EditLord: Learning Code Transformation Rules for Code Editing

Code editing is a foundational task in software development, where its effectiveness depends on whether it introduces desired code property changes without changing the original code's intended functionality. Existing approaches often formulate code editing as an implicit end-to-end task, omittin...

PROVSYN: Synthesizing Provenance Graphs for Data Augmentation in Intrusion Detection Systems

Provenance graph analysis plays a vital role in intrusion detection, particularly against Advanced Persistent Threats APTs, by exposing complex attack patterns. While recent systems combine graph neural networks GNNs with natural language processing NLP to capture structural and semantic features...

Securing Traffic Sign Recognition Systems in Autonomous Vehicles

Deep Neural Networks DNNs are widely used for traffic sign recognition because they can automatically extract high-level features from images. These DNNs are trained on large-scale datasets obtained from unknown sources. Therefore, it is important to ensure that the models remain secure and are n...

MISLEADER: Defending against Model Extraction with Ensembles of Distilled Models

Model extraction attacks aim to replicate the functionality of a black-box model through query access, threatening the intellectual property IP of machine-learning-as-a-service MLaaS providers. Defending against such attacks is challenging, as it must balance efficiency, robustness, and utility...

GSDFuse: Capturing Cognitive Inconsistencies from Multi-Dimensional Weak Signals in Social Media Steganalysis

The ubiquity of social media platforms facilitates malicious linguistic steganography, posing significant security risks. Steganalysis is profoundly hindered by the challenge of identifying subtle cognitive inconsistencies arising from textual fragmentation and complex dialogue structures, and th...

Is Artificial Intelligence Generated Image Detection a Solved Problem?

The rapid advancement of generative models, such as GANs and Diffusion models, has enabled the creation of highly realistic synthetic images, raising serious concerns about misinformation, deepfakes, and copyright infringement. Although numerous Artificial Intelligence Generated Image AIGI...

Facial Recognition Leveraging Generative Adversarial Networks

Face recognition performance based on deep learning heavily relies on large-scale training data, which is often difficult to acquire in practical applications. To address this challenge, this paper proposes a GAN-based data augmentation method with three key contributions: 1 a residual-embedded...

DP-TRAE: a Dual-Phase Merging Transferable Reversible Adversarial Example for Image Privacy Protection

In the field of digital security, Reversible Adversarial Examples RAE combine adversarial attacks with reversible data hiding techniques to effectively protect sensitive data and prevent unauthorized analysis by malicious Deep Neural Networks DNNs. However, existing RAE techniques primarily focus...

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things

In intelligent industry, autonomous driving and other environments, the Internet of Things IoT highly integrated with robotic to form the Internet of Robotic Things IoRT. However, network intrusion to IoRT can lead to data leakage, service interruption in IoRT and even physical damage by...

Mitigating the Structural Bias in Graph Adversarial Defenses

In recent years, graph neural networks GNNs have shown great potential in addressing various graph structure-related downstream tasks. However, recent studies have found that current GNNs are susceptible to malicious adversarial attacks. Given the inevitable presence of adversarial attacks in the...

A Study on Mixup-Inspired Augmentation Methods for Software Vulnerability Detection

Various deep learning DL methods have recently been utilized to detect software vulnerabilities. Real-world software vulnerability datasets are rare and hard to acquire, as there is no simple metric for classifying vulnerability. Such datasets are heavily imbalanced, and none of the current...

Malicious code in ml-interactive-data-augmentation (npm)

--- -= Per source details. Do not edit below this line.=- Source: ghsa-malware e20810134f19a11553a575cd601700601cf374b00626760c86d6c3905cb0113b Any computer that has this package installed or running should be considered fully compromised. All secrets and keys stored on that computer should be...

[SECURITY] Fedora 40 Update: abseil-cpp-20240116.2-1.fc40

Abseil is an open-source collection of C++ library code designed to augment the C++ standard library. The Abseil library code is collected from Google's own C++ code base, has been extensively tested and used in production, and is the same code we depend on in our daily coding lives. In some case...

Strategic IT Staff Augmentation: A Roadmap for C-Level Executives

By Owais Sultan Finding the Perfect IT Staff Augmentation and Staffing Services Company for Your Needs. This is a post from HackRead.com Read the original post: Strategic IT Staff Augmentation: A Roadmap for C-Level Executives...

Airbus AoA – Angle of Attack sensor issue

I read a lot of air incident investigation reports. The aviation industry is a shining example of sharing and learning, resulting in increased safety. I wish that the cyber industry on the ground could find a way to effectively share similar experiences and learnings. Anyway, one report caught my...

6 Reasons Managed Detection and Response Is Hitting Its Stride

Cyber threats have risen to the 1 concern of CEOs, which means security teams — in the hot seat for years — are really feeling it now. Files and data live in the cloud. Work is hybrid or remote. There’s turmoil around the world. Cyberattacks are not just a distant boogieman – they’re here and...

Structured threat hunting: One way Microsoft Threat Experts prioritizes customer defense

Todays threat landscape is incredibly fast-paced. New campaigns surface all the time, and the amount of damage that they can cause is not always immediately apparent. Security operations centers SOCs must be equipped with the tools and insight to identify and resolve potentially high-impact threa...

Authentication flaw

The authentication algorithm in Abbott Laboratories pacemakers manufactured prior to Aug 28, 2017, which involves an authentication key and time stamp, can be compromised or bypassed, which may allow a nearby attacker to issue unauthorized commands to the pacemaker via RF communications. CVSS v3...

[SECURITY] Fedora 22 Update: drupal7-views_bulk_operations-3.3-1.fc22

This module augments Views by allowing bulk operations to be executed on the displayed rows. It does so by showing a checkbox in front of each node, and adding a select box containing operations that can be applied. Drupal Core or Rules actions can be used. This package provides the following...