2 research outputs found
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