SDN - Architectural Enabler for Reliable Communication over Millimeter-Wave 5G Networks

Millimeter-wave (mmWave) frequency bands offer a new frontier for next-generation wireless networks, popularly known as 5G, to enable multi-gigabit communication; however, the availability and reliability of mmWave signals are significantly limited due to its unfavorable propagation characteristics. Thus, mmWave networks rely on directional narrow-beam transmissions to overcome severe path-loss. To mitigate the impact of transmission-reception directionality and provide uninterrupted network services, ensuring the availability of mmWave transmission links is important. In this paper, we proposed a new flexible network architecture to provide efficient resource coordination among serving basestations during user mobility. The key idea of this holistic architecture is to exploit the software-defined networking (SDN) technology with mmWave communication to provide a flexible and resilient network architecture. Besides, this paper presents an efficient and seamless uncoordinated network operation to support reliable communication in highly-dynamic environments characterized by high density and mobility of wireless devices. To warrant high-reliability and guard against the potential radio link failure, we introduce a new transmission framework to ensure that there is at least one basestation is connected to the UE at all times. We validate the proposed transmission scheme through simulations.Comment: This article has been accepted for publication at the IEEE GLOBECOM 2018 Workshops, Abu Dhabi, UAE, 9-13 December 201

LiSA: A Lightweight and Secure Authentication Mechanism for Smart Metering Infrastructure

Smart metering infrastructure (SMI) is the core component of the smart grid (SG) which enables two-way communication between consumers and utility companies to control, monitor, and manage the energy consumption data. Despite their salient features, SMIs equipped with information and communication technology are associated with new threats due to their dependency on public communication networks. Therefore, the security of SMI communications raises the need for robust authentication and key agreement primitives that can satisfy the security requirements of the SG. Thus, in order to realize the aforementioned issues, this paper introduces a lightweight and secure authentication protocol, "LiSA", primarily to secure SMIs in SG setups. The protocol employs Elliptic Curve Cryptography at its core to provide various security features such as mutual authentication, anonymity, replay protection, session key security, and resistance against various attacks. Precisely, LiSA exploits the hardness of the Elliptic Curve Qu Vanstone (EVQV) certificate mechanism along with Elliptic Curve Diffie Hellman Problem (ECDHP) and Elliptic Curve Discrete Logarithm Problem (ECDLP). Additionally, LiSA is designed to provide the highest level of security relative to the existing schemes with least computational and communicational overheads. For instance, LiSA incurred barely 11.826 ms and 0.992 ms for executing different passes across the smart meter and the service providers. Further, it required a total of 544 bits for message transmission during each session.Comment: To appear in IEEE Globecom 201

Environmental monitoring smart system with selfsustaining wireless sensor network using data validation algorithms

Study in Wireless Sensor Network (WSN) has been becoming an emerging and promising research topic aiming for the advancement in the Internet of Things (IoT) for a reliable connection. The capability of the wireless sensor to be used in a complex environment can become hard to reach areas and also be able to communicate in an ad-hoc manner, attracted researchers in recent times. Development in wireless sensor network producing a lot of new applications to sense environment remotely are facing challenges restricting it to perform up to its potential. Data validation and data reliability are such existing problems in this domain that needed to be addressed. Because sensed data cannot be blindly trusted upon, as it may have faults and errors occurred with-in the sensing environment. Besides, to guarantee the active state of the sensing system in a remote area is also essential in terms of power usage and management. The focus of the paper is data validation acquired from sensors deployed in remote areas. Although, lots of data validation algorithms have been proposed by researchers to identify single data fault. However, our research identifies multiple faults, namely spike fault, out of range fault, outliers, and stuck at fault using a hybrid form of an algorithm. A comparison with the existing algorithm shows that the proposed algorithm improved data validation by 97 % in detecting multiple data faults using Artificial Intelligence techniques

Detailed Review on The Denial of Service (DoS) and Distributed Denial of Service (DDoS) Attacks in Software Defined Networks (SDNs) and Defense Strategies

The development of Software Defined Networking (SDN) has altered the landscape of computer networking in recent years. Its scalable architecture has become a blueprint for the design of several advanced future networks. To achieve improve and efficient monitoring, control and management capabilities of the network, software defined networks differentiate or decouple the control logic from the data forwarding plane. As a result, logical control is centralized solely in the controller. Due to the centralized nature, SDNs are exposed to several vulnerabilities such as Spoofing, Flooding, and primarily Denial of Service (DoS) and Distributed Denial of Service (DDoS) among other attacks. In effect, the performance of SDN degrades based on these attacks. This paper presents a comprehensive review of several DoS and DDoS defense/mitigation strategies and classifies them into distinct classes with regards to the methodologies employed. Furthermore, suggestions were made to enhance current mitigation strategies accordingly

A metaheuristic optimization approach for energy efficiency in the IoT networks

© 2020 John Wiley & Sons, Ltd. Recently Internet of Things (IoT) is being used in several fields like smart city, agriculture, weather forecasting, smart grids, waste management, etc. Even though IoT has huge potential in several applications, there are some areas for improvement. In the current work, we have concentrated on minimizing the energy consumption of sensors in the IoT network that will lead to an increase in the network lifetime. In this work, to optimize the energy consumption, most appropriate Cluster Head (CH) is chosen in the IoT network. The proposed work makes use of a hybrid metaheuristic algorithm, namely, Whale Optimization Algorithm (WOA) with Simulated Annealing (SA). To select the optimal CH in the clusters of IoT network, several performance metrics such as the number of alive nodes, load, temperature, residual energy, cost function have been used. The proposed approach is then compared with several state-of-the-art optimization algorithms like Artificial Bee Colony algorithm, Genetic Algorithm, Adaptive Gravitational Search algorithm, WOA. The results prove the superiority of the proposed hybrid approach over existing approaches

GTM approach towards engineering a features-oriented evaluation framework for secure authentication in IIoT environment

Industry Internet of Things (IIoT) has become the most evolving area over the last few years. The number of IoT devices connected in industry has sharply elevated but this surge has led to the vulnerability and data breach such as if a malicious entry is made to the secure network, it will forfeit all the network resources. For this purpose a full pledged secure authentication method is essential to safeguard IIoT network. There is a bulky list of number of authentications protocols available to keep network safe with a variety of features so but it becomes herculean task for network administrator to pick the strong and secure authentication method due to huge number of criteria, conflicting objectives and availability of authentication protocols in industry environment. It has become imperative to get the most rational authentication method in devices operating in IIoT. To address this issue, a feature-oriented assessment framework is put forward to provide a ground for ranking and selection of best authentication mechanism. This framework uses a mathematic approach known as Graph Theory Matrix Approach (GTMA) and selects the best authentication method based on the number of features. These features are related to authentication and covers almost every aspect of authentication method and are used as benchmark for selection purposes. This framework takes into account the most important features and helps in selecting the best and most ideal features-oriented authentication method that can be employed in IIoT to keep the integrity and security of connected devices and overall network infrastructure.Qatar National Library and Qatar University - grant No. QUHI-CBE-21/22-1

Proactive content caching in future generation communication networks: Energy and security considerations

The proliferation of hand-held devices and Internet of Things (IoT) applications has heightened demand for popular content download. A high volume of content streaming/downloading services during peak hours can cause network congestion. Proactive content caching has emerged as a prospective solution to tackle this congestion problem. In proactive content caching, data storage units are used to store popular content in helper nodes at the network edge. This contributes to a reduction of peak traffic load and network congestion. However, data storage units require additional energy, which offers a challenge to researchers that intend to reduce energy consumption up to 90% in next generation networks. This thesis presents proactive content caching techniques to reduce grid energy consumption by utilizing renewable energy sources to power-up data storage units in helper nodes. The integration of renewable energy sources with proactive caching is a significant challenge due to the intermittent nature of renewable energy sources and investment costs. In this thesis, this challenge is tackled by introducing strategies to determine the optimal time of the day for content caching and optimal scheduling of caching nodes. The proposed strategies consider not only the availability of renewable energy but also temporal changes in network trac to reduce associated energy costs. While proactive caching can facilitate the reduction of peak trac load and the integration of renewable energy, cached content objects at helper nodes are often more vulnerable to malicious attacks due to less stringent security at edge nodes. Potential content leakage can lead to catastrophic consequences, particularly for cache-equipped Industrial Internet of Things (IIoT) applications. In this thesis, the concept of \trusted caching nodes (TCNs) is introduced. TCNs cache popular content objects and provide security services to connected links. The proposed study optimally allocates TCNs and selects the most suitable content forwarding paths. Furthermore, a caching strategy is designed for mobile edge computing systems to support IoT task offloading. The strategy optimally assigns security resources to offloaded tasks while satisfying their individual requirements. However, security measures often contribute to overheads in terms of both energy consumption and delay. Consequently, in this thesis, caching techniques have been designed to investigate the trade-off between energy consumption and probable security breaches. Overall, this thesis contributes to the current literature by simultaneously investigating energy and security aspects of caching systems whilst introducing solutions to relevant research problems