U.S. House Bans WhatsApp on Official Devices Over Security and Data Protection Issues

The U.S. House of Representatives has formally banned congressional staff members from using WhatsApp on government-issued devices, citing security concerns. The development was first reported by Axios. The decision, according to the House Chief Administrative Officer CAO, was motivated by worrie...

The Impact of the Russia-Ukraine Conflict on the Cloud Computing Risk Landscape

The Russian invasion of Ukraine has fundamentally altered the information technology IT risk landscape, particularly in cloud computing environments. This paper examines how this geopolitical conflict has accelerated data sovereignty concerns, transformed cybersecurity paradigms, and reshaped clo...

Can One Safety Loop Guard Them All? Agentic Guard Rails for Federated Computing

We propose Guardian-FC, a novel two-layer framework for privacy preserving federated computing that unifies safety enforcement across diverse privacy preserving mechanisms, including cryptographic back-ends like fully homomorphic encryption FHE and multiparty computation MPC, as well as statistic...

ROS-20250624-15

Vulnerability in the Javascript Object Signing and Encryption Go JOSE standards set implementation is related to uncontrolled consumption of internal resources properly when analyzing JWS and JWE input data. Exploitation of the vulnerability could allow an attacker acting remotely to cause a deni...

Secure Multi-Key Homomorphic Encryption with Application to Privacy-Preserving Federated Learning

Whitepaper called Secure Multi-Key Homomorphic Encryption With Application To Privacy-Preserving Federated Learning...

CVE-2025-49824

conda-smithy is a tool for combining a conda recipe with configurations to build using freely hosted CI services into a single repository. Prior to version 3.47.1, the travisencryptbinstartoken implementation in the conda-smithy package has been identified as vulnerable to an Oracle Padding Attac...

CVE-2025-49216

An authentication bypass vulnerability in the Trend Micro Endpoint Encryption PolicyServer could allow an attacker to access key methods as an admin user and modify product configurations on affected installations...

CVE-2025-49215

A post-auth SQL injection vulnerability in the Trend Micro Endpoint Encryption PolicyServer could allow an attacker to escalate privileges on affected installations. Please note: an attacker must first obtain the ability to execute low-privileged code on the target system to exploit this...

CVE-2025-49218

A post-auth SQL injection vulnerability in the Trend Micro Endpoint Encryption PolicyServer could allow an attacker to escalate privileges on affected installations. This is similar to, but not identical to CVE-2025-49215. Please note: an attacker must first obtain the ability to execute...

CVE-2025-49211

A SQL injection vulnerability in the Trend Micro Endpoint Encryption PolicyServer could allow an attacker to escalate privileges on affected installations. Please note: an attacker must first obtain the ability to execute low-privileged code on the target system to exploit this vulnerability...

CVE-2025-49213

An insecure deserialization operation in the Trend Micro Endpoint Encryption PolicyServer could lead to a pre-authentication remote code execution on affected installations. Note that this vulnerability is similar to CVE-2025-49212 but is in a different method...

CVE-2025-49217

An insecure deserialization operation in the Trend Micro Endpoint Encryption PolicyServer could lead to a pre-authentication remote code execution on affected installations. Note that this vulnerability is similar to CVE-2025-49213 but is in a different method...

Advisory ROSA-SA-2025-2898

Software: openssl 1.1.1k OS: ROSA Virtualization 3.0 packageevrstring: openssl-1.1.1k-12.0.1.rv30 CVE-ID: CVE-2019-1547 BDU-ID: 2019-04084 CVE-Crit: MEDIUM CVE-DESC.: A vulnerability in the ecerr.c and eclib.c functions of the OpenSSL library is related to the lack of data encryption measures...

Accurate BGV Parameters Selection: Accounting for Secret and Public Key Dependencies in Average-Case Analysis

The Brakerski-Gentry-Vaikuntanathan BGV scheme is one of the most significant fully homomorphic encryption FHE schemes. It belongs to a class of FHE schemes whose security is based on the presumed intractability of the Learning with Errors LWE problem and its ring variant RLWE. Such schemes deal...

HE-LRM: Encrypted Deep Learning Recommendation Models Using Fully Homomorphic Encryption

Fully Homomorphic Encryption FHE is an encryption scheme that not only encrypts data but also allows for computations to be applied directly on the encrypted data. While computationally expensive, FHE can enable privacy-preserving neural inference in the client-server setting: a client encrypts...

Versatile and Fast Location-Based Private Information Retrieval with Fully Homomorphic Encryption over the Torus

Location-based services often require users to share sensitive locational data, raising privacy concerns due to potential misuse or exploitation by untrusted servers. In response, we present VeLoPIR, a versatile location-based private information retrieval PIR system designed to preserve user...

Cut Tracing with E-Graphs for Boolean FHE Circuit Synthesis

Fully Homomorphic Encryption FHE is a promising privacy-preserving technology enabling secure computation over encrypted data. A major limitation of current FHE schemes is their high runtime overhead. As a result, automatic optimization of circuits describing FHE computation has garnered...

Leveraging Photonic Interconnects for Scalable and Efficient Fully Homomorphic Encryption

Fully Homomorphic Encryption FHE facilitates secure computations on encrypted data but imposes significant demands on memory bandwidth and computational power. While current FHE accelerators focus on optimizing computation, they often face bandwidth limitations that result in performance...

Privacy-Preserving Federated Learning against Malicious Clients Based on Verifiable Functional Encryption

Federated learning is a promising distributed learning paradigm that enables collaborative model training without exposing local client data, thereby protect data privacy. However, it also brings new threats and challenges. The advancement of model inversion attacks has rendered the plaintext...

Bidirectional Biometric Authentication Using Transciphering and (T)FHE

Biometric authentication systems pose privacy risks, as leaked templates such as iris or fingerprints can lead to security breaches. Fully Homomorphic Encryption FHE enables secure encrypted evaluation, but its deployment is hindered by large ciphertexts, high key overhead, and limited trust...