LGTBIDS: Layer-wise Graph Theory Based Intrusion Detection System in Beyond 5G

The advancement in wireless communication technologies is becoming more demanding and pervasive. One of the fundamental parameters that limit the efficiency of the network are the security challenges. The communication network is vulnerable to security attacks such as spoofing attacks and signal strength attacks. Intrusion detection signifies a central approach to ensuring the security of the communication network. In this paper, an Intrusion Detection System based on the framework of graph theory is proposed. A Layerwise Graph Theory-Based Intrusion Detection System (LGTBIDS) algorithm is designed to detect the attacked node. The algorithm performs the layer-wise analysis to extract the vulnerable nodes and ultimately the attacked node(s). For each layer, every node is scanned for the possibility of susceptible node(s). The strategy of the IDS is based on the analysis of energy efficiency and secrecy rate. The nodes with the energy efficiency and secrecy rate beyond the range of upper and lower thresholds are detected as the nodes under attack. Further, detected node(s) are transmitted with a random sequence of bits followed by the process of re-authentication. The obtained results validate the better performance, low time computations, and low complexity. Finally, the proposed approach is compared with the conventional solution of intrusion detection.Comment: in IEEE Transactions on Network and Service Management, 202

Half-Duplex Attack: An Effectual Attack Modelling in D2D Communication

The visualization of future generation Wireless Communication Network WCN redirects the presumption of onward innovations, the fulfillment of user demands in the form of high data rates, energy efficiency, low latency, and long-range services. To content these demands, various technologies such as massive MIMO Multiple Input Multiple Output, UDN Ultra Dense Network, spectrum sharing, D2D Device to Device communication were improvised in the next generation WCN. In comparison to previous technologies, these technologies exhibit flat architecture, the involvement of clouds in the network, centralized architecture incorporating small cells which creates vulnerable breaches initiating menaces to the security of the network. The half-duplex attack is another threat to the WCN, where the resource spoofing mechanism is attained in the downlink phase of D2D communication. Instead of triggering an attack on both uplink and downlink, solely downlink is targeted by the attacker. This scheme allows the reduced failed attempt rate of the attacker as compared to the conventional attacks. The analysis is determined on the basis of Poissons distribution to determine the probability of failed attempts of half duplex attack in contrast to a full duplex attac

Security in 5G Networks: A Systematic Analysis of High-Speed Data Connections

Maximum user systems on 5G networks will now not be consumer phones or computers, but IoT device. Via 2021, there might be about 30 billion such devices. The quantity of attacks on the IoT is growing. Device protection is terrible and malware distribution is without problems scalable. Protection has ended up the primary challenge in many telecommunications industries these days as risks may have high outcomes. especially, because the center and enable technologies might be related to the 5G network, the confidential information will pass at all layers in destiny Wi-Fi structures. Even with modern-day 4G networks, now not each operator succeeds in securely configuring the center network and protecting it from all angles. As SDN and NFV are carried out for network cutting in 5G, the administration will become even extra difficult. Flexibility in 5G networks comes at the fee of multiplied complexity and high bandwidth communication settings to monitor. 5G will offer broadband access anywhere, entertain better person mobility, and permit connectivity of a large number of devices in an ultra- reliable and low-priced manner. Furthermore, we present protection solutions to those demanding situations and future instructions for secure 5G systems

GPS Anomaly Detection And Machine Learning Models For Precise Unmanned Aerial Systems

The rapid development and deployment of 5G/6G networks have brought numerous benefits such as faster speeds, enhanced capacity, improved reliability, lower latency, greater network efficiency, and enablement of new applications. Emerging applications of 5G impacting billions of devices and embedded electronics also pose cyber security vulnerabilities. This thesis focuses on the development of Global Positioning Systems (GPS) Based Anomaly Detection and corresponding algorithms for Unmanned Aerial Systems (UAS). Chapter 1 provides an overview of the thesis background and its objectives. Chapter 2 presents an overview of the 5G architectures, their advantages, and potential cyber threat types. Chapter 3 addresses the issue of GPS dropouts by taking the use case of the Dallas-Fort Worth (DFW) airport. By analyzing data from surveillance drones in the (DFW) area, its message frequency, and statistics on time differences between GPS messages were examined. Chapter 4 focuses on modeling and detecting false data injection (FDI) on GPS. Specifically, three scenarios, including Gaussian noise injection, data duplication, data manipulation are modeled. Further, multiple detection schemes that are Clustering-based and reinforcement learning techniques are deployed and detection accuracy were investigated. Chapter 5 shows the results of Chapters 3 and 4. Overall, this research provides a categorization and possible outlier detection to minimize the GPS interference for UAS enhancing the security and reliability of UAS operations

When Two-Layer Federated Learning and Mean-Field Game Meet 5G and Beyond Security: Cooperative Defense Systems for 5G and Beyond Network Slicing

Cyber security for 5G and Beyond (5GB) network slicing is drawing much attention due to the increase of complex and dangerous cyber-attacks that could target the critical components of network slicing, such as radio access and core network. This paper proposes a new cyber defense approach based on two-layer Federated Learning (FL) to protect 5GB network slicing from the most dangerous network attacks and a mean-field game to safeguard the FL-enabled defense system from poisoning attacks. Our proposed distributed defense systems cooperate, intending to detect internal and external attacks targeting the critical components of 5GB network slicing and detecting infected parts in the 5GB defense system. Our experimental results show that our cooperative defense systems exhibit high accuracy detection rates against network attacks, namely (distributed) denial of service and botnets while being robust against poisoning attacks and requiring a few overheads generated by defense systems. To the best of our knowledge, we are the first to propose lightweight and accurate cooperative defense systems based on two-layer FL and non-cooperative games to enhance security against attackers in 5GB network slicing

Secure and reliable wireless advertising system using intellectual characteristic selection algorithm for smart cities

Smart cities wireless advertising (smart mobile-AD) filed is one of the well-known area of research where smart devices using mobile ad hoc networks (MANET) platform for advertisement and marketing purposes. Wireless advertising through multiple fusion internet of things (IoT) sensors is one of the important field where the sensors combines multiple sensors information and accomplish the control of self-governing intelligent machines for smart cities advertising framework. With many advantages, this field has suffered with data security. In order to tackle security threats, intrusion detection system (IDS) is adopted. However, the existing IDS system are not able to fulfill the security requirements. This paper proposes an intellectual characteristic selection algorithm (ICSA) integrated with normalized intelligent genetic algorithm-based min-max feature selection (NIGA-MFS). The proposed solution designs for wireless advertising system for business/advertising data security and other transactions using independent reconfigurable architecture. This approach supports the wireless advertising portals to manage the data delivery by using 4G standard. The proposed reconfigurable architecture is validated by using applications specific to microcontrollers with multiple fusion IoT sensors

A Survey on Data Plane Programming with P4: Fundamentals, Advances, and Applied Research

With traditional networking, users can configure control plane protocols to match the specific network configuration, but without the ability to fundamentally change the underlying algorithms. With SDN, the users may provide their own control plane, that can control network devices through their data plane APIs. Programmable data planes allow users to define their own data plane algorithms for network devices including appropriate data plane APIs which may be leveraged by user-defined SDN control. Thus, programmable data planes and SDN offer great flexibility for network customization, be it for specialized, commercial appliances, e.g., in 5G or data center networks, or for rapid prototyping in industrial and academic research. Programming protocol-independent packet processors (P4) has emerged as the currently most widespread abstraction, programming language, and concept for data plane programming. It is developed and standardized by an open community and it is supported by various software and hardware platforms. In this paper, we survey the literature from 2015 to 2020 on data plane programming with P4. Our survey covers 497 references of which 367 are scientific publications. We organize our work into two parts. In the first part, we give an overview of data plane programming models, the programming language, architectures, compilers, targets, and data plane APIs. We also consider research efforts to advance P4 technology. In the second part, we analyze a large body of literature considering P4-based applied research. We categorize 241 research papers into different application domains, summarize their contributions, and extract prototypes, target platforms, and source code availability.Comment: Submitted to IEEE Communications Surveys and Tutorials (COMS) on 2021-01-2

Novel modeling and optimization for joint Cybersecurity-vs-QoS Intrusion Detection Mechanisms in 5G networks

The rapid emergence of 5G technology brings new cybersecurity challenges that hold significant implications for our economy, society, and environment. Among these challenges, ensuring the effectiveness of Intrusion Detection Mechanisms (IDMs) in monitoring networks and detecting 5G-related cyberattacks is of utmost importance. However, optimizing cybersecurity levels and selecting appropriate IDMs remain as critical and ongoing challenges. This work considers multiple pre-deployed distributed Security Agents (SAs) across the network, each capable of running various IDMs, where they differ by their effectiveness in detecting the attacks (referred to as security term) and the consumption of resources (referred to as Quality of Service (QoS) costs). We formulate a joint security and QoS utility function leveraging the Cobb–Douglas production utility function. There are several parameters that impact the joint objective problem, including the set of elasticity parameters, that reflect the importance of the two objectives. We derive an optimal set of elasticity parameters in closed form to identify the balancing point where both objectives have equal utility values. Through comprehensive simulations, we demonstrate that increasing the detection level of SAs enhances the security utility while simultaneously diminishing the QoS utility, as more computational, bandwidth, and monetary resources are utilized for IDM processing. After optimization, our mechanism can strike an effective balance between cybersecurity and QoS overhead while demonstrating the importance of different parameters in the joint problem