Search results for "Intrusion"

“Submarine spring and salt water intrusion in fractured environment

2003

A Hierarchical Detection and Response System to Enhance Security Against Lethal Cyber-Attacks in UAV Networks

2018

International audience; Unmanned aerial vehicles (UAVs) networks have not yet received considerable research attention. Specifically, security issues are a major concern because such networks, which carry vital information, are prone to various attacks. In this paper, we design and implement a novel intrusion detection and response scheme, which operates at the UAV and ground station levels, to detect malicious anomalies that threaten the network. In this scheme, a set of detection and response techniques are proposed to monitor the UAV behaviors and categorize them into the appropriate list (normal, abnormal, suspect, and malicious) according to the detected cyber-attack. We focus on the m…

Motivated forgetting reduces veridical memories but slightly increases false memories in both young and healthy older people.

2017

The aim of the current study is to examine the effects of motivated forgetting and aging on true and false memory. Sixty young and 54 healthy older adults were instructed to study two lists of 18 words each. Each list was composed of three sets of six words associated with three non-presented critical words. After studying list 1, half of the participants received the instruction to forget List 1, whereas the other half received the instruction to remember List 1. Next, all the subjects studied list 2; finally, they were asked to remember the words studied in both lists. The results showed that when participants intended to forget the studied List 1, they were less likely to recall the stud…

Effects of suppressing neutral and obsession-like thoughts in normal subjects: beyond frequency

2004

Abstract Recent cognitive-behavioral theories on obsessive–compulsive disorder (OCD) show that deliberate attempts to suppress intrusive and undesirable thoughts lie at the genesis of clinical obsessions. In this paper the results of an experimental study on the suppression of neutral and obsession-like thoughts in normal subjects are presented. Eighty-seven university students performed in three experimental periods: (1) base-line monitoring, (2) experimental instruction, and (3) monitoring. For each of these periods, the frequency of the occurrence of a “white bear” thought or a personally relevant intrusive thought was registered. Half of the subjects received instructions to suppress th…

Dysmorphic and illness anxiety‐related unwanted intrusive thoughts in individuals with obsessive–compulsive disorder

2021

Background/objective Unwanted intrusive thoughts (UITs) are considered normal variants of the obsessions found in obsessive-compulsive disorder (OCD). Similarly, intrusive and persistent preoccupations about appearance defects in body dysmorphic disorder (BDD) and images and thoughts about illness in illness anxiety disorder (IAD) are abnormal variants of the thoughts and concerns about appearance and health found in non-clinical individuals. This study examines whether patients with OCD have frequent and distressing UITs with contents related to BDD and IAD, in addition to OCD-related UITs. Method Thirty-nine participants with OCD (Mage = 32.45, standard deviation [SD] = 11.57; 63% men) co…

Transverse sacral fracture with intrapelvic intrusion of the lumbosacral spine: case report and review of the literature.

2000

Mitigating DDoS using weight‐based geographical clustering

2020

Distributed denial of service (DDoS) attacks have for the last two decades been among the greatest threats facing the internet infrastructure. Mitigating DDoS attacks is a particularly challenging task as an attacker tries to conceal a huge amount of traffic inside a legitimate traffic flow. This article proposes to use data mining approaches to find unique hidden data structures which are able to characterize the normal traffic flow. This will serve as a mean for filtering illegitimate traffic under DDoS attacks. In this endeavor, we devise three algorithms built on previously uncharted areas within mitigation techniques where clustering techniques are used to create geographical clusters …

Ten years surface-atmosphere water budget from the ISAC micrometeorological base in Salento peninsula and comments on the aquifer balance

2016

Data from a ten years (2003-2013) period of activity of the ISAC-Lecce micrometeorological station have been discussed focusing on the atmosphere-surface exchange. Some suitable indices have been calculated such as the precipitation intensity, the aridity index and the ground water infiltration fraction (ratio of the difference between precipitation and real evapotranspiration and the precipitation). Possible trends of annual averages in the decadal period are considered, trying to take also into account the statistical uncertainty associated to measurement errors and missing data. The results indicate a significant increasing in the precipitation intensity together with an experimental evi…

Artificial Intelligence for Cybersecurity: A Systematic Mapping of Literature

2020

Due to the ever-increasing complexities in cybercrimes, there is the need for cybersecurity methods to be more robust and intelligent. This will make defense mechanisms to be capable of making real-time decisions that can effectively respond to sophisticated attacks. To support this, both researchers and practitioners need to be familiar with current methods of ensuring cybersecurity (CyberSec). In particular, the use of artificial intelligence for combating cybercrimes. However, there is lack of summaries on artificial intelligent methods for combating cybercrimes. To address this knowledge gap, this study sampled 131 articles from two main scholarly databases (ACM digital library and IEEE…

Multi-layer intrusion detection system with ExtraTrees feature selection, extreme learning machine ensemble, and softmax aggregation

2019

Abstract Recent advances in intrusion detection systems based on machine learning have indeed outperformed other techniques, but struggle with detecting multiple classes of attacks with high accuracy. We propose a method that works in three stages. First, the ExtraTrees classifier is used to select relevant features for each type of attack individually for each (ELM). Then, an ensemble of ELMs is used to detect each type of attack separately. Finally, the results of all ELMs are combined using a softmax layer to refine the results and increase the accuracy further. The intuition behind our system is that multi-class classification is quite difficult compared to binary classification. So, we…