A Discrete Event Simulation of Network Centric Operations: Modeling Unbalanced Combat Configurations in Symmetric Engagements

Network Centric Operations (NCO) has been dubbed the most significant revolution in military affairs (RMA) in the past 200 years. The promise of NCO is based on the notion that information sharing and connectivity is fundamental to the effectiveness of a combat force. This due to the ability of a properly networked force to self-synchronize itself as it engages enemy forces. The purposeful arrangement of assets in a combat force is what makes it \u27properly networked\u27. What is a purposeful arrangement of combat assets? How should a force organize to enhance information sharing and connectivity? And how does connectivity within a networked force impact its combat effectiveness? This research builds a discrete-event simulation of the information age combat model, which is a representation of NCO, in an attempt to understand the impact of information sharing and connectivity among the elements of a military force on its combat effectiveness. Unbalanced combat configurations doing symmetric engagements were selected as the prime focus. They were studied and simulated to gain insights into the dynamics of networked operations. The proposed discrete event combat model displayed significant increases in efficiency and speed of running compared to previous modeling work that utilized agent-directed simulations. Linear and nonlinear regression analyses were conducted to highlight the performance metrics that wield significant predictive power over the probability of winning a combat engagement

Empirical Test of Fama and French Three-Factor Model in Amman Stock Exchange

This study aims to empirically test the ability of Fama and French (1993) Three-Factor Model (FF3F) in predicting monthly excess rates of returns of stocks traded in Amman Stock Exchange (ASE) during the period (2001 - 2010). The study uses similar methodology of FF3F. Stocks in the sample have sorted according to the size (market value) and value (book-tomarket ratio, B/M) in order to form portfolios and measuring the dependent and independent variables. To estimate the FF3F parameters, a time series regression ran using the ordinary least square method. The study documents positive value effect in ASE. Portfolios with high B/M outperformed those of low B/M. Also, the study finds small size effect, but not in a like-manner as in the U.S or other developed markets. The study finds that multi factor asset pricing model works better than the single factor model, i.e. the CAPM. Therefore, it is recommended that participants in ASE should exploit size and value effect in investment strategy and replace the CAPM by FF3F in various asset pricing applications

A Hierarchical Structure towards Securing Data Transmission in Cognitive Radio Networks

Cognitive Radio (CR) technology is considered as a promising technology to overcome spectrum scarcity problem in wireless networks, by sharing the spectrum between both unlicensed users (secondary users, (SUs)) and licensed users (primary users, (PUs)), provided that the SUs respect the PUs’ rights to use the spectrum exclusively. An important technical area in cognitive radio networks (CRNs) is wireless security. A secure CRN must meet different security requirements, which are: confidentiality, integrity, availability and authentication. Data confidentiality is a mandatory requirement in cognitive radio networks, generally to maintain the privacy of the data owner (PU or SU). Integrity means that data is transmitted from the source to the destination without alteration. While availability is to release the channels assigned to one SU as soon as a PU wants to use its spectrum. Authentication in CRN means that each node has to authenticate itself before it can use the available spectrum channels. New classes of security threats and challenges in CRNs have been introduced that target the different layers of OSI model and affect the security requirements. Providing strong security may prove to be the most difficult aspect of making CR a long-term commercially-viable concept. Protection of routes used for data transmission is a critical prerequisite to ensure the robustness of iv the routing process. Therefore, route discovery must be done in such a way that lets each node find the best secure path(s) for its data transmission. In this work, network security of CRN is improved through proposing different models that are built to fulfil the security requirements mentioned above. Improving the network security enhances the network performance, taking into consideration the quality of service (QoS) desired by the different network nodes such as bandwidth and time delay. This work aims to combine the spectrum sensing phase and the spectrum management phase, as well as to detect all the adversary nodes that slow down the network performance by selectively holding and not forwarding packets to their next hop(s). We measure the network node’s reliability for using network resources through a value called belief level (BL), which is considered as the main parameter for our entire work. BL is used to monitor the nodes’ behavior during the spectrum sensing phase, and then it is used to form the best path(s) during the spectrum management phase. Particularly, this work follows a hierarchical structure that has three different layers. At the bottom layer, a novel authentication mechanism is developed to fulfil the authentication and the availability security requirements, which ends assigning a belief level (BL) to each node. At the middle layer, the nodes’ behavior during the spectrum sensing phase is monitored to detect all the adversary node(s). Finally, at the top layer, a novel routing algorithm is proposed that uses the nodes’ security (BL) as a routing metric. SUs collaborate with each other to monitor other nodes’ behavior. Users’ data confidentiality and integrity are satisfied through this hierarchical structure that uses the cluster-based, central authority, and nodes collaboration concepts. By doing so, the traffic carried in the CRN is secured and adversary nodes are detected and penalized

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

A Secure and Efficient Authentication Mechanism Applied to Cognitive Radio Networks

Cognitive radio (CR) has been introduced to accommodate the steady increment in the spectrum demand. Wireless security in cognitive radio network (CRN) is a challenging technical area due to the dynamic and unique characteristics of CRNs. As a cognitive node can dynamically join or leave the spectrum, providing secure communication becomes problematic and requires more investigation. Authentication is a primary security property in wireless networks wherein the identity of a cognitive node is verified before providing access to available resources. In this paper, a two-level authentication scheme for communication in CRN is proposed. Before joining the network, a CR node is validated by obtaining security credentials from an authorized point. The proposed scheme relies on public- and symmetric-key cryptography, instead of using a digital signaturebased approach. It encrypts data between the communicating nodes in order to improve network security in terms of resource availability and accessibility.This mitigates attacks such as Reflection attack, Denial of Service attack and Man-in-the-Middle attack. The scheme has been evaluated and verified in terms of security functionality, its correctness and the performance, which shows less computation and communication requirements

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

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

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