No abstract

Offering a secure communication in wireless adhoc network is yet an open-end problem irrespective of archives of existing literatures towards security enhancement. Inclination towards solving specific forms of attack in adhoc network is majorly seen as an existing trend which lowers the applicability of existing security solution while application environment or attack scenario is changed. Therefore, the proposed system implements an analytical secure routing modeling which performs consistent monitoring of the malicious behaviour of its neighboring node and formulates decision towards secure routing by the source nodes. Harnessing the potential ofconceptual probabilistic modeling, the proposed system is capable as well as applicable for resisting maximum number / types of threats in wireless network. The study outcome show proposed scheme offer better performance in contrast to existing secure routing scheme.

Wireless Ad hoc Network offers a cost effective communication to the users free from any infrastructural dependencies. It is characterized by decentralized architecture, mobile nodes, dynamic topology, etc. that makes the network formation typically challenging. In the past decade, there has been a series of research work towards enhancing its routing performance by addressing various significant problems. This manuscript mainly orients around the progress being made in the line of secure routing protocol, which is still a bigger issue. The paper discusses different approaches undertaken by existing literature towards discrete security problem and explores the effective level of security. The study outcome of the paper finds that progress towards wireless ad hoc network is still very less and there is a need to come up with robust security framework. The paper also discusses the research gap being identified from the existing techniques and finally discusses the future work direction to address the certain unsolved problem.

Study towards Wireless Adhoc Network dates two decades back with various researchers evolving up with new solutions towards addressing its problems. Irrespective of various other problems, the issues related to the secure routing is yet unsolved owing to massively increasing fatal strategies of the adversary. Review of existing literature shows that the existing secure routing scheme can only govern over the stated attacks reducing the applicability in case of dynamic attacks. Therefore, this manuscript introduces a novel probabilistic model which offers the capability to wireless nodes to identify the malicious behavior and react accordingly. Different from existing intrusion prevention system, the proposed system allows the malicious node to participate in the data forwarding process and exhaust its resources with no chance of launching an attack. The simulated outcome of the study shows that the proposed secure routing scheme offers better data forwarding characteristic in contrast to the existing system in the aspect of intrusion detection and secure data transmission.

Incorporating domain-specific priors in search and navigation tasks has shown promising results in improving generalization and sample complexity over end-toend trained policies. In this work, we study how object embeddings that capture spatial semantic priors can guide search and navigation task in a structured environment. We know that humans can search for an object like a book, or a plate in an unseen house, based on spatial semantics of bigger objects detected. For example, a book is likely to be on a bookshelf or a table, whereas a plate is likely to be in a cupboard or dishwasher. We propose a method to incorporate such spatial semantic awareness in robots by leveraging pre-trained language models and multirelational knowledge bases as object embeddings. We demonstrate using these object embeddings to search a query object in an unseen indoor environment. We measure the performance of these embeddings in an indoor simulator (AI2Thor). We further evaluate different pre-trained embedding on Success Rate (SR) and Success weighted by Path Length (SPL).