Survey on Multi-Document Summarization: Systematic Literature Review

In this era of information technology, abundant information is available on the internet in the form of web pages and documents on any given topic. Finding the most relevant and informative content out of these huge number of documents, without spending several hours of reading has become a very challenging task. Various methods of multi-document summarization have been developed to overcome this problem. The multi-document summarization methods try to produce high-quality summaries of documents with low redundancy. This study conducts a systematic literature review of existing methods for multi-document summarization methods and provides an in-depth analysis of performance achieved by these methods. The findings of the study show that more effective methods are still required for getting higher accuracy of these methods. The study also identifies some open challenges that can gain the attention of future researchers of this domain

Secure Authentication Mechanism for Cluster based Vehicular Adhoc Network (VANET): A Survey

Vehicular Ad Hoc Networks (VANETs) play a crucial role in Intelligent Transportation Systems (ITS) by facilitating communication between vehicles and infrastructure. This communication aims to enhance road safety, improve traffic efficiency, and enhance passenger comfort. The secure and reliable exchange of information is paramount to ensure the integrity and confidentiality of data, while the authentication of vehicles and messages is essential to prevent unauthorized access and malicious activities. This survey paper presents a comprehensive analysis of existing authentication mechanisms proposed for cluster-based VANETs. The strengths, weaknesses, and suitability of these mechanisms for various scenarios are carefully examined. Additionally, the integration of secure key management techniques is discussed to enhance the overall authentication process. Cluster-based VANETs are formed by dividing the network into smaller groups or clusters, with designated cluster heads comprising one or more vehicles. Furthermore, this paper identifies gaps in the existing literature through an exploration of previous surveys. Several schemes based on different methods are critically evaluated, considering factors such as throughput, detection rate, security, packet delivery ratio, and end-to-end delay. To provide optimal solutions for authentication in cluster-based VANETs, this paper highlights AI- and ML-based routing-based schemes. These approaches leverage artificial intelligence and machine learning techniques to enhance authentication within the cluster-based VANET network. Finally, this paper explores the open research challenges that exist in the realm of authentication for cluster-based Vehicular Adhoc Networks, shedding light on areas that require further investigation and development