The increase in the usage of various computing and mobile devices has resulted in implementing large scale ad hoc networks as the user demand is on the rise and companies’ find it difficult to invest more in the IT infrastructure to meet the surging demand. The traditional model of networking enables the mobile devices to face various issues like lower bandwidth, mobility, security and storage et. Hence, in order to meet the overall service requirement and to enhance the overall efficiency of the network, cloud computing was introduced. The implementation of these devices tends to support in every node, it enhances better communication in a better range towards another nodes. There is a critical administration and support devices from everywhere in an effective manner.

Intelligent security system is an important part of intelligent site construction, which directly affects the life safety of operators and the level of engineering supervision. Traditional security communication systems for construction, mineral mining and other fields have problems such as small network coverage, low capacity, short terminal life and relatively simple function. According to the application scenarios and business requirements of intelligent security system, this paper uses LoRa AD-hoc networking technology to carry out the network architecture research and key technology design of intelligent security AD-hoc networking system. Further, the detailed design of the embedded software of the system terminal and gateway is completed, and the functions of physical sign monitoring, danger warning and terminal positioning are realized.

Low probability of detection (LPD) has recently emerged as a means to enhance the privacy and security of wireless networks. Unlike existing wireless security techniques, LPD measures aim to conceal the entire existence of wireless communication instead of safeguarding the information transmitted from users. Motivated by LPD communication, in this paper, we study a privacy-preserving and distributed framework based on graph neural networks to minimise the detectability of a wireless ad-hoc network as a whole and predict an optimal communication region for each node in the wireless network, allowing them to communicate while remaining undetected from external actors. We also demonstrate the effectiveness of the proposed method in terms of two performance measures, i.e., mean absolute error and median absolute error.

Vehicular Ad Hoc Networks (VANETs) have the capability of swapping every node of every individual while driving and traveling on the roadside. The VANET-connected vehicle can send and receive data such as requests for emergency assistance, current traffic conditions, etc. VANET assistance with a vehicle for communication purposes is desperately needed. The routing method has the characteristics of safe routing to repair the trust-based features on a specific node.When malicious activity is uncovered, intrusion detection systems (IDS) are crucial tools for mitigating the damage. Collaborations between vehicles in a VANET enhance detection precision by spreading information about interactions across their nodes. This makes the machine learning distribution system feasible, scalable, and usable for creating VANET-based cooperative detection techniques. Privacy considerations are a major impediment to collaborative learning due to the data flow between nodes. A malicious node can get private details about other nodes by observing them. This study proposes a cooperative IDS for VANETs that safeguards the data generated by machine learning. In the intrusion detection phase, the selected optimal characteristics is used to detect network intrusion via a hybrid Deep Neural Network and Bidirectional Long Short-Term Memory approach. The Trust-based routing protocol then performs the intrusion prevention process, stopping the hostile node by having it select the most efficient routing path possible.

Named Data Networking (NDN) has been considered a promising network architecture for Vehicular Ad Hoc Networks (VANETs), what became known as Vehicular Named-Data Networking (VNDN). This new paradigm brings the potential to improve Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) that are inefficient in urban intelligent transport scenarios. Despite the advantages, VNDN brings inherent problems, such as the routing interest packages on NDN, which causes serious problem in the vehicular environment. The broadcast storm attack results in a huge amount of packet loss, provoking transmission overload. In addition, the link disconnection caused by the highly dynamic topology leads to a low package delivery rate. In this article, we propose a strategy for forwarding packages of interest in VNDN networks, using fuzzy logic to mitigate the broadcast storm. The proposal also aims to avoid packet collision and efficient data recovery, which the approach is based on metrics such as the nodes distance, the link stability and the signal quality. The results show a reduction in the number of Interest and Data packets without disrupting network performance maintaining adequate Interest delays.

One of the popular networks highly used for creating various Adhoc network applications is Mobile Ad hoc Networks, which are vulnerable to various security attacks, one of which is the blackhole attack. One of the networks that come under MANET is the Vehicular Adhoc network. It uses multi-hop data transmission, which provides various pathways to malicious attacks. One of the attacks, non-identifiable easily, is a blackhole attack, a category of DoS attack. Earlier research methods provided different algorithms for identifying and detecting individual attacks or standard security methods. At the same time, the accuracy of malicious activity detection and elimination is not up to the mark. In which a malevolent node misleadingly publicizes itself as having the shortest path to a destination, causing other nodes to send their data to it, which the attacker discards. This paper proposes a genetic algorithm-based approach for detecting blackhole attacks in VANETs. Our approach uses a combination of network metrics, such as network throughput and end-to-end delay, and genetic algorithms to identify malicious nodes. The genetic algorithm is used to optimize the selection of network metrics and determine the weights given to each metric in the detection process. Simulation results show that our approach effectively detects blackhole attacks with high accuracy and low false positive rates.

At present, the application of wireless Ad hoc network in the field of mobile security inspection is in its infancy, and the network security protection means for the power industry are still insufficient, which is highlighted by the lack of efficient security authentication means for Ad hoc network, and it is difficult to completely eliminate security risks such as illegal terminal intrusion, data counterfeiting and tampering. A decentralized security authentication scheme suitable for Ad hoc network is designed, which can solve the security trust transfer problem on the variable network topology. Under any network route, the security trust is transferred to the proxy node step by step through multiple peer authentication, and the authentication chain is eUEblished between the digital intelligence edge proxy device, the proxy node and the node to be accessed. On the one hand, it can effectively solve the counterfeit problem of A-nodes and proxy nodes; on the other hand, it can greatly reduce the problem of reduced security authentication efficiency caused by deepening network hierarchy.

The new power system puts forward higher requirements for the communication interconnection of power equipment, especially in power areas that are difficult to cover by public networks and private power networks. As an efficient means, although building power communication ad hoc network has the advantages of low cost and flexibility, it puts forward higher requirements for the security of power ad hoc networks. This paper proposes a lightweight and secure access method for power WIFI to better meet the real-time requirements of power ad hoc networks. Based on the analysis of STA and AP flexible networking switching modes of WIFI ad hoc network system, this paper focuses on the security challenges of power WIFI ad hoc network system. Meanwhile, according to the environmental characteristics of the power ad hoc network, we simplify and improve the classic WIFI secure communication in three stages: Scanning, link authentication, and association, to improve lightweight and secure access to power WIFI. The secure access example of power ad hoc network of multiple nodes proves the effectiveness of the proposed method.

Information-Centric Networking (ICN) has emerged as a perfect match to support data-driven applications. Typically, ICN ensures data integrity and authenticity, by provisioning signed and verifiable data packets. Nonetheless, the ICN cryptography-based security scheme entails increased computational and communication cost, while also necessitates continuous connectivity to the infrastructure. We claim that this security approach requires supportive mechanisms to perform adequately in scenarios involving disruptive connectivity and short-term communication. In this paper, we investigate the applicability of two security approaches, namely the in-force cryptographybased approach and a ‘lighter’ reputation-based one, in ad hoc information-centric networks, and aim to identify the pros and cons of each solution. Our experiments rely on a scenario deemed appropriate for the particular research objective: we selected an ICN-based Flying Ad hoc Network (FANET). We assess the impact of intermittent connectivity, as well as, the associated computational and communication cost, and the dynamics of mobility. Our results demonstrate that the reputation-based approach allows for building trust relations in a fast and lightweight manner, but without requiring permanent connectivity to trusted third parties. Therefore, we argue that the standard ICN security system can be consolidated by integrating reputation-based trust as an essential complementary mechanism.

Unmanned aerial vehicles (UAVs) can be deployed and managed in a variety of applications with the help of flying ad hoc networks, or FANETs. However, the dynamically changing topology in FANET has raised significant challenges, mainly related to the insurance of security as a required service for the optimal performance of FANET networks. Blockchain technology has recently been used as an innovative solution to improve FANET security, due to its main characteristics such as transparency, decentralization, and tamper-proof nature. In this poster, we detail some current applications of Blockchain to secure FANET including military, surveillance, and Industry 4.0 services. Finally, we discuss some of the common issues associated with the application of Blockchain on FANET networks.

Flying Ad-hoc Networks (FANET) is an evolving phenomenon in the types of ad-hoc networks, which connects Multiple UAVs (Unmanned Aerial Vehicles) or drones. It is a rapidly deployable, infrastructure-less, self-configurable, and flexible communication environment for data transmission among the multi-UAVs and the Base Station (BS). As a result of technological advancement, the deployment of Multi-UAV networks or FANET has increased. Particularly in life-threatening applications like disaster management and military operations, this kind of ad-hoc network will be highly beneficial. Due to its characteristics of infrastructure-less and non-hierarchical behavior, FANETs faces several security issues in their flexible data communication. Since these kinds of networks are significantly emerging, there is a vital need to establish a threat model capable of identifying vulnerabilities, quantifying risks, and addressing them. In Existing observations, these FANET environment are highly vulnerable to any kind of security threats which in turn degrades the overall performance of the network. Securing the data packets in FANET communication is a crucial task because the nodes involved in this network are movable. Malicious nodes can compromise the confidentiality, availability, and integrity of the network by intruding and modifying data or discarding network packets. In this article, the classification of attacks and several security issues for the FANETs are highlighted. Then the experimental analysis of Packet-loss based detection and Content-Modification detection in the FANETs are implemented and discussed using Omnet++ simulation tool.

Neural Network Security - Trust is an essential concept in ad hoc network security. Creating and maintaining trusted relationships between nodes is a challenging task. This paper proposes a decentralized method for evaluating trust in ad hoc networks. The method uses neural networks and local information to predict the trust of neighboring nodes. The method was compared with the original centralized version, showing that even without global information knowledge, the method has, on average, 97\% accuracy in classification and 94\% in regression problem. An important contribution of this paper is overcoming the main limitation of the original method, which is the centralized evaluation of trust. Moreover, the decentralized method output is a perfect fit to use as an input to enhance routing in ad hoc networks.

MANET Security - The detection and maintenance of the pathway from the source to the destination or from one node to another node is the major role played by the nodes in the MANET. During their period, nodes arrive or leave the network, and endlessly modify their comparative location. The dynamic nature introduces several security issues. Secure routing protocol is a significant area for attaining better security in the network by keeping the routing protocols against attacks. Thus, this research work focuses on developing a secure routing protocol for MAN ET. Here, a dynamic anomaly detection scheme has proposed to detect against malicious attacks in the network. This scheme has been incorporated with AODV protocol to enhance the performance of AODV in disseminating packets to target node. In this research work Protected AODV (PAODV) is protocol is introduced to identify the false alarm node in the network and route path for reliable communication between the source to destination. Simulation results it shows the detection rate, Packet drop rate and delay is minimized compare to the existing technique.

MANET Security - Recently, the mobile ad hoc network (MANET) has enjoyed a great reputation thanks to its advantages such as: high performance, no expensive infrastructure to install, use of unlicensed frequency spectrum, and fast distribution of information around the transmitter. But the topology of MANETs attracts the attention of several attacks. Although authentication and encryption techniques can provide some protection, especially by minimizing the number of intrusions, such cryptographic techniques do not work effectively in the case of unseen or unknown attacks. In this case, the machine learning approach is successful to detect unfamiliar intrusive behavior. Security methodologies in MANETs mainly focus on eliminating malicious attacks, misbehaving nodes, and providing secure routing.

MANET Security - The current stady is confined in proposing a reputation based approach for detecting malicious activity where past activities of each node is recorded for future reference. It has been regarded that the Mobile ad-hoc network commonly called as (MANET) is stated as the critical wireless network on the mobile devices using self related assets. Security considered as the main challenge in MANET. Many existing work has done on the basis of detecting attacks by using various approaches like Intrusion Detection, Bait detection, Cooperative malicious detection and so on. In this paper some approaches for identifying malicious nodes has been discussed. But this Reputation based approach mainly focuses on sleuthing the critcal nodes on the trusted path than the shortest path. Each node will record the activity of its own like data received from and Transferred to information. As soon as a node update its activity it is verified and a trust factor is assigned. By comparing the assigned trust factor a list of suspicious or malicious node is created..

MANET Security - Remote correspondence innovations are assuming a critical part in the plan and execution of Mobile Ad hoc Network (MANET). The portrayal of MANET, for example, dynamism in geography, restricted transfer speed and power usage expands the unlicensed correspondence advancements and intricacies in existing conventions. This paper analyzes the current and not so distant future Wireless correspondence Technologies in the 2.4 GHz band. Additionally, this paper thinks about the features and limits of those advances lastly closes with the need for the improvement of reasonable brought together convention for existing and future remote advances. It has been considered that the overview and correlation introduced in this paper would help specialists and application engineers in choosing a fitting innovation for MANET administrations.

MANET Security - Mobile ad hoc networks can expand access networks service zones and offer wireless to previously unconnected or spotty areas. Ad hoc networking faces transmission failures limited wireless range, disguised terminal faults and packet losses, mobility-induced route alterations, and battery constraints. A network layer metric shows total network performance. Ad-hoc networking provides access networks, dynamic multi-hop architecture, and peer-to-peer communication. In MANET, each node acts as a router, determining the optimum route by travelling through other nodes. MANET includes dynamic topology, fast deployment, energy-restricted operation, and adjustable capacity and bandwidth. Dynamic MANET increases security vulnerabilities. Researchers have employed intrusion detection, routing, and other techniques to provide security solutions. Current technologies can t safeguard network nodes. In a hostile environment, network performance decreases as nodes increase. This paper presents a reliable and energy-efficient Firefly Energy Optimized Routing (IFEOR)-based routing method to maximise MANET data transmission energy. IFEOR measures MANET firefly light intensity to improve routing stability. The route path s energy consumption determines the firefly s brightness during MANET data packet transfer. Adopting IFEOR enhanced packet delivery rates and routing overheads. End-to-end delay isn t reduced since nodes in a route may be idle before sending a message. Unused nodes use energy.

MANET Attack Detection - Mobile Adhoc Networks also known as MANETS or Wireless Adhoc Networks is a network that usually has a routable networking environment on top of a Link Layer ad hoc network. They consist of a set of mobile nodes connected wirelessly in a self-configured, self-healing network without having a fixed infrastructure. MANETS, have been predominantly utilized in military or emergency situations however, the prospects of Manets’ usage outside these realms is now being considered for possible public adoption in light of the recent global events such as the pandemic and new emerging infectious diseases. These particular events birthed new challenges, one of which was the considerable strain that was placed on mainstream ISP’s. Whilst there has been a significant amount of research conducted in the sphere Manet Security via various means such as: development of intrusion detection systems, attack classification and prediction systems, etcetera. There still exists prevailing concerns of MANET security and risks. Additionally, recently researched trends within the field has evidenced key disparities in terms of studies related to MANET Risk profiles. This paper seeks to provide an overview of existing studies with respect to MANETS as well as briefly introduces a new method of determining the initial Risk Profile of MANETS via the usage of probabilistic machine learning techniques. It explores new regions of probability-based approaches to further supplement the existing impact-based methodologies for assessing risk within Manets.

MANET Attack Detection - One of the most essential self-configuring and independent wireless networks is the MANET. MANET employs a large number of intermediate nodes to exchange information without the need for any centralized infrastructure. However, some nodes act in a selfish manner, utilizing the network's resources solely for their own benefit and refusing to share with the surrounding nodes. Mobile ad hoc network security is a critical factor that is widely accepted. Selfish nodes are the primary problem of MANET. In a MANET, nodes that are only interested in themselves do not involve in the process of packet forwarding. A node can be identified as selfish or malicious due to some misbehavior reasons. Selfishness on the part of network nodes may be a factor in the low delivery ratio of packets and data loss. A high end-to-end delay is caused by node failure in a MANET network. To study the selfish node attack, a malicious selfish node is put into the network, and a trust-based algorithm for the selfish node attack is also suggested. In order to discover a solution to this issue, we have developed an algorithm called SNRM for the detection of selfish nodes. The routing protocol used in this paper for analysis is AODV. Using a simulation tool, PDR and end-to-end delay are evaluated and compared.

MANET Attack Detection - Recently, the mobile ad hoc network (MANET) has enjoyed a great reputation thanks to its advantages such as: high performance, no expensive infrastructure to install, use of unlicensed frequency spectrum, and fast distribution of information around the transmitter. But the topology of MANETs attracts the attention of several attacks. Although authentication and encryption techniques can provide some protection, especially by minimizing the number of intrusions, such cryptographic techniques do not work effectively in the case of unseen or unknown attacks. In this case, the machine learning approach is successful to detect unfamiliar intrusive behavior. Security methodologies in MANETs mainly focus on eliminating malicious attacks, misbehaving nodes, and providing secure routing. In this paper we present to most recent works that propose or apply the concept of Machine Learning (ML) to secure the MANET environment.

MANET Attack Detection - The current stady is confined in proposing a reputation based approach for detecting malicious activity where past activities of each node is recorded for future reference. It has been regarded that the Mobile ad-hoc network commonly called as (MANET) is stated as the critical wireless network on the mobile devices using self related assets. Security considered as the main challenge in MANET. Many existing work has done on the basis of detecting attacks by using various approaches like Intrusion Detection, Bait detection, Cooperative malicious detection and so on. In this paper some approaches for identifying malicious nodes has been discussed. But this Reputation based approach mainly focuses on sleuthing the critcal nodes on the trusted path than the shortest path. Each node will record the activity of its own like data received from and Transferred to information. As soon as a node update its activity it is verified and a trust factor is assigned. By comparing the assigned trust factor a list of suspicious or malicious node is created.

MANET Attack Prevention - Mobile ad hoc networks (MANETS) have gained much attention due to their dynamic nature and efficiency. These networks are operated in highly dynamic and unpredictable environment. Rapid advances in the field of correspondence have vastly enhanced today's transmission networks. As a result, the measurement of data transmission in business and military applications has grown dramatically. Since these applications include the transmission of information, the need for security concerns has grown as well. Due to their dynamic nature, they are susceptible to various attacks. The lack of a centralized authority to supervise the individual nodes operating in the network makes security in the mobile adhoc network a major challenge. Attacks can originate both within and outside the network. In this paper, a survey of various attacks in MANETs and their prevention and mitigation techniques given by researchers have been presented.

MANET Attack Prevention - Recently, the rising use of portable devices with advanced wireless communication gives Mobile ad-hoc networks more significance with the expanding number of widespread applications. This infrastructure uses a link-to-link wireless connection to transfer the data called route, which uses a routing protocol. AODV is a reactive protocol that uses control packets to discover a route toward the destination node in the network. Since MANET is an open infrastructure without a centralized controller, it is at risk of security assaults that are generated through the malicious node at the time of route discovery and data transmission. For example, the Blackhole attack in which the offender node retains and drops few or all data/control packets by using vulnerabilities of the on-demand routing protocols. This paper proposed a trust-based method to prevent the network against blackhole attack. This paper modeled the behavior of blackhole node and proposes a trust-based security technique. Further suggested technique is analyzed and evaluated against various evaluation metrics like PDR, throughput, end-to-end delay, attack percentage, etc. The proposed security technique is also compared with three different scenarios, namely attack, watchdog, and IDS scenarios, using the above evaluation metrics. The comparison shows that the proposed trust-based security ensures the detection and prevention against blackhole nodes not only at the time of route discovery but also at the time of real-time data transmission.

MANET Attack Prevention - Since the mid-1990s, the growth of laptops and Wi-Fi networks has led to a great increase in the use of MANET (Mobile ad hoc network) in wireless communication. MANET is a group of mobile devices for example mobile phones, computers, laptops, radios, sensors, etc., that communicate with each other wirelessly without any support from existing internet infrastructure or any other kind of fixed stations. As MANET is an infrastructure-less network it is prone to various attacks, which can lead to loss of information during communication, security breaches or other unauthentic malpractices. Various types of attacks to which MANET can be vulnerable are denial of service (DOS) and packet dropping attacks such as Gray hole, Blackhole, Wormhole, etc. In this research, we are particularly focusing on the detection and prevention of Gray hole attack. Gray hole node drops selective data packets, while participating in the routing process like other nodes, and advertises itself as a genuine node. The Intrusion Detection System (IDS) technique is used for identification and aversion of the Gray hole attack. Use of AODV routing protocol is made in the network. The network is incorporated and simulation parameters such as PDR (Packet Delivery Ratio), Energy Consumption, End-to-end delay, and Throughput are analyzed using simulation software.

MANET Privacy - A sub group of mobile ad hoc network(MANET) that is vehicular Ad Hoc Network (VANET) that assists in, vehicle to infrastructure (V2I) and vehicle to vehicle (V2V) intercommunications. An important characteristics of VANET consists of, highly dynamic, distributed networking and self-organizing topologies. In safeguarding billions of human live features of VANET and its uses regarding safety on roads drew attention towards huge amount of interest in academic fields and industries, moreover with study and development on enhancing the facilities of transport transit infrastructure. Major challenging and crucial security problems takes place during information transmission with open-access surrounding such as VANET. Non-repudiation, data confidentiality, Authentication, data availability and data integrity behave as a critical part of VANET’s security. Privacy preservation over VANET is major concern, in this research we will elaborate different attacks over VANET and will conclude how block chain based VANET will perform better and less error prone.