The acceptability of a location-based service (LBS) hinges on its ability to efficiently provide service while protecting both the privacy of the customer and the server's economic interests. These include the privacy of the user, point-of-interests (POIs) privacy of the service provider, and provision for anonymous payment. Existing schemes fulfill these requirements only partially. Most of the schemes protect the query privacy of the user and the privacy of the services provided by the server, however, at high computation and communication costs. We propose a privacy-provisioning location-based service(P2LBS) scheme that provides unconditional privacy to the user's query and protects the basket of services offered by the service provider from unnecessary revelation along with an inbuilt anonymous payment scheme. To ensure the authentication of the user and the server, the P2LBS scheme uses a ring signature and anonymous payment protocol respectively. Query privacy and the services' reply privacy are provided through an oblivious transfer (OT) protocol. Results show that the P2LBS scheme is efficient compared to other current state-of-the-art schemes in terms of communication and computation costs. It fulfills all the end-to-end requirements needed to make an LBS scheme viable.

Query content privacy and location privacy of the user and point of interest (POI) of the service provider are a serious concern for location-based services (LBS). The current LBS schemes either protect the query content privacy or location privacy. To protect query content of the user and POI of the server, several schemes have been proposed based on${k}$-anonymity, Oblivious transfer (OT), private information retrieval (PIR), and homomorphic encryption. To protect location privacy, the existing schemes either use cryptographic schemes or need a trusted third party (TTP) between the server and the user. A change of location requires re-execution of the core scheme, which causes communication and computational overhead. To address these problems, we propose a linkable location-based services (L2BS) scheme that uses Modified Linkable Spontaneous Anonymous Group (MLSAG) signature scheme and the OT scheme. The proposed MLSAG scheme provides privacy-preserving authentication with privacy preserving service linking. The OT protocol protects the query content of the user and the POI of the server. When a user requests for service and sends a query to the same server second time onwards, the L2BS scheme does not require re-execution of the OT. This, L2BSWOT scheme, decreases the communication and computation costs in addition to privacy-preserving linking of past and current queries from the same user. Results show that L2BS scheme with or without the need for OT execution (L2BSWOT scheme) outperforms other existing LBS schemes in terms of communication and computation costs while satisfying all privacy requirements of an LBS.

This work presents an uncertainty-based Trust Model (TM). It uses Dempster Shafer Theory (DST) to cater to uncertainty arising due to information scarcity in Vehicular Adhoc Networks (VANETs). DST combines direct and indirect trust values of vehicles sending messages to build its new trust opinion. Malicious vehicles, albeit authenticated, may alter or drop messages. The solution is to establish trust. Trust establishment assumes that vehicle behaviour is predictable, and its past transactions are useful for anticipating its future response. The high vehicular mobility, dynamic topology, and low neighbourhood density in VANETs cause a lack of credible information for establishing trust. The work also presents the introduction of the penalty function, forgetting function, rewarding factor, and the uncertainty-based importance factor during the combination of direct and indirect trust values using DST. Apart from this, the forgiving factor deals with a situation when a distrusted vehicle starts behaving ideally. Additionally, we present trust contexts based on types of messages altered or dropped by them. Four different trust levels and uncertainty in DUEL aids the receiver make correct decisions during an attack. DUEL is applied and tested on the real-time data of vehicle trajectory. Results show that DUEL can capture both false message attacks and message suppression attacks even in rapidly changing neighbourhoods and performs well in terms of high values of TPR and low values of FPR.

Graph convolutional networks (GCN) exploit graph connectivity through their adjacency matrix. However, the assignment of equal importance to every one-hop neighbor and incognizance of intra-neighbor connectivity restricts its performance. Graph attention networks (GAT) address the problem of treating all neighbors equally by employing a self-attention mechanism, which encodes the node of interest using the weighted features of its one-hop neighbors. This imparts appropriate similarity based weight between connected nodes. The learning of weights of nodes takes into consideration the intra-neighbor connectivity between nodes common to a neighborhood. However, this ignores the nature of neighborhood of the node of interest. In this work, we propose to encode the nature of the neighborhood of a node onto itself by appropriately weighing the node's self-loop. The local clustering coefficient of a graph explores to what extent which nodes in a graph tend to bunch together. A vertex with a low clustering coefficient and a large degree shows connectivity between different classes. Similarly, a vertex with a high clustering coefficient and low degree represents tightly coupled similar vertices belonging to the same class. Thus, the node self-loop is initially weighed with the local clustering coefficient. Experiment results on the benchmark graph dataset, including Cora, Citeseer, and Pubmed, shows that even with sparse two layers, the local clustering coefficient based self-loop outperforms the baseline GCN by ≈ 3%. The Ablation study and learning curve prove that the proposed model remains stable and learns the optimal feature representation in comparatively less number of epochs.

An authentication technique allows node to dynamically join the network, sense data and transmit authenticated data before going back to sleep. All the existing cryptosystems suffer from high computation or communication overhead, delayed authentication, severe energy diminution attacks and lack of scalability. The lack of efficiency, scalability or security can be attributed to the standard cryptographic primitives employed by the protocols. In this paper, Rainbow multivariate signature is proposed and explored as an alternative cryptographic mechanism for message authentication in Wireless sensor networks (WSN). The Rainbow class of signatures has been found to be suitable for resource scarce systems although the key size is large. The work determines the efficacy of this signature in a WSN environment by finding the computational and communication overheads due to the signature. Simulation shows that there is a significant increase in delay and queue size with a corresponding delay in the message throughput. However, the computational needs, the delay and throughput penalties are within tolerable limits even when the network density increases significantly. This shows that Rainbow signature can be used as an underlying cryptographic mechanism for efficient and scalable authentication protocols.

A vehicle can be tracked through its locatable transmission. The broadcast by a source contains its current identity and also allows estimation of its location by a receiver. This possibility of mapping between the physical entity and the estimated location through the communication broadcast is a threat to privacy. The changes in the location due to motion and the alteration in the temporal identifiers diminish the correlation between location and physical entity. However, such a mapping can still be recognized when an actively communicating node in relative isolation is observed for a sufficient interval of time. This paper addresses the challenges in providing anonymity to a moving vehicle that continually switches identifiers. As a vehicle moves on a road, its neighbors change in accordance to its relative speed with neighboring vehicles. This change in the nature and size of the neighborhood, i.e. the entropy, the degree of the anonymity of a vehicle. It is shown that the effective entropy reduces drastically due to change in the neighbors and transmissions by vehicles. The work studies the possibility that a node may retain its anonymity by switching identities in the vicinity of other vehicles to decorrelate its location and identity relation. A heuristic that allows a vehicle to switch its identity at a time and place where the potential of anonymity preservation can be maximized by increasing the entropy is proposed. The performance of the proposed heuristic is evaluated in a highway environment with vehicle mobility and dynamic vehicle population. Simulation results indicate that updating pseudonyms in accordance to the heuristic maximizes the entropy and through it, the anonymity of a vehicle.

BACKGROUND: Feature selection is an approach to overcome the 'curse of dimensionality' in complex researches like disease classification using microarrays. Statistical methods are utilized more in this domain. Most of them do not fit for a wide range of datasets. The transform oriented signal processing domains are not probed much when other fields like image and video processing utilize them well. Wavelets, one of such techniques, have the potential to be utilized in feature selection method. The aim of this paper is to assess the capability of Haar wavelet power spectrum in the problem of clustering and gene selection based on expression data in the context of disease classification and to propose a method based on Haar wavelet power spectrum. RESULTS: Haar wavelet power spectra of genes were analysed and it was observed to be different in different diagnostic categories. This difference in trend and magnitude of the spectrum may be utilized in gene selection. Most of the genes selected by earlier complex methods were selected by the very simple present method. Each earlier works proved only few genes are quite enough to approach the classification problem 1. Hence the present method may be tried in conjunction with other classification methods. The technique was applied without removing the noise in data to validate the robustness of the method against the noise or outliers in the data. No special software or complex implementation is needed. The qualities of the genes selected by the present method were analysed through their gene expression data. Most of them were observed to be related to solve the classification issue since they were dominant in the diagnostic category of the dataset for which they were selected as features. CONCLUSION: In the present paper, the problem of feature selection of microarray gene expression data was considered. We analyzed the wavelet power spectrum of genes and proposed a clustering and feature selection method useful for classification based on Haar wavelet power spectrum. Application of this technique in this area is novel, simple, and faster than other methods, fit for a wide range of data types. The results are encouraging and throw light into the possibility of using this technique for problem domains like disease classification, gene network identification and personalized drug design.

Internet services are being deployed over an infrastructure that involves co‐operation between multiple organizations and systems. This has necessitated the need for standard means to share the information between the service providers and their customers. This information essentially pertains to the service level obligations between the service provider and their customers so that the customers can ensure the quality of service (QoS) that they are able to achieve at their end. A service level agreement (SLA) essentially quantifies the level of service as it includes the metrics that define the quality of service. The research undertaken identifies the QoS dimensions, which are required to define the multimedia services. Each application used by the user will involve different values of the QoS dimensions in order to maintain an expected level of service. The QoS requirement for a particular application will also depend upon the provisioning of the network resources depending on the client and server side CPU and memory available for processing. The relationship between the system resources, QoS dimensions and the SLA has been depicted in the form of a general model of SLA and as an example taken for the video conferencing application.