the science and practice of scaling up in HSS. Methods We will adapt our overall method from the RAND/UCLA Appropriateness Method. Following this, we will perform a two-prong study design (knowledge synthesis and Delphi study) grounded in an integrated knowledge translation approach. This approach involves extensive participation of a network of stakeholders interested in patient and public involvement (PPI) in scaling up and a multidisciplinary steering committee. We will conduct a systematic scoping review following the methodology recommended in the Joanna Briggs Institute Reviewers Manual. We will use the following eligibility criteria: (1) participants—any stakeholder involved in creating or testing a strategy for PPI; (2) intervention—any PPI strategy proposed for scaling-up initiatives; (3) comparator—no restriction; (4) outcomes: any process or outcome metrics related to PPI; and (5) setting—HSS. We will search electronic databases (e.g., Medline, Web of Science, Sociological Abstract) from inception onwards, hand search relevant websites, screen the reference lists of included records, and consult experts in the field. Two reviewers will independently select and extract eligible studies. We will summarize data quantitatively and qualitatively and report results using the PRISMA extension for Scoping Reviews (PRISMA-ScR) checklist. We will conduct an online Delphi survey to achieve consensus on the relevant strategies for PPI in scaling-up initiatives in HSS. Participants will include stakeholders from low-, middle-, and high-income countries. We anticipate that three rounds will allow an acceptable degree of agreement on research priorities. Discussion Our findings will advance understanding of how to meaningfully and equitably involve patients and the public in scaling-up initiatives for sustainable HSS. Systematic review registration We registered this protocol with the Open Science Framework on August 19, 2020 (https://osf.io/zqpx7/).

scholarly journals Framing Twitter Public Sentiment on Nigerian Government COVID-19 Palliatives Distribution Using Machine Learning

2021 ◽  
Vol 13 (6) ◽  
pp. 3497
Author(s):  
Hassan Adamu ◽  
Syaheerah Lebai Lutfi ◽  
Nurul Hashimah Ahamed Hassain Malim ◽  
Rohail Hassan ◽  
Assunta Di Vaio ◽  
...  
Keyword(s):  
Machine Learning ◽  
Support Vector Machine ◽  
Nearest Neighbor ◽  
Primary Objective ◽  
Support Vector ◽  
Standard English ◽  
Emotion Classification ◽  
K Nearest Neighbor ◽  
The Public ◽  
The Government

Sustainable development plays a vital role in information and communication technology. In times of pandemics such as COVID-19, vulnerable people need help to survive. This help includes the distribution of relief packages and materials by the government with the primary objective of lessening the economic and psychological effects on the citizens affected by disasters such as the COVID-19 pandemic. However, there has not been an efficient way to monitor public funds’ accountability and transparency, especially in developing countries such as Nigeria. The understanding of public emotions by the government on distributed palliatives is important as it would indicate the reach and impact of the distribution exercise. Although several studies on English emotion classification have been conducted, these studies are not portable to a wider inclusive Nigerian case. This is because Informal Nigerian English (Pidgin), which Nigerians widely speak, has quite a different vocabulary from Standard English, thus limiting the applicability of the emotion classification of Standard English machine learning models. An Informal Nigerian English (Pidgin English) emotions dataset is constructed, pre-processed, and annotated. The dataset is then used to classify five emotion classes (anger, sadness, joy, fear, and disgust) on the COVID-19 palliatives and relief aid distribution in Nigeria using standard machine learning (ML) algorithms. Six ML algorithms are used in this study, and a comparative analysis of their performance is conducted. The algorithms are Multinomial Naïve Bayes (MNB), Support Vector Machine (SVM), Random Forest (RF), Logistics Regression (LR), K-Nearest Neighbor (KNN), and Decision Tree (DT). The conducted experiments reveal that Support Vector Machine outperforms the remaining classifiers with the highest accuracy of 88%. The “disgust” emotion class surpassed other emotion classes, i.e., sadness, joy, fear, and anger, with the highest number of counts from the classification conducted on the constructed dataset. Additionally, the conducted correlation analysis shows a significant relationship between the emotion classes of “Joy” and “Fear”, which implies that the public is excited about the palliatives’ distribution but afraid of inequality and transparency in the distribution process due to reasons such as corruption. Conclusively, the results from this experiment clearly show that the public emotions on COVID-19 support and relief aid packages’ distribution in Nigeria were not satisfactory, considering that the negative emotions from the public outnumbered the public happiness.

A CUBIC EL-GAMAL ENCRYPTION SCHEME BASED ON LUCAS SEQUENCE AND ELLIPTIC CURVE

2021 ◽  
Vol 10 (11) ◽  
pp. 3439-3447
Author(s):  
T. J. Wong ◽  
L. F. Koo ◽  
F. H. Naning ◽  
A. F. N. Rasedee ◽  
M. M. Magiman ◽  
...  
Keyword(s):  
Elliptic Curve ◽  
Elliptic Curve Cryptography ◽  
Mathematical Problem ◽  
Public Key ◽  
Public Key Cryptosystem ◽  
Encryption Scheme ◽  
Secret Key ◽  
Chosen Plaintext Attack ◽  
The Public ◽  
Lucas Sequence

The public key cryptosystem is fundamental in safeguard communication in cyberspace. This paper described a new cryptosystem analogous to El-Gamal encryption scheme, which utilizing the Lucas sequence and Elliptic Curve. Similar to Elliptic Curve Cryptography (ECC) and Rivest-Shamir-Adleman (RSA), the proposed cryptosystem requires a precise hard mathematical problem as the essential part of security strength. The chosen plaintext attack (CPA) was employed to investigate the security of this cryptosystem. The result shows that the system is vulnerable against the CPA when the sender decrypts a plaintext with modified public key, where the cryptanalyst able to break the security of the proposed cryptosystem by recovering the plaintext even without knowing the secret key from either the sender or receiver.

scholarly journals High Embedding Capacity Data Hiding Algorithm for H.264/AVC Video Sequences without Intraframe Distortion Drift

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Dinh-Chien Nguyen ◽  
Thai-Son Nguyen ◽  
Chin-Chen Chang ◽  
Huan-Sheng Hsueh ◽  
Fang-Rong Hsu
Keyword(s):  
Digital Media ◽  
Data Hiding ◽  
Video Sequences ◽  
Embedding Capacity ◽  
Secret Data ◽  
Low Distortion ◽  
High Embedding Capacity ◽  
Advanced Video Coding ◽  
Distortion Drift ◽  
Capacity Data

Data hiding is a technique that allows secret data to be delivered securely by embedding the data into cover digital media. In this paper, we propose a new data hiding algorithm for H.264/advanced video coding (AVC) of video sequences with high embedding capacity. In the proposed scheme, to embed secret data into the quantized discrete cosine transform (QDCT) coefficients of I frames without any intraframe distortion drift, some embeddable coefficient pairs are selected in each block, and they are divided into two different groups, i.e., the embedding group and the averting group. The embedding group is used to carry the secret data, and the averting group is used to prevent distortion drift in the adjacent blocks. The experimental results show that the proposed scheme can avoid intraframe distortion drift and guarantee low distortion of video sequences. In addition, the proposed scheme provides enhanced embedding capacity compared to previous schemes. Moreover, the embedded secret data can be extracted completely without the requirement of the original secret data.

scholarly journals Design and development of a secure certificateless proxy signature based (SE-CLPS) encryption scheme for cloud storage

2021 ◽  
Vol 10 (1) ◽  
pp. 57
Author(s):  
Ms. K. Sudharani ◽  
Dr. N. K. Sakthivel
Keyword(s):  
Computational Cost ◽  
Public Key Cryptography ◽  
True Positive Rate ◽  
Proxy Signature ◽  
Attack Detection ◽  
Third Party ◽  
Public Key ◽  
Secret Key ◽  
True Negative ◽  
The Public

Certificateless Public Key Cryptography (CL-PKC) scheme is a new standard that combines Identity (ID)-based cryptography and tradi- tional PKC. It yields better security than the ID-based cryptography scheme without requiring digital certificates. In the CL-PKC scheme, as the Key Generation Center (KGC) generates a public key using a partial secret key, the need for authenticating the public key by a trusted third party is avoided. Due to the lack of authentication, the public key associated with the private key of a user may be replaced by anyone. Therefore, the ciphertext cannot be decrypted accurately. To mitigate this issue, an Enhanced Certificateless Proxy Signature (E-CLPS) is proposed to offer high security guarantee and requires minimum computational cost. In this work, the Hackman tool is used for detecting the dictionary attacks in the cloud. From the experimental analysis, it is observed that the proposed E-CLPS scheme yields better Attack Detection Rate, True Positive Rate, True Negative Rate and Minimum False Positives and False Negatives than the existing schemes.   

scholarly journals Study protocol for Post Pregnancy Family Planning Choices, an operations research study examining the effectiveness of interventions in the public and private sectors in Indonesia and Kenya

2020 ◽  
Vol 4 ◽  
pp. 89
Author(s):  
Elaine Charurat ◽  
Sara Kennedy ◽  
Siti Qomariyah ◽  
Anne Schuster ◽  
Megan Christofield ◽  
...  
Keyword(s):  
Family Planning ◽  
Study Protocol ◽  
Operations Research ◽  
Research Study ◽  
Scale Up ◽  
Unmet Need ◽  
Study Data ◽  
Multiple Time ◽  
Public And Private ◽  
The Public

Background: Global evidence suggests many postpartum and postabortion women have an unmet need for family planning (FP) after delivery or receiving care following loss of a pregnancy. Post Pregnancy Family Planning Choices, an operations research study, aims to examine the effectiveness of a package of postpregnancy FP interventions, inclusive of postpartum and postabortion FP. The interventions are being implemented in selected public and private facilities in Indonesia and Kenya and focus on quality FP counseling and service provision prior to discharge. This manuscript presents the study protocol, documenting how the study team intends to determine key factors that influence uptake of postpregnancy FP. Methods: This is a multi-country, quasi-experimental operations research study in Brebes and Batang Districts of Indonesia and Meru and Kilifi Counties of Kenya. Quantitative and qualitative data is collected from multiple data sources and participants through interviews and assessments at multiple time points. Participants include health facilities; antenatal, postpartum, and postabortion clients; and key informants at national, subnational, facility, and community levels. Quantitative study data is collected and managed through the use of REDCap (Research Electronic Data Capture). Once data are thoroughly cleaned and reviewed, regression models and multilevel analyses will explore quantitative data. Qualitative study data is collected using audio recordings and transcribed to Microsoft Word, then analyzed using ATLAS.ti. Qualitative datasets will be analyzed using grounded theory methods. Discussion: The ultimate goals of the study are to generate and disseminate actionable evidence of positive drivers, barriers, and activities that do not yield results with regard to increasing postpregnancy FP programmatic activities, and to institutionalize postpregnancy FP in the public and private sectors in Indonesia and Kenya. We hope these learnings and experience will contribute to global efforts to advance and scale up postpregnancy FP in similar settings beyond these two countries. Trial registration: ClinicalTrials.gov NCT03333473

scholarly journals Liveness Measurements Using Optical Flow for Biometric Person Authentication

2012 ◽  
Vol 19 (2) ◽  
pp. 257-268 ◽  
Author(s):  
Maciej Smiatacz
Keyword(s):  
Optical Flow ◽  
Video Sequences ◽  
Support Vector ◽  
Biometric Identification ◽  
Behavioral Characteristics ◽  
Security Level ◽  
Identification Algorithm ◽  
Face Region ◽  
The Face ◽  
Consumer Devices

Liveness Measurements Using Optical Flow for Biometric Person Authentication Biometric identification systems, i.e. the systems that are able to recognize humans by analyzing their physiological or behavioral characteristics, have gained a lot of interest in recent years. They can be used to raise the security level in certain institutions or can be treated as a convenient replacement for PINs and passwords for regular users. Automatic face recognition is one of the most popular biometric technologies, widely used even by many low-end consumer devices such as netbooks. However, even the most accurate face identification algorithm would be useless if it could be cheated by presenting a photograph of a person instead of the real face. Therefore, the proper liveness measurement is extremely important. In this paper we present a method that differentiates between video sequences showing real persons and their photographs. First we calculate the optical flow of the face region using the Farnebäck algorithm. Then we convert the motion information into images and perform the initial data selection. Finally, we apply the Support Vector Machine to distinguish between real faces and photographs. The experimental results confirm that the proposed approach could be successfully applied in practice.

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