CVE-2019-17063

In Snowtide PDFxStream before 3.7.1 for Java, a crafted PDF file can trigger an extremely long running computation because of page-tree mishandling...

CVE-2013-5750

The login form in the FriendsOfSymfony FOSUserBundle bundle before 1.3.3 for Symfony allows remote attackers to cause a denial of service CPU consumption via a long password that triggers an expensive hash computation, as demonstrated by a PBKDF2 computation...

A Survey on Secure Machine Learning

In this survey, we will explore the interaction between secure multiparty computation and the area of machine learning. Recent advances in secure multiparty computation MPC have significantly improved its applicability in the realm of machine learning ML, offering robust solutions for...

Covert Attacks on Machine Learning Training in Passively Secure MPC

Secure multiparty computation MPC allows data owners to train machine learning models on combined data while keeping the underlying training data private. The MPC threat model either considers an adversary who passively corrupts some parties without affecting their overall behavior, or an adversa...

On the Day They Experience: Awakening Self-Sovereign Experiential AI Agents

Drawing on Andrew Parker's "Light Switch" theory-which posits that the emergence of vision ignited a Cambrian explosion of life by driving the evolution of hard parts necessary for survival and fueling an evolutionary arms race between predators and prey-this essay speculates on an analogous...

Linux kernel 安全漏洞

Linux kernel is the kernel used by Linux, the open source operating system of the Linux Foundation in the United States. A security vulnerability exists in the Linux kernel that stems from a DIVROUNDUP integer overflow that could lead to a computation error...

Implementation of Shor Algorithm: Factoring a 4096-Bit Integer under Specific Constraints

In recent years, advancements in quantum chip technology, such as Willow, have contributed to reducing quantum computation error rates, potentially accelerating the practical adoption of quantum computing. As a result, the design of quantum algorithms suitable for real-world applications has beco...

Private Transformer Inference in MLaaS: a Survey

Transformer models have revolutionized AI, powering applications like content generation and sentiment analysis. However, their deployment in Machine Learning as a Service MLaaS raises significant privacy concerns, primarily due to the centralized processing of sensitive user data. Private...

Privacy-Preserving Runtime Verification

Runtime verification offers scalable solutions to improve the safety and reliability of systems. However, systems that require verification or monitoring by a third party to ensure compliance with a specification might contain sensitive information, causing privacy concerns when usual runtime...

SAFE-SiP: Secure Authentication Framework for System-In-Package Using Multi-Party Computation

The emergence of chiplet-based heterogeneous integration is transforming the semiconductor, AI, and high-performance computing industries by enabling modular designs and improved scalability. However, assembling chiplets from multiple vendors after fabrication introduces a complex supply chain th...

Privacy-Preserving Analytics for Smart Meter (AMI) Data: a Hybrid Approach to Comply with CPUC Privacy Regulations

Advanced Metering Infrastructure AMI data from smart electric and gas meters enables valuable insights for utilities and consumers, but also raises significant privacy concerns. In California, regulatory decisions CPUC D.11-07-056 and D.11-08-045 mandate strict privacy protections for customer...

GDNTT: an Area-Efficient Parallel NTT Accelerator Using Glitch-Driven Near-Memory Computing and Reconfigurable 10T SRAM

With the rapid advancement of quantum computing technology, post-quantum cryptography PQC has emerged as a pivotal direction for next-generation encryption standards. Among these, lattice-based cryptographic schemes rely heavily on the fast Number Theoretic Transform NTT over polynomial rings,...

Standing Firm in 5G: a Single-Round, Dropout-Resilient Secure Aggregation for Federated Learning

Federated learning FL is well-suited to 5G networks, where many mobile devices generate sensitive edge data. Secure aggregation protocols enhance privacy in FL by ensuring that individual user updates reveal no information about the underlying client data. However, the dynamic and large-scale...

Measuring Security in 5G and Future Networks

In today's increasingly interconnected and fast-paced digital ecosystem, mobile networks, such as 5G and future generations such as 6G, play a pivotal role and must be considered as critical infrastructures. Ensuring their security is paramount to safeguard both individual users and the industrie...

Privacy Challenges in Image Processing Applications

As image processing systems proliferate, privacy concerns intensify given the sensitive personal information contained in images. This paper examines privacy challenges in image processing and surveys emerging privacy-preserving techniques including differential privacy, secure multiparty...

EulerOS 2.0 SP12 : openssl (EulerOS-SA-2025-1431)

According to the versions of the openssl packages installed, the EulerOS installation on the remote host is affected by the following vulnerabilities : Issue summary: A timing side-channel which could potentially allow recovering the private key exists in the ECDSA signature computation. Impact...

NCSC Guidance on “Advanced Cryptography”

The UK's National Cyber Security Centre just released its white paper on "Advanced Cryptography," which it defines as "cryptographic techniques for processing encrypted data, providing enhanced functionality over and above that provided by traditional cryptography." It includes things like...

AI-Based Crypto Tokens: the Illusion of Decentralized AI?

The convergence of blockchain and artificial intelligence AI has led to the emergence of AI-based tokens, which are cryptographic assets designed to power decentralized AI platforms and services. This paper provides a comprehensive review of leading AI-token projects, examining their technical...

Federated One-Shot Learning with Data Privacy and Objective-Hiding

Privacy in federated learning is crucial, encompassing two key aspects: safeguarding the privacy of clients' data and maintaining the privacy of the federator's objective from the clients. While the first aspect has been extensively studied, the second has received much less attention. We present...

ScaloWork: Useful Proof-Of-Work with Distributed Pool Mining

Bitcoin blockchain uses hash-based Proof-of-Work PoW that prevents unwanted participants from hogging the network resources. Anyone entering the mining game has to prove that they have expended a specific amount of computational power. However, the most popular Bitcoin blockchain consumes 175.87...