At each iteration, the PS broadcasts different quantized global model updates to different participating devices based on the last global model estimates available at the devices.
Log-based cyber threat hunting has emerged as an important solution to counter sophisticated cyber attacks.
Log-based cyber threat hunting has emerged as an important solution to counter sophisticated attacks.
At each iteration, wireless devices perform local updates using their local data and the most recent global model received from the PS, and send their local updates to the PS over a wireless fading multiple access channel (MAC).
The PS has access to the global model and shares it with the devices for local training, and the devices return the result of their local updates to the PS to update the global model.
We analyze the convergence behavior of the proposed LFL algorithm assuming the availability of accurate local model updates at the server.
At each iteration of FL, a subset of the devices are scheduled to transmit their local model updates to the PS over orthogonal channel resources, while each participating device must compress its model update to accommodate to its link capacity.
To facilitate the task of expressing anomalies based on expert knowledge, our system provides a domain-specific query language, SAQL, which allows analysts to express models for (1) rule-based anomalies, (2) time-series anomalies, (3) invariant-based anomalies, and (4) outlier-based anomalies.
Cryptography and Security Databases
Traditional eye tracking requires specialized hardware, which means collecting gaze data from many observers is expensive, tedious and slow.
The relationships between statistical and geometric properties of attack vectors employed in the attack scenarios and learning algorithms are analyzed to detect unobservable attacks using statistical learning methods.
A new segmentation fusion method is proposed that ensembles the output of several segmentation algorithms applied on a remotely sensed image.
In this paper, we propose two recommendation models, for individuals and for groups respectively, based on social contagion and social influence network theory.
Collaborative filtering (CF) is one of the most popular approaches to build a recommendation system.