Enhanced image encryption scheme with new mapreduce approach for big size images

Achieving a secured image encryption (IES) scheme for sensitive and confidential data communications, especially in a Hadoop environment is challenging. An accurate and secure cryptosystem for colour images requires the generation of intricate secret keys that protect the images from diverse attacks. To attain such a goal, this work proposed an improved shuffled confusion-diffusion based colour IES using a hyper-chaotic plain image. First, five different sequences of random numbers were generated. Then, two of the sequences were used to shuffle the image pixels and bits, while the remaining three were used to XOR the values of the image pixels. Performance of the developed IES was evaluated in terms of various measures such as key space size, correlation coefficient, entropy, mean squared error (MSE), peak signal to noise ratio (PSNR) and differential analysis. Values of correlation coefficient (0.000732), entropy (7.9997), PSNR (7.61), and MSE (11258) were determined to be better (against various attacks) compared to current existing techniques. The IES developed in this study was found to have outperformed other comparable cryptosystems. It is thus asserted that the developed IES can be advantageous for encrypting big data sets on parallel machines. Additionally, the developed IES was also implemented on a Hadoop environment using MapReduce to evaluate its performance against known attacks. In this process, the given image was first divided and characterized in a key-value format. Next, the Map function was invoked for every key-value pair by implementing a mapper. The Map function was used to process data splits, represented in the form of key-value pairs in parallel modes without any communication between other map processes. The Map function processed a series of key/value pairs and subsequently generated zero or more key/value pairs. Furthermore, the Map function also divided the input image into partitions before generating the secret key and XOR matrix. The secret key and XOR matrix were exploited to encrypt the image. The Reduce function merged the resultant images from the Map tasks in producing the final image. Furthermore, the value of PSNR did not exceed 7.61 when the developed IES was evaluated against known attacks for both the standard dataset and big data size images. As can be seen, the correlation coefficient value of the developed IES did not exceed 0.000732. As the handling of big data size images is different from that of standard data size images, findings of this study suggest that the developed IES could be most beneficial for big data and big size images

Towards Green Computing Oriented Security: A Lightweight Postquantum Signature for IoE

[EN] Postquantum cryptography for elevating security against attacks by quantum computers in the Internet of Everything (IoE) is still in its infancy. Most postquantum based cryptosystems have longer keys and signature sizes and require more computations that span several orders of magnitude in energy consumption and computation time, hence the sizes of the keys and signature are considered as another aspect of security by green design. To address these issues, the security solutions should migrate to the advanced and potent methods for protection against quantum attacks and offer energy efficient and faster cryptocomputations. In this context, a novel security framework Lightweight Postquantum ID-based Signature (LPQS) for secure communication in the IoE environment is presented. The proposed LPQS framework incorporates a supersingular isogeny curve to present a digital signature with small key sizes which is quantum-resistant. To reduce the size of the keys, compressed curves are used and the validation of the signature depends on the commutative property of the curves. The unforgeability of LPQS under an adaptively chosen message attack is proved. Security analysis and the experimental validation of LPQS are performed under a realistic software simulation environment to assess its lightweight performance considering embedded nodes. It is evident that the size of keys and the signature of LPQS is smaller than that of existing signature-based postquantum security techniques for IoE. It is robust in the postquantum environment and efficient in terms of energy and computations.This project was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University. Jeddah. under grant No. (DF-457-156-1441).Rani, R.; Kumar, S.; Kaiwartya, O.; Khasawneh, AM.; Lloret, J.; Al-Khasawneh, MA.; Mahmoud, M.... (2021). Towards Green Computing Oriented Security: A Lightweight Postquantum Signature for IoE. Sensors. 21(5):1-20. https://doi.org/10.3390/s2105188312021

Green Communication for Underwater Wireless Sensor Networks: Triangle Metric Based Multi-Layered Routing Protocol

[EN] In this paper, we propose a non-localization routing protocol for underwater wireless sensor networks (UWSNs), namely, the triangle metric based multi-layered routing protocol (TM2RP). The main idea of the proposed TM2RP is to utilize supernodes along with depth information and residual energy to balance the energy consumption between sensors. Moreover, TM2RP is the first multi-layered and multi-metric pressure routing protocol that considers link quality with residual energy to improve the selection of next forwarding nodes with more reliable and energy-efficient links. The aqua-sim package based on the ns-2 simulator was used to evaluate the performance of the proposed TM2RP. The obtained results were compared to other similar methods such as depth based routing (DBR) and multi-layered routing protocol (MRP). Simulation results showed that the proposed protocol (TM2RP) obtained better outcomes in terms of energy consumption, network lifetime, packet delivery ratio, and end-to-end delay.This project was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah (under grant no. DF-524-156-1441). The authors, therefore, gratefully acknowledge DSR for the technical and financial supportKhasawneh, AM.; Kaiwartya, O.; Lloret, J.; Abuaddous, HY.; Abualigah, L.; Shinwan, MA.; Al-Khasawneh, MA.... (2020). Green Communication for Underwater Wireless Sensor Networks: Triangle Metric Based Multi-Layered Routing Protocol. Sensors. 20(24):1-23. https://doi.org/10.3390/s20247278123202

Cotton crop cultivation oriented semantic framework based on IoT smart farming application

The fact that each technological concept comes from the advances in the research and development, Internet of Things (IoT) grows and touches virtually every area of human activities. This has yielded the possibility of analyzing various types of sensors-environment from any kind of IoT platform. The existing IoT platforms focuses more on the area related to urban infrastructure, smart cities, healthcare, smart industry, smart mobility and much more. In this paper, we are focusing on the architecture of designing the application of IoT based solution in agriculture with more specific to Cotton farming. Our specific approach on farming is relevant to cotton crops cultivation, irrigation and harvesting of yields. In the context of cotton crops cultivation, there are many factors that should be concerned which includes weather, legal regulation, market conditions and resource availability. As a result, this paper presents a cotton crops cultivation oriented semantic framework based on IoT smart farming application which supports smart reasoning over multiple heterogenous data streams associated with the sensors providing a comprehensive semantic pipeline. This framework will support large scale data analytic solution, rapid event recognition, seamless interoperability, operations, sensors and other relevant features covering online web based semantic ontological solution in an agriculture context

Rift: a high-performance consensus algorithm for Consortium Blockchain

The emergence of Blockchain have revolutionize the decentralization in distributed architecture. The advances in the consensus mechanism techniques and the development of different variants of consensus algorithms gives a huge impact on its progress. These technologies allow to have a distributed peer-to-peer network in which each external entity can be able to interact with other entities without any trusted intermediary in a verifiable manner. The existing consensus algorithms are mostly concerned with public blockchain having focused on public ledgers in general. The consortium blockchain is least focused as compared with other variants of blockchain (public and private) showing the need to address this vacuum. In this paper, we proposed a consensus algorithm named Rift for consortium blockchain which works on the principle of trust mechanism for achieving consensus in a blockchain. The consensus is achieved by distributed nodes in a consortium blockchain which were controlled by consortium members to decentralize the arbitration by voting and trust metrics. In this paper, we elaborate the comprehensive idea of Rift and discuss the working model for this algorithm. We also perform simulation on the proposed algorithm and determine the performance variables to evaluate the effectiveness of Rift. The evaluated results show the improvement in the performance which is the objective requirement for the evaluation

MapReduce a comprehensive review

MapReduce encompasses a framework in the processing and management of large scale datasets within a distributed cluster. The framework has been employed in several applications including search indexes generation, analysis of access log, document clustering, and other data analytics. A flexible computation model is adopted in MapReduce in addition to plain interface which comprises the functions of map and reduce. The interface is customizable based on application developers. MapReduce has captured the interest among many scholars whereby the interest has been on increasing its usability and efficiency in support to database-centric operations. Accordingly, this paper provides a complete review regarding a vast continuum of proposals and systems concentrating basically on the support of distributed data management and processing with the use of the framework of MapReduce

An improved chaotic image encryption algorithm

Chaotic-based image encryption algorithms are countless in number. Encryption techniques based on Chaos are among the most effectual algorithms for encryption of data image. In past works, chaos-based cryptosystems applied the chaotic dynamical system with the linkage to the harmonization of two chaotic systems and controls. Good performances have resulted but there were several downsides pertaining to the single rule usage by each, impacting security, privacy and dependability of the techniques mentioned. Serious problems were also documented in their usage in satellite imagery. As a possible solution, a novel chaos-based symmetric method of key cryptosystem is proposed in this paper. This method employs external secret key that Logistic, Henon and Gauss iterated maps have previously expanded. For creating the secret key matrix for image encryption, these maps are merged. Here, simple logical XOR and multiple key generation processes were applied. Assessment to the method is performed on the satellite images dataset, and security is evaluated through the experimental analysis. As evidenced, the chaos-based satellite image cryptosystem demonstrates appropriateness for satellite image encryption and decryption in the preservation of security and dependability of the storage and transmission process

Common investigation process model for internet of things forensics

Internet of Things Forensics (IoTFs) is a new discipline in digital forensics science used in the detection, acquisition, preservation, rebuilding, analyzing, and the presentation of evidence from IoT environments. IoTFs discipline still suffers from several issues and challenges that have in the recent past been documented. For example, heterogeneity of IoT infrastructures has mainly been a key challenge. The heterogeneity of the IoT infrastructures makes the IoTFs very complex, and ambiguous among various forensic domain. This paper aims to propose a common investigation processes for IoTFs using the metamodeling method called Common Investigation Process Model (CIPM) for IoTFs. The proposed CIPM consists of four common investigation processes: i) preparation process, ii) collection process, iii) analysis process and iv) final report process. The proposed CIPM can assist IoTFs users to facilitate, manage, and organize the investigation tasks

CIPM: Common identification process model for database forensics field

Database Forensics (DBF) domain is a branch of digital forensics, concerned with the identification, collection, reconstruction, analysis, and documentation of database crimes. Different researchers have introduced several identification models to handle database crimes. Majority of proposed models are not specific and are redundant, which makes these models a problem because of the multidimensional nature and high diversity of database systems. Accordingly, using the metamodeling approach, the current study is aimed at proposing a unified identification model applicable to the database forensic field. The model integrates and harmonizes all exiting identification processes into a single abstract model, called Common Identification Process Model (CIPM). The model comprises six phases: 1) notifying an incident, 2) responding to the incident, 3) identification of the incident source, 4) verification of the incident, 5) isolation of the database server and 6) provision of an investigation environment. CIMP was found capable of helping the practitioners and newcomers to the forensics domain to control database crimes

Comparative analysis of network forensic tools and network forensics processes

Network Forensics (NFs) is a branch of digital forensics which used to detect and capture potential digital crimes over computer networked environments crime. Network Forensic Tools (NFTs) and Network Forensic Processes (NFPs) have abilities to examine networks, collect all normal and abnormal traffic/data, help in network incident analysis, and assist in creating an appropriate incident detection and reaction and also create a forensic hypothesis that can be used in a court of law. Also, it assists in examining the internal incidents and exploitation of assets, attack goals, executes threat evaluation, also by evaluating network performance. According to existing literature, there exist quite a number of NFTs and NTPs that are used for identification, collection, reconstruction, and analysing the chain of incidents that happen on networks. However, they were vary and differ in their roles and functionalities. The main objective of this paper, therefore, is to assess and see the distinction that exist between Network Forensic Tools (NFTs) and Network Forensic Processes (NFPs). Precisely, this paper focuses on comparing among four famous NFTs: Xplico, OmniPeek, NetDetector, and NetIetercept. The outputs of this paper show that the Xplico tool has abilities to identify, collect, reconstruct, and analyse the chain of incidents that happen on networks than other NF tools