Blar i NTNU Open på forfatter "Yazidi, Anis"
-
A General Formalism for Defining and Detecting OpenFlow Rule Anomalies
Aryan, Ramtin; Yazidi, Anis; Engelstad, Paal E.; Kure, Øivind (Chapter, 2017)SDN network's policies are updated dynamically at a high pace. As a result, conflicts between policies are prone to occur. Due to the large number of switches and heterogeneous policies within a typical SDN network, detecting ... -
AWkS: adaptive, weighted k‑means‑based superpixels for improved saliency detection
Gupta, Ashish Kumar; Seal, Ayan; Yazidi, Anis (Peer reviewed; Journal article, 2020)Clustering inspired superpixel algorithms perform a restricted partitioning of an image, where each visually coherent region containing perceptually similar pixels serves as a primitive in subsequent processing stages. ... -
Balanced difficulty task finder: an adaptive recommendation method for learning tasks based on the concept of state of flow
Yazidi, Anis; Abolpour Mofrad, Asieh; Goodwin, Morten; Hammer, Hugo Lewi; Arntzen, Erik (Peer reviewed; Journal article, 2020)An adaptive task difficulty assignment method which we reckon as balanced difficulty task finder (BDTF) is proposed in this paper. The aim is to recommend tasks to a learner using a trade-off between skills of the learner ... -
Enhanced Equivalence Projective Simulation: A Framework for Modeling Formation of Stimulus Equivalence Classes
Abolpour Mofrad, Asieh; Yazidi, Anis; Abolpour Mofrad, Samaneh; Hammer, Hugo Lewi; Arntzen, Erik (Peer reviewed; Journal article, 2021)Formation of stimulus equivalence classes has been recently modeled through equivalence projective simulation (EPS), a modified version of a projective simulation (PS) learning agent. PS is endowed with an episodic memory ... -
Enhancing security attacks analysis using regularized machine learning techniques
Hagos, Desta Haileselassie; Yazidi, Anis; Kure, Øivind; Engelstad, Paal E. (Journal article; Peer reviewed, 2017)With the increasing threats of security attacks, Machine learning (ML) has become a popular technique to detect those attacks. However, most of the ML approaches are black-box methods and their inner-workings are difficult ... -
Equivalence Projective Simulation as a Framework for Modeling Formation of Stimulus Equivalence Classes
Abolpour Mofrad, Asieh; Yazidi, Anis; Hammer, Hugo Lewi; Arntzen, Erik (Journal article; Peer reviewed, 2020)Stimulus equivalence (SE) and projective simulation (PS) study complex behavior, the former in human subjects and the latter in artificial agents. We apply the PS learning framework for modeling the formation of equivalence ... -
Evading a Machine Learning-based Intrusion Detection System through Adversarial Perturbations
Fladby, Torgeir; Haugerud, Hårek; Nichele, Stefano; Begnum, Kyrre; Yazidi, Anis (Chapter, 2020)Machine-learning based Intrusion Detection and Prevention Systems provide significant value to organizations because they can efficiently detect previously unseen variations of known threats, new threats related to known ... -
EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality
Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (Chapter, 2020)Dynamical systems possess a computational capacity that may be exploited in a reservoir computing paradigm. This paper presents a general representation of dynamical systems which is based on matrix multiplication. That ... -
A general representation of dynamical systems for reservoir computing
Pontes-Filho, Sidney; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, I.; Tufte, Gunnar; Nichele, Stefano (Chapter, 2019)Dynamical systems are capable of performing computation in a reservoir computing paradigm. This paper presents a general representation of these systems as an artificial neural network (ANN). Initially, we implement the ... -
General TCP state inference model from passive measurements using machine learning techniques
Hagos, Desta Haileselassie; Engelstad, Paal E.; Yazidi, Anis; Kure, Øivind (Journal article; Peer reviewed, 2018)Many applications in the Internet use the reliable end-to-end Transmission Control Protocol (TCP) as a transport protocol due to practical considerations. There are many different TCP variants widely in use, and each variant ... -
A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality
Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (Peer reviewed; Journal article, 2020)Although deep learning has recently increased in popularity, it suffers from various problems including high computational complexity, energy greedy computation, and lack of scalability, to mention a few. In this paper, ... -
Recovering Request Patterns to a CPU Processor from Observed CPU Consumption Data
Hammer, Hugo Lewi; Yazidi, Anis; Bratterud, Alfred; Haugerud, Hårek; Feng, Boning (LNICST;, Conference object; Peer reviewed, 2016)Statistical queuing models are popular to analyze a computer systems ability to process different types requests. A common strategy is to run stress tests by sending artificial requests to the system. The rate and sizes ... -
A Reinforcement Learning based Game Theoretic Approach for Distributed Power Control in Downlink NOMA
Rauniyar, Ashish; Yazidi, Anis; Engelstad, Paal E.; Østerbø, Olav Norvald (Chapter, 2020)Optimal power allocation problem in wireless networks is known to be usually a complex optimization problem. In this paper, we present a simple and energy-efficient distributed power control in downlink Non-Orthogonal ...