Domain Adaptation for Image Classification of Defects in Semiconductor Manufacturing

In the semiconductor sector, due to high demand but also strong and increasing competition, time to market and quality are key factors in securing significant market share in various application areas. Thanks to the success of deep learning methods in recent years in the computer vision domain,...

Where AI Provides Value

If you've worried that AI might take your job, deprive you of your livelihood, or maybe even replace your role in society, it probably feels good to see the latest AI tools fail spectacularly. If AI recommends glue as a pizza topping, then you're safe for another day. But the fact remains that AI...

Think Twice Before Adaptation: Improving Adaptability of DeepFake Detection Via Online Test-Time Adaptation

Whitepaper called Think Twice Before Adaptation: Improving Adaptability Of DeepFake Detection Via Online Test-Time Adaptation...

Striking Back at Cobalt: Using Network Traffic Metadata to Detect Cobalt Strike Masquerading Command and Control Channels

Off-the-shelf software for Command and Control is often used by attackers and legitimate pentesters looking for discretion. Among other functionalities, these tools facilitate the customization of their network traffic so it can mimic popular websites, thereby increasing their secrecy. Cobalt...

OS Command Exec, Unix Command Shell, Bind TCP (via Lua)

Execute an OS command from PHP. Listen for a connection and spawn a command shell via Lua Module Options msf use payload/php/unix/cmd/bindlua msf payloadbindlua show actions ...actions... msf payloadbindlua set ACTION msf payloadbindlua show options ...show and set options... msf payloadbindlua r...

Adapting under Fire: Multi-Agent Reinforcement Learning for Adversarial Drift in Network Security

Evolving attacks are a critical challenge for the long-term success of Network Intrusion Detection Systems NIDS. The rise of these changing patterns has exposed the limitations of traditional network security methods. While signature-based methods are used to detect different types of attacks, th...

FedShield-LLM: a Secure and Scalable Federated Fine-Tuned Large Language Model

Federated Learning FL offers a decentralized framework for training and fine-tuning Large Language Models LLMs by leveraging computational resources across organizations while keeping sensitive data on local devices. It addresses privacy and security concerns while navigating challenges associate...

OpenCCA: an Open Framework to Enable Arm CCA Research

Confidential computing has gained traction across major architectures with Intel TDX, AMD SEV-SNP, and Arm CCA. Unlike TDX and SEV-SNP, a key challenge in researching Arm CCA is the absence of hardware support, forcing researchers to develop ad-hoc performance prototypes on non-CCA Arm boards. Th...

Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification

Purpose: This study proposes a framework for fine-tuning large language models LLMs with differential privacy DP to perform multi-abnormality classification on radiology report text. By injecting calibrated noise during fine-tuning, the framework seeks to mitigate the privacy risks associated wit...

Privacy-Preserving Prompt Personalization in Federated Learning for Multimodal Large Language Models

Prompt learning is a crucial technique for adapting pre-trained multimodal language models MLLMs to user tasks. Federated prompt personalization FPP is further developed to address data heterogeneity and local overfitting, however, it exposes personalized prompts - valuable intellectual assets - ...

SHE-LoRA: Selective Homomorphic Encryption for Federated Tuning with Heterogeneous LoRA

Federated fine-tuning of large language models LLMs is critical for improving their performance in handling domain-specific tasks. However, prior work has shown that clients' private data can actually be recovered via gradient inversion attacks. Existing privacy preservation techniques against su...

Dynamic Encryption-Based Cloud Security Model Using Facial Image and Password-Based Key Generation for Multimedia Data

In this cloud-dependent era, various security techniques, such as encryption, steganography, and hybrid approaches, have been utilized in cloud computing to enhance security, maintain enormous storage capacity, and provide ease of access. However, the absence of data type-specific encryption and...

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?

Low rank adaptation LoRA has emerged as a prominent technique for fine-tuning large language models LLMs thanks to its superb efficiency gains over previous methods. While extensive studies have examined the performance and structural properties of LoRA, its behavior upon training-time attacks...

kernel: Bluetooth: L2CAP: Fix div-by-zero in l2cap_le_flowctl_init()

in linux kernel bluetooth L2CAP, l2capleflowctlinit can cause both div-by-zero and an integer overflow since hdev-lemtu may not fall in the valid range...

Private LoRA Fine-Tuning of Open-Source LLMs with Homomorphic Encryption

Preserving data confidentiality during the fine-tuning of open-source Large Language Models LLMs is crucial for sensitive applications. This work introduces an interactive protocol adapting the Low-Rank Adaptation LoRA technique for private fine-tuning. Homomorphic Encryption HE protects the...

Self-Supervised Transformer-Based Contrastive Learning for Intrusion Detection Systems

As the digital landscape becomes more interconnected, the frequency and severity of zero-day attacks, have significantly increased, leading to an urgent need for innovative Intrusion Detection Systems IDS. Machine Learning-based IDS that learn from the network traffic characteristics and can...

Notes on Univariate Sumcheck

These notes describe an adaptation of the multivariate sumcheck protocol to univariate polynomials interpolated over roots of unity...

DeeCLIP: a Robust and Generalizable Transformer-Based Framework for Detecting AI-Generated Images

This paper introduces DeeCLIP, a novel framework for detecting AI-generated images using CLIP-ViT and fusion learning. Despite significant advancements in generative models capable of creating highly photorealistic images, existing detection methods often struggle to generalize across different...

SOLIDO: a Robust Watermarking Method for Speech Synthesis Via Low-Rank Adaptation

Whitepaper called SOLIDO: A Robust Watermarking Method For Speech Synthesis Via Low-Rank Adaptation...

MULTI-LF: a Unified Continuous Learning Framework for Real-Time DDoS Detection in Multi-Environment Networks

Detecting Distributed Denial of Service DDoS attacks in Multi-Environment M-En networks presents significant challenges due to diverse malicious traffic patterns and the evolving nature of cyber threats. Existing AI-based detection systems struggle to adapt to new attack strategies and lack...