Hybrid Approach to Steganography System Based on Quantum Encryption and Chaos Algorithms

This paper proposes a hybrid system for secretly embedding images into the dithered multilevelimage. Confident hybridizations between steganography and quantum encryptions are either rare inliterature or suffer a poor effectiveness in secure communication. This paper scrambles and divides thesecret image into groups to be embedded in the blocks of the cover image using three chaos algorithms.These are Lorenz map, Henon map, and Logistic map algorithms. The encryption of embedded imagesconducted using the quantum one-time pad. Results showed that the proposed hybrid system succeeded inembedding and combining images with quantum cryptography algorithms

Securing medical records based on inter-planetary file system and blockchain

In general, health records include important information like the patient’s history, findings of examinations and assessments, diagnosis reports, documentation of consent, and treatment plans. Sharing this information has grown to be a challenge concerning data security, as it could result in compromising patient privacy. Therefore, the patient's information should not be misused or tampered with. In this paper, a full process of storing and retrieving medical records is proposed using a decentralized system through the integration of two emerging technologies: Blockchain and Inter-Planetary File System (IPFS). The system provides solutions for the major security concerns associated with medical files, including authentication and authorization, database breaches, data integrity of local and cloud storage, and data availability. The obtained results indicate a high level of safety by adding security layers such as confidentiality, authentication, authorization and access control, based on different factors. All these aspects contribute to reaching the aim of the proposed system, which is storing and retrieving medical records in a decentralized and safe manner

Enhancement of speech scrambles using DNA technique and chaotic maps over transformation domain

This work presents and describes a new method for speech scrambles in light of chaotic maps and DNA coding. Both a wavelet transform (DWT) and Discrete cosine transform (DCT) are used to change the speech signal into another format for processing. The chaotic maps are represented by Logistic-Chebyshev map (LCH) and Random Logistic map (RLM) which are employed for generating sequences of keys that are used in the proposed system, hence the use of DNA encoding technology as an emerging technology for enhancing the security of speech. The proposed system is illustrated explicitly and tested with various security speech signals metrics, such as the coefficient, signal to noise ratio and peak signal to noise ratio. All tests of the proposed system concluded that the speech signal is reliably secure and undetectable, and hence the proposed system provides a sufficient security level

Secure SDN Traffic based on Machine Learning Classifier

Nowadays, the majority of human activities are carried out utilizing a variety of services or applications that rely on the local and Internet connectivity services provided by private or public networks. With the developments in Machine Learning and Software Defined Networking, traffic classification has become an essential study subject.  As a consequence of the segregation of control and data planes, Software Defined Networks have some security flaws. To cope with malicious code in SDN, certain operational security techniques have been devised. In this paper, a machine learning model, supervised, was utilized to identify normal and malicious traffic flows. While, normal traffic were generated using Internet traffic generator, malicious traffic were accomplish by Scapy and Python. The main network features of the OpenFlow flow table such as Packets count, bytes counts, packet rates, byte rate for forward and revers flows, were extracted. The combination of good ML classifier and dataset produced the greatest accuracy rate over 99% in DDoS attack detection, according to the results. Further to the main aim, the presented approach could be utilized to classify different traffic flows with the purpose of balance and priorities the important traffic

Image security system using hybrid cryptosystem

This work presents and describes a novel method to hide messages in images in a hybrid manner, as steganography is combined with quantum cryptography. Through stimulating and implementing this hybrid approach, the least significant bit (LSB) substitution is employed for hiding secret messages within cover images that consist of three bands (Red, Green and Blue), after which the output is encrypted using quantum one-time pad encryption. The models are illustrated explicitly and tested. In addition, the test analysis uses a steganalysis tool called StegExpose to detect LSB steganography in images. The experimental results proved that the image hiding is reliably secure and undetectable, and hence the proposed new hybrid model provides a sufficient security level as well as we have tested the proposed system using robust state-of- the-art steganalysis techniques and found the low payload threshold maintained in the proposed system produces a high margin of communication security safety. No payload files were detected (0% detections), despite each file containing the entire content of the information as embedded text

Predicting Online Learning Success Based on Learners’ Perceptions: The Integration of the Information System Success Model and the Security Triangle Framework

Although online learning has become ubiquitous worldwide, earlier research has neglected the relationship between its actual use and security concerns. Learners’ lack of security awareness while using learning technologies remains rarely studied. This paper integrates Delone and McLean’s information system success (D&M-ISS) model with the security triangle framework. Data from 2,451 higher education students at different universities and a wide variety of disciplines in Iraq were collected. In addition to the effectiveness of the D&M-ISS factors, the research findings based on the structural equation model suggest that the three constructs of the security triangle framework—namely, confidentiality, integrity, and availability—were significant predictors of students’ use of online learning. This research can thus help academic organizations understand factors that can lead to the successful implementation of online learning and learners’ security awareness