Search results for "Exploit"
showing 10 items of 284 documents
AIOC2: A deep Q-learning approach to autonomic I/O congestion control in Lustre
2021
Abstract In high performance computing systems, I/O congestion is a common problem in large-scale distributed file systems. However, the current implementation mainly requires administrator to manually design low-level implementation and optimization, we proposes an adaptive I/O congestion control framework, named AIOC 2 , which can not only adaptively tune the I/O congestion control parameters, but also exploit the deep Q-learning method to start the training parameters and optimize the tuning for different types of workloads from the server and the client at the same time. AIOC 2 combines the feedback-based dynamic I/O congestion control and deep Q-learning parameter tuning technology to …
Infrared image processing and its application to forest fire surveillance
2007
This paper describes an scheme for automatic forest surveillance. A complete system for forest fire detection is firstly presented although we focus on infrared image processing. The proposed scheme based on infrared image processing performs early detection of any fire threat. With the aim of determining the presence or absence of fire, the proposed algorithms performs the fusion of different detectors which exploit different expected characteristics of a real fire, like persistence and increase. Theoretical results and practical simulations are presented to corroborate the control of the system related with probability of false alarm (PFA). Probability of detection (PD) dependence on sign…
New evidence for chunk-based models in word segmentation.
2014
International audience; : There is large evidence that infants are able to exploit statistical cues to discover the words of their language. However, how they proceed to do so is the object of enduring debates. The prevalent position is that words are extracted from the prior computation of statistics, in particular the transitional probabilities between syllables. As an alternative, chunk-based models posit that the sensitivity to statistics results from other processes, whereby many potential chunks are considered as candidate words, then selected as a function of their relevance. These two classes of models have proven to be difficult to dissociate. We propose here a procedure, which lea…
FISH: Face Intensity-Shape Histogram representation for automatic face splicing detection
2019
Abstract Tampered images spread nowadays over any visual media influencing our judgement in many aspects of our life. This is particularly critical for face splicing manipulations, where recognizable identities are put out of context. To contrast these activities on a large scale, automatic detectors are required. In this paper, we present a novel method for automatic face splicing detection, based on computer vision, that exploits inconsistencies in the lighting environment estimated from different faces in the scene. Differently from previous approaches, we do not rely on an ideal mathematical model of the lighting environment. Instead, our solution, built upon the concept of histogram-ba…
Countering Adversarial Inference Evasion Attacks Towards ML-Based Smart Lock in Cyber-Physical System Context
2021
Machine Learning (ML) has been taking significant evolutionary steps and provided sophisticated means in developing novel and smart, up-to-date applications. However, the development has also brought new types of hazards into the daylight that can have even destructive consequences required to be addressed. Evasion attacks are among the most utilized attacks that can be generated in adversarial settings during the system operation. In assumption, ML environment is benign, but in reality, perpetrators may exploit vulnerabilities to conduct these gradient-free or gradient-based malicious adversarial inference attacks towards cyber-physical systems (CPS), such as smart buildings. Evasion attac…
Eliciting Information on the Vulnerability Black Market from Interviews
2010
Threats to computing prompted by software vulnerabilities are abundant and costly for those affected. Adding to this problem is the emerging vulnerability black markets (VBMs), since they become places to trade malware and exploits. VBMs are discussed based on information derived from interviews with security researchers. The effort is enriched by further examination of documents surrounding the disclosure of four selected vulnerabilities cases. The result suggests that the VBMs is bifurcated into two distinct parts; the skilled-hacker and the script-kiddie VBMs with a possible link between them, where the latter become places to sell malware or exploit kits after the zero day vulnerability…
A System for Simultaneous People Tracking and Posture Recognition in the context of Human-Computer Interaction
2005
The paper deals with an artificial-vision based system for simultaneous people tracking and posture recognition In the context of human-computer Interaction. We adopt no particular assumptions on the movement of a person and on Its appearance, making the system suitable to several real-world applications. The system can be roughly subdivided Into two highly correlated phases: tracking and recognition. The tracking phase Is concerned with establishing coherent relations of the same subject between frames. We adopted the Condensation algorithm due to Its robustness In highly cluttered environments. The recognition phase adopts a modified elgenspace technique In order to classify between sever…
Trading with Asymmetric Volatility Spillovers
2007
: We study the profitability of trading strategies based on volatility spillovers between large and small firms. By using the Volatility Impulse-Response Function of Lin (1997) and its extensions, we detect that any volatility shock coming from small companies is important to large companies, but the reverse is only true for negative shocks coming from large firms. To exploit these asymmetric patterns in volatility, different trading rules are designed based on the inverse relationship existing between expected return and volatility. We find that most strategies generate excess after-transaction cost profits, especially after very bad news and very good news coming from large or small firm…
Corporate Social Responsibility and Sustainability of Local Community: A Case Study of the Transnational Project in China-Pakistan Economic Corridor
2019
While achieving great benefits, the Belt and Road Initiative (BRI) has triggered potential problems between the transnational projects and local communities in the participant countries. However, there is still a knowledge gap on how corporate social responsibility (CSR) is adopted, and how CSR affects the local community. Based on a context of China-Pakistan Economic Corridor (CPEC), this research exploits a combination of qualitative and quantitative methods to fill the gap. It finds that the CSR activities in the CPEC project are initiated by the long-term CSR initiative. Organized by the professional CSR foundation in an autonomous environment, the panoramic CSR activities are governed …
An Augmented Reality (AR) CAD System at Construction Sites
2011
Augmented Reality (AR) technologies allow computer-generated content to be superimposed over a live camera view of the real world. Although AR is still a very promising technology, currently only a few commercial applications for industrial purposes exploit the potential of adding contextual content to real scenarios. Most of AR applications are oriented to fields such as education or entertainment, where the requirements in terms of repeatability, fault tolerance, reliability and safety are low. Different visualization devices, tracking methods and interaction techniques are described in the literature, establishing a classification between Indoor and Outdoor AR systems. On the one hand, t…