Towards Proactive Defense against Cyber Cognitive Attacks

Cyber cognitive attacks leverage disruptive innovations DIs to exploit psychological biases and manipulate decision-making processes. Emerging technologies, such as AI-driven disinformation and synthetic media, have accelerated the scale and sophistication of these threats. Prior studies primaril...

EUVD-2020-22731

Malware in sbrugna...

EUVD-2020-6828

Malware in sbrugna...

EUVD-2018-14579

Malware in sbrugna...

The vulnerability of the PostgreSQL pgAgent task scheduler, related to forecasting deficiencies, allows a hacker to trigger a service failure.

The vulnerability of the PostgreSQL pgAgent task scheduler is related to deficiencies in forecasting. Exploiting this vulnerability allows a perpetrator to trigger a service failure...

KillChainGraph: ML Framework for Predicting and Mapping ATT&CK Techniques

The escalating complexity and volume of cyberattacks demand proactive detection strategies that go beyond traditional rule-based systems. This paper presents a phase-aware, multi-model machine learning framework that emulates adversarial behavior across the seven phases of the Cyber Kill Chain...

Drone Detection with Event Cameras

The diffusion of drones presents significant security and safety challenges. Traditional surveillance systems, particularly conventional frame-based cameras, struggle to reliably detect these targets due to their small size, high agility, and the resulting motion blur and poor performance in...

Smart Buildings Energy Consumption Forecasting Using Adaptive Evolutionary Ensemble Learning Models

Smart buildings are gaining popularity because they can enhance energy efficiency, lower costs, improve security, and provide a more comfortable and convenient environment for building occupants. A considerable portion of the global energy supply is consumed in the building sector and plays a...

Automated Energy Billing with Blockchain and the Prophet Forecasting Model: a Holistic Approach

This paper presents a comprehensive approach to automated energy billing that leverages IoT-based smart meters, blockchain technology, and the Prophet time series forecasting model. The proposed system facilitates real-time power consumption monitoring via Wi-Fi-enabled ESP32 modules and a mobile...

Trojan Horse Hunt in Time Series Forecasting for Space Operations

This competition hosted on Kaggle https://www.kaggle.com/competitions/trojan-horse-hunt-in-space is the first part of a series of follow-up competitions and hackathons related to the "Assurance for Space Domain AI Applications" project funded by the European Space Agency...

CVE-2020-14692

Vulnerability in the Oracle Financial Services Loan Loss Forecasting and Provisioning product of Oracle Financial Services Applications component: User Interface. Supported versions that are affected are 8.0.6-8.0.8. Easily exploitable vulnerability allows low privileged attacker with network...

The Ephemeral Threat: Assessing the Security of Algorithmic Trading Systems Powered by Deep Learning

We study the security of stock price forecasting using Deep Learning DL in computational finance. Despite abundant prior research on the vulnerability of DL to adversarial perturbations, such work has hitherto hardly addressed practical adversarial threat models in the context of DL-powered...

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting

Digital twins DTs are improving water distribution systems by using real-time data, analytics, and prediction models to optimize operations. This paper presents a DT platform designed for a Spanish water supply network, utilizing Long Short-Term Memory LSTM networks to predict water consumption...

Adversarial Observations in Weather Forecasting

AI-based systems, such as Google's GenCast, have recently redefined the state of the art in weather forecasting, offering more accurate and timely predictions of both everyday weather and extreme events. While these systems are on the verge of replacing traditional meteorological methods, they al...

Leveraging Functional Encryption and Deep Learning for Privacy-Preserving Traffic Forecasting

Over the past few years, traffic congestion has continuously plagued the nation's transportation system creating several negative impacts including longer travel times, increased pollution rates, and higher collision risks. To overcome these challenges, Intelligent Transportation Systems ITS aim ...

CVE-2020-2938

Vulnerability in the Oracle Financial Services Loan Loss Forecasting and Provisioning product of Oracle Financial Services Applications component: User Interface. Supported versions that are affected are 8.0.6 - 8.0.8. Easily exploitable vulnerability allows low privileged attacker with network...

Microsoft Azure Machine Learning Forecasting Toolkit azuremlftkrelease Uncontrolled Search Path Element Remote Code Execution Vulnerability

This vulnerability allows remote attackers to execute arbitrary code on affected installations of Forecasting Toolkit for Microsoft Azure. Authentication is not required to exploit this vulnerability. The specific flaw exists within the installation of Forecasting Toolkit. When installed from the...

Anomaly Detection at Scale Using SQL and Facebook’s Prophet Forecasting Algorithm

Anomaly detection is a very important task. At Imperva we use it for threat hunting, risk analysis, risk mitigation, trends detection and more. In a previous post we showed how it can be done in a simple method by SQL. This time we wanted to use Prophet, which is an algorithm for forecasting time...

CVE-2020-14692

Vulnerability in the Oracle Financial Services Loan Loss Forecasting and Provisioning product of Oracle Financial Services Applications component: User Interface. Supported versions that are affected are 8.0.6-8.0.8. Easily exploitable vulnerability allows low privileged attacker with network...

CVE-2020-14692

Vulnerability in the Oracle Financial Services Loan Loss Forecasting and Provisioning product of Oracle Financial Services Applications component: User Interface. Supported versions that are affected are 8.0.6-8.0.8. Easily exploitable vulnerability allows low privileged attacker with network...