Revocable key aggregate searchable encryption with user privacy and anonymity
The KASE schemes allow fine-grained delegation of search rights over a selected dataset using an aggregate key. However, when the existing KASE schemes are deployed in real-time applications, the support of revocation of delegated rights is highly ...
Reinforcement learning-based cooperative sensing in cognitive radio networks for primary user detection
Cognitive radio networks achieve a better utilisation of spectrum through spectrum sharing. Due to interference, power levels and hidden terminal problem, it becomes challenging to detect the presence of primary users accurately and without this, spectrum ...
A comprehensive study of watermarking schemes for 3D polygon mesh objects
Three-dimensional (3D) objects have been used in machine design, architecture design, entertainment, cultural heritage, medical field, etc. during the last two decades. Increasing trends of 3D objects attract the researcher, academician, and industry ...
Cryptanalysis and improvement of an authentication scheme for IoT
With the interference of various types of embedded devices, sensors and gadgets in day-to-day life, the buzzword internet of things (IoT) has become very popular. In the context of IoT environment, proper device authentication is important. Recently, Wang ...
Ensemble learning algorithms with feature reduction mechanism for intrusion detection system
One of the most significant requirements for improving the accuracy and performance of the detection engine in an intrusion detection system (IDS) is to identify and pick just the most important and relevant features. Due to the advancement of some ...
ML-SDNIDS: an attack detection mechanism for SDN based on machine learning
With the rapid development of network technology, there are more and more application scenarios of software defined networking (SDN), such as big data, cloud computing, internet of things, etc. However, the facilities in the SDN network face security ...
Applying swarm intelligence and data mining approach in detecting online and digital theft
Various methods have been proposed to deal with phishing attacks. Using machine learning along with data mining, such as MLP techniques, is one of the practical approaches to detect these attacks. To detect phishing attacks by the neural network with ...
Development of adaptive AdaBoost classifier with optimal feature selection for enhanced intrusion detection in IoT
The fundamental intention of this paper is to model IDS in IoT platforms using an adaptive AdaBoost classifier. In the data collection phase, the intrusion dataset of IoT is collected from the standard benchmark sources. Further, data cleaning is ...
Multiple backup method of financial encrypted data on internet of things platform
In order to overcome the problems of data access, time-consuming and poor security, existing in the traditional multiple backup method of financial encrypted data, a new multiple backup method of financial encrypted data is proposed under the platform of ...
You are safe when you tell the truth: a blockchain-based privacy-preserving evidence collection and distribution system for digital forensics
With the development of information technology, digital evidence has played a crucial role in court trial. However, digital evidence incurs serious security threats and privacy issues in the process of collection, storage and distribution, and the real ...