http://home.engineering.iastate.edu/~morris/papers/14/crn_survey_deanna.pdf

A layered approach to cognitive radio network security

Stock market data is a time-series data in which stock value varies depends on time. Prediction of the stock market is an endeavor to assess the future value of a company’s stock rate which will increase the investor’s profit. The accurate prediction of stock market analysis is still a challenging task. The proposed system predicts stock price of any company mentioned by the user for the next few days. Using the predicted stock price and datasets collected from various sources regarding a certain equity, the overall sentiment of the stock is predicted. The prediction of stock price is done by regression and candlestick pattern detection. The proposed system generates signals on the candlestick graph which allows to predict market movement to a sufficient level of accuracy so that the user is able to judge whether a stock is a ‘Buy/Sell’ and whether to short the stock or go long by delivery. The prediction accuracy of the stock exchange has analyzed and improved to 85% using machine learning algorithms.

Stock market analysis using candlestick regression and market trend prediction (CKRM)

Anomaly detection and trust authority in artificial intelligence and cloud computing

With the information and communication technologies (ICT) and Internet of Things (IoT) gradually advancing, smart homes have been able to provide home services to users. The user can enjoy a high level of comfort and improve his quality of life by using home services provided by smart devices. However, the smart home has security and privacy problems, since the user and smart devices communicate through an insecure channel. Therefore, a secure authentication protocol should be established between the user and smart devices. In 2020, Xiang and Zheng presented a situation-aware protocol for device authentication in smart grid-enabled smart home environments. However, we demonstrate that their protocol can suffer from stolen smart device, impersonation, and session key disclosure attacks and fails to provide secure mutual authentication. Therefore, we propose a secure and lightweight authentication protocol for IoT-based smart homes to resolve the security flaws of Xiang and Zheng’s protocol. We proved the security of the proposed protocol by performing informal and formal security analyses, using the real or random (ROR) model, Burrows–Abadi–Needham (BAN) logic, and the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. Moreover, we provide a comparison of performance and security properties between the proposed protocol and related existing protocols. We demonstrate that the proposed protocol ensures better security and lower computational costs than related protocols, and is suitable for practical IoT-based smart home environments.

A Secure and Lightweight Authentication Protocol for IoT-Based Smart Homes

Cognitive radio networks (CRNs) are an emerging paradigm for next generation wireless communication systems allowing for more efficient radio spectrum utilization. In order to harness the full potential that CRNs may offer, many challenges and problems need to be overcome and addressed. One of the critical questions is the performance of secondary networks under primary user activity constraints. In this respect, queueing assumes a primary role in characterizing the delay, throughput and other performance metrics for secondary users, which in turn has implications for resource allocation, medium access control and quality of service provisioning. This survey presents an overview and classification of the various queueing models and techniques which have been proposed in the literature in the context of CRNs. Furthermore, open problems, future research directions and further potential applications related to queueing for CRNs are identified.

Queueing Models for Cognitive Radio Networks: A Survey

In cognitive radio networks, secondary users (SUs) opportunistically utilize the spectrum without harmful interruption to the primary users (PUs). In this article, the overlay medium access control (MAC) scheme is considered in which SU uses the spectrum portion which is not utilized by PU. The imperfect sensing is considered at SU network (SUN) to detect PU's transmission. In the SUN, carrier sense multiple access protocol with contention window (CW) is used to minimize the collisions between SUs and PUs. Multichannel decentralized MAC protocol is investigated to analyse the throughput and examine the impact of various arrival rates of PUs (opportunities) and SUs, number of SUs, number of channels, and CWs. Numerical results verify various events and demonstrate the performance of the proposed MAC protocol under imperfect sensing conditions.

Multichannel CSMA Based MAC Scheme for Unsaturated Cognitive Radio Networks: Performance Study of the Opportunity and Contention Window

Coordinated approach for area exploration and navigation has been challenging to the researchers' community for last few decades. While exploring or navigation a team of robots area division for each robot, algorithm implemented and coordination among them have been challenging. Here, coordinated approach to navigate given environment to find best path to reach the goal, sectorization of the environment and further dividing in into co-centric circles have been proposed for navigation in which all robots select local goals satisfying minimum cost approach to reach their local goal. Further, shared memory approach at mother robot has been implemented to establish effective communication among the robots. The cost in terms of time of navigation to reach known target in an unknown environment has been taken into account to determine best possible path to the given target.

Coordinated multi-robot navigation using sectorization of environment

In wireless sensor network (WSN) nodes relay data, which maintains consistency in the sensor network. If cut vertex nodes failed it leads to partitioning in network, which disrupts the communication. It requires an autonomous technique that finds the fail node and provides recovery to them. In this paper the proposed approach provides recovery from network partitioning in distribute WSN. The proposed approach increases the lifetime of network.

Distributed Recovery in Moveable Wireless Sensor Networks

A comprehensive survey of fake news in social networks: Attributes, features, and detection approaches

It hasbeen anticipated that the fifth generation (5G) wireless systems will deliver an efficient growth of the energy and spectral efficiency. To accomplish these goals, centralized radio access networks (C-RAN) is presented as the advanced wireless access networks paradigm with centralized baseband units (BBUs) and remote radio heads (RRHs). Although it is affected by Common Public Radio Interface (CPRI) limitations which requires high bandwidth for existing BBU/RRH interfaces. Moreover, the fronthaul links the BBU and RRH. But CPRI limits the deployment of C-RAN for fronthaul networking due to its fixed-rate fronthaul interface which transmit CPRI streams even in the absence of traffic load. However, this causes data transmission inefficient. So, the classical fronthauling method demands high bandwidth and the failure of fronthaul will cause losing a very high bandwidth. The purpose of this paper is to develop energy detection (ED) based algorithm which permits the secondary users to use the channel without interfering the primary users, so that the bandwidth in the fronthaul can be used in an efficient manner. A dynamic threshold with noise uncertainty based ED algorithm is proposed in this paper. It compares the fixed threshold with dynamic threshold by comparing probability of detection with probability of false alarm. Finally, by using this proposed algorithm, it can be concluded that performance of the probability of detection improves even with the presence of noise uncertainty.

Lokesh Chouhan

Papers

Multichannel CSMA Based MAC Scheme for Unsaturated Cognitive Radio Networks: Performance Study of the Opportunity and Contention Window

Coordinated multi-robot navigation using sectorization of environment

Distributed Recovery in Moveable Wireless Sensor Networks

A comprehensive survey of fake news in social networks: Attributes, features, and detection approaches

Adaptive Energy Detection Based Solution for Fronthaul Problem in C-RAN