A novel blockchain architecture based on network functions virtualization (NFV) with auto smart contracts

Network Function Virtualization (NFV) is considered to be a hopeful technology for supporting blockchain with many features like flexible networks and intelligent equipment. NFV decreases the expenses incurred on the maintenance and operation of assets that are generated through expenses, in addition to capital expenditures based on the isolate the physical devices from the main tasks executed by that equipment. Blockchain currency transfers or technology is the most powerful security tool that ensures the security of data. The prominent challenges in NFV are the processes of transition, vendor compatibility, network management, rapid growth, and security. The software industry and skills of networking are experiencing fast expansion and deployment of the Network Functions Virtualization (NFV) approach, jointly in blockchain and cloud networks. In this paper, a novel method is offered to virtualize the work of the blockchain based on the NFV with auto work of the smart contract between virtual nodes based on cloud computing. By blending NFV with Blockchain, all of the above-mentioned challenges have been overcome by moving to software environments through creating virtual nodes, as well as smooth interaction among them and managing the transactions between nodes and clients, indicating ideal network management. Through the proposed work, a throughput of up to 20% is obtained by applying NFV compared to not applying NFV to the blockchain. In addition, the costs of the hardware are eliminated and eventually a secure environment is used which distances the system from virtual attacks

A Realizable Quantum Three-Pass Protocol Authentication Based on Hill-Cipher Algorithm

A realizable quantum three-pass protocol authentication based on Hill-cipher algorithm is presented by encoded and decoded plaintext using classical Hill-cipher algorithm. It is shown that the encoded message transferred to the particles called quantum state where we assumed that a photon is used as a qubit and after the encoded message is transferred into photons, the polarization of each photon is rotated by an angle θj, which is chosen randomly for each qubit. The sender and receiver agree over a Hill-cipher key, the encryption occurs by utilization of the quantum three-pass protocol (QTPP), the decryption will be illustrated, and an example shows how the algorithm will work. Finally, the security of this algorithm is analyzed in detail

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

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

Enhanced Security of Software-defined Network and Network Slice Through Hybrid Quantum Key Distribution Protocol

Software-defined networking (SDN) has revolutionized the world of technology as networks have become more flexible, dynamic and programmable. The ability to conduct network slicing in 5G networks is one of the most crucial features of SDN implementation. Although network programming provides new security solutions of traditional networks, SDN and network slicing also have security issues, an important one being the weaknesses related to openflow channel between the data plane and controller as the network can be attacked via the openflow channel and exploit communications with the control plane. Our work proposes a solution to provide adequate security for openflow messages through using a hybrid key consisting of classical and quantum key distribution protocols to provide double security depending on the computational complexity and physical properties of quantum. To achieve this goal, the hybrid key used with transport layer security protocol to provide confidentiality, integrity and quantum authentication to secure openflow channel. We experimentally based on the SDN-testbed and network slicing to show the workflow of exchanging quantum and classical keys between the control plane and data plane and our results showed the effectiveness of the hybrid key to enhance the security of the transport layer security protocol. Thereby achieving adequate security for openflow channel against classical and quantum computer attacks

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

Effect of Laser Mode and Power on the Tribological Behavior of Additively Manufactured Inconel 718 Alloy

The influence of laser modes and power on the tribological behavior of additively manufactured Inconel 718 alloy using the directed energy deposition (DED) process was investigated. The samples were fabricated with continuous wave (CW) and pulse wave (PW) laser modes using 700, 900, and 1100 W laser power. The samples exhibited high hardness (3–5 GPa) and modulus (150–200 GPa) which increases with the laser power for CW- and PW-fabricated samples, and this was associated with the increasing densification and hardening secondary phase. The coefficient of friction increases with laser power for the CW samples but decreases for the PW samples. The samples exhibited low wear rates ranging between 25 and 70 × 10−5 mm3/Nm. Pulse wave samples demonstrated better tribological performance compared to continuous wave at any laser power. The dominant wear mechanism is the three-body abrasive wear followed by localized and discrete adhesion wear mechanism.</p