Search

Vehicular ad-hoc network (VANET) is widely applied in transportation applications to ensure safety and security during road transportation. In VANET, all the information's are interchanged among vehicles with the available infrastructure on the roadside to form an ad-hoc network. In VANET, due to its communication in an open medium achieving the major security goals like integrity, authenticity, anonymity and traceability are the major concern. Since, there are numerous vehicles in the network generation and verification of digital signature requires high storage along with and verification time. To overcome all these issues, in this paper an Efficient group signature based certificate less verification scheme (EGSCVS) has been proposed to provide lightweight end to end authentication in the network. The proposed EGSCVS employs certificate less aggregation signature mechanism which is based on Elliptical curve cryptography to optimize the storage and reduce the overhead in terms of communication and computation during authentication process. Moreover, the proposed protocol utilizes the Random oracle model (ROM) to provide the formal security analysis. The implementation of the proposed protocol has been implemented using NS3 simulator with realistic simulation parameters. The simulation result shows that the proposed protocol improves the transmission overhead by 53.16%, computational cost by 48.75%, communication cost by 42.81%, signing delay by 55.17%, verification delay by 28.38% and aggregate verification delay by 45.35%. [ABSTRACT FROM AUTHOR]

The main advantage of Vehicular Adhoc Networks being an inherent part of Intelligent Transportation Systems is to ensure the safety and comfort of commuters on the roads. In VANETs, due to the wide open nature of wireless communications, data transmission has been subjected to variety of security and privacy threats which causes disruptions in the network. Hence data has to be authenticated prior to communication. To address this problem enhanced elliptic curve cryptography based certificate-less signature aggregation scheme has been proposed to ensure full privacy preservation and to provide efficient security to the VANETs. Through formal and informal security analysis the proposed scheme has been tested and proven to be secure under suppositions made using Diffie-Hellman assumptions by using Random Oracle Model. The proposed scheme is implemented using MIRACL C + + library and by using Veins Integrated Simulation Framework. The proposed scheme has been analyzed and compared with the existing standards which prove that the proposed scheme is efficient in terms of computation cost and communication costs. The major novelty of the proposed scheme is the use of aggregation and point addition which does not cause delay in verification and also reduces overhead in the road-side units by employing elliptic curve cryptography based distributed data authentication scheme. Hence, the traditional problems of certificate management and key escrow problem is solved by the proposed scheme in an efficient manner. This makes the proposed scheme to be much suitable for high volatile and resource-constrained vanet environments. [ABSTRACT FROM AUTHOR]

Underwater Wireless Sensor Networks (UWSNs) are the type of WSNs that transmit the data through water medium and monitor the oceanic conditions, water contents, under-sea habitations, underwater beings and military objects. Unlike air medium, water channel creates stronger communication barriers. In addition, the malicious data injection and other network attacks create security problems during data communication. Protecting the vulnerable UWSN channel is not an easy task under critical water conditions. Many research works proposed in the literature used cryptography principles and intelligent intrusion detection systems to secure the network activities from malicious nodes. However, the need for Machine Learning (ML) and Deep Learning (DL) associated Medium Access Control (MAC) principles is expected for handling the barriers in uncertain UWSN. In this regard, this article proposes a new Intrusion detection system with Integrated Secure MAC principles and Long Short-Term Memory (LSTM) architectures for organizing real-time neighbor monitoring tasks. The proposed system implements Generative Adversarial Network (GAN) driven UWSN channel assessment models and Secure LSTM-MAC principles to protect the data communication. In this regard, the proposed model creates the Intrusion Detection System (IDS) using trained distributed agents. These agents run in each legitimate sensor node contain novel LSTM-MAC engine, intrusion dataset, rule-based monitoring techniques, Secure Hashing Algorithm-3 (SHA-3), Two Fish algorithm and packet filtering tools. The proposed LSTM and agent-based model drives adaptive MAC channel operations to avoid malicious traffics in to legitimate nodes. In addition, this work implements neighbor-based packet monitoring, signal jamming and alert messaging procedures to build reliable security services against different types of attacks. The experiments and the observations reveal the performance of proposed techniques is proved to be 5% to 10% higher than existing techniques in various aspects measured with different metrics. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSNs) contain multiple wireless sensor nodes deployed around the geographical locations. The WSN used in military applications need more security and hence the deployment of trustworthy nodes and links in WSN provides more secure data transmission in Decentralized Military Sensor Networks (DMSNs). Moreover, the DMSNs work with different set of significance constraints including higher security requirements. The design of DMSNs targets surveillance tasks, intruder tracking tasks, army resource maintenance tasks and communication security requirements. Therefore, building a secure and dynamic DMSN against multiple threats is a challenging task. In addition, security principles developed for DMSN cause excessive energy consumption. Moreover, DMSN has completely open distributed architecture without having any base stations. Under this situation, the need for effective and secured data communication can be achieved with the help of a secure routing protocol. Block chains are generally used for making secure financial transactions. However, the routing protocols used in DMSN can support autonomous routing transactions from one node to other node. In this situation, block chain enabled routing procedures can ensure the trustworthiness of any data that is forwarded through different sensor nodes. Hence, a new Generative Adversarial Networks (GAN) based Block Chain enabled secured Routing Protocol (GBCRP) is proposed in this paper which authenticates and validates the ongoing routing procedures of DMSN. Moreover, a new intrusion detection system is also proposed in this work using GAN which is deployed in the nodes of the DMSN for enhancing the security of communication. Since block chain based routing protocols do not provide security, the GBCRP works for creating volatile block chains using decentralized authentication principles and effective intrusion detection. The proposed system uses a Fully Decentralized Generative Adversarial Network (FDGAN) for monitoring the secure routing transactions by the development of an intrusion detection system. The results obtained from this work show that the proposed GBCRP providing better secured routing compared to the existing systems with respect to security, energy consumption and routing metrics. [ABSTRACT FROM AUTHOR]

Middle-box based attacks create serious functional defects in the devices such as firewalls, address translators, load balancers, server units, and other data inspecting devices. Middle-box based attacks are more severe than terminal node-based attacks. These attacks are mainly initiated to malfunction the internal events of middle-level devices. Notably, Internet of Healthcare Things (IoHT) is a completely distributed and heterogeneous environment that leads into more vulnerable events. In the distributed medical system field, the middle-box devices manage secret medical data transactions, internal network communication, patient data protection principles and packet inspection procedures. The medical data collected from each patient needs secrecy and stability in various aspects in the IoHT environment. The middle-box based attacks injected into the IoHT nodes create inefficiency in maintaining patient data, Denial of Service (DoS) at middle-box nodes, excessive diagnosis time, and lack of data protection. For handling these issues, a new security architecture and a new attack detection model are proposed in this paper which has been developed using ranking subsets and Convolutional Neural Network (CNN) principles. The proposed CNN with ranking principles model is designed with binary class fuzzy fisher face optimization technique and flower pollination optimization method to initiate feature extraction. The extracted features of each data flow are analyzed using CNN and ranking subset methodologies. In this proposed model, the continuous involvement of middle-box events in respective devices are classified under various anomaly cases and legitimate cases. The proposed IoHT model attains maximum success rate than the existing models as indicated in implementation section. [ABSTRACT FROM AUTHOR]

A wireless sensor network (WSN) is made up of many sensor nodes with insufficient energy, storage, and processing capabilities. Data gathering and transmission to the base station are two of the main responsibilities of the sensor nodes (BS). As a result, the network lifespan becomes the key factor in the successful design of data collection strategies in WSN. In this study, we provide the Enriched energy optimized LEACH (EE-OLEACH) protocol for data transfer. Through a combination of efficient optimum clustering and an optimal route selection mechanism, it provides a means for energy-efficient routing in WSN. The Homogeneous Hunter-Wolf optimization (HHWO) is used for clustering, and a cluster head is chosen for each cluster to reduce energy loss among sensor nodes and maximize efficiency in their use of available resources. Nodes with the highest residual energy may receive the most energy-efficient routing. In order to send the data to BS, the nodes with the greatest residual energy are chosen. The pheromone-profound Ant optimization (PPAO) method was then used to reduce energy consumption throughout the path-selection process. It contributes to a higher packet delivery ratio while reducing power consumption. According to the experimental findings, the proposed EE-OLEACH performs better than the current Protocol in terms of packet delivery ratio, end-to-end latency, and energy usage. In this paper, we compare the performance of the existing hierarchical routing protocols under varying conditions (packet size, starting energy level, etc.) and demonstrate how the optimal CH selection based on a suggested algorithm improves both network lifetime and energy consumption. The Simulation results shows that the EE-OLEACH enhances energy efficiency by 30%, delay by 35%, node survived by 45%, network lifetime by 56%, packet delivery ratio by 47% and throughput by 38% when compared with other existing protocols. The results clearly show that the suggested EE-OLEACH extends the lifespan of the network and reduce the energy consumption. [ABSTRACT FROM AUTHOR]