For instance, digital archives for textiles offer keyword search, which is fairly well understood, and arrange their content following a certain taxonomy, but search functionality at the level of thread structure is still missing.
Swift response to the detection of endangered minors is an ongoing concern for law enforcement.
Multi-year digital forensic backlogs have become commonplace in law enforcement agencies throughout the globe.
This knowledge and know-how information are collected from various sources, hence the question is how to organise this knowledge so that it can be efficiently exploited.
The integrating and cooperating of these two steps need an effective knowledge management, concretely an efficient map of knowledge in order to take the advantage of mined knowledge to guide mining the data.
Achieving high performance for facial age estimation with subjects in the borderline between adulthood and non-adulthood has always been a challenge.
Our approach is to build a neural network model utilizing Adversarial Autoencoder (AAE-$\alpha$) in order to detect the activity of an attacker who leverages off-the-shelf tools and system applications.
EM side-channel analysis is a technique where unintentional electromagnetic emissions are used for eavesdropping on the operations and data handling of computing devices.
Cryptography and Security General Literature
To date, there is little research on the digital traces in modern radio communication equipment.
Cryptography and Security Computers and Society
In this paper, we present a new approach of distributed clustering for spatial datasets, based on an innovative and efficient aggregation technique.
Instead of considering each time-step separately, the observation of prediction errors from a certain number of time-steps is now proposed as a new idea for detecting collective anomalies.
In this paper, we present a comparative study of software libraries and algorithms to optimise the processing of LiDAR data.
Remote sensing research focusing on feature selection has long attracted the attention of the remote sensing community because feature selection is a prerequisite for image processing and various applications.
However, their application to very large spatial datasets presents numerous challenges such as high-dimensionality data, heterogeneity, and high complexity of some algorithms.
We examine two fitness functions from previous studies and develop two new fitness functions to evolve GP classifier with superior accuracy on the minority class and overall.
Most of the cur- rent research on anomaly detection is based on the learning of normally and anomaly behaviors.