CVE-2013-1167

Cisco IOS XE 3.2 through 3.4 before 3.4.2S, and 3.5, on 1000 series Aggregation Services Routers ASR, when bridge domain interface BDI is enabled, allows remote attackers to cause a denial of service card reload via packets that are not properly handled during the processing of encapsulation, aka...

CVE-2013-2779

Cisco IOS XE 3.4 before 3.4.5S, and 3.5 through 3.7 before 3.7.1S, on 1000 series Aggregation Services Routers ASR does not properly implement the Cisco Multicast Leaf Recycle Elimination MLRE feature, which allows remote attackers to cause a denial of service card reload via fragmented IPv6 MVPN...

Privacy-Aware Cyberterrorism Network Analysis Using Graph Neural Networks and Federated Learning

Cyberterrorism poses a formidable threat to digital infrastructures, with increasing reliance on encrypted, decentralized platforms that obscure threat actor activity. To address the challenge of analyzing such adversarial networks while preserving the privacy of distributed intelligence data, we...

FedGraM: Defending against Untargeted Attacks in Federated Learning Via Embedding Gram Matrix

Federated Learning FL enables geographically distributed clients to collaboratively train machine learning models by sharing only their local models, ensuring data privacy. However, FL is vulnerable to untargeted attacks that aim to degrade the global model's performance on the underlying data...

SVAFD: a Secure and Verifiable Co-Aggregation Protocol for Federated Distillation

Secure Aggregation SA is an indispensable component of Federated Learning FL that concentrates on privacy preservation while allowing for robust aggregation. However, most SA designs rely heavily on the unrealistic assumption of homogeneous model architectures. Federated Distillation FD, which...

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...

Coded Robust Aggregation for Distributed Learning under Byzantine Attacks

In this paper, we investigate the problem of distributed learning DL in the presence of Byzantine attacks. For this problem, various robust bounded aggregation RBA rules have been proposed at the central server to mitigate the impact of Byzantine attacks. However, current DL methods apply RBA rul...

FL-PLAS: Federated Learning with Partial Layer Aggregation for Backdoor Defense against High-Ratio Malicious Clients

Federated learning FL is gaining increasing attention as an emerging collaborative machine learning approach, particularly in the context of large-scale computing and data systems. However, the fundamental algorithm of FL, Federated Averaging FedAvg, is susceptible to backdoor attacks. Although...

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...

Efficient Full-Stack Private Federated Deep Learning with Post-Quantum Security

Federated learning FL enables collaborative model training while preserving user data privacy by keeping data local. Despite these advantages, FL remains vulnerable to privacy attacks on user updates and model parameters during training and deployment. Secure aggregation protocols have been...

com.airbus-cyber-security.graylog:graylog-plugin-aggregation-count (>=1.1.0 <=4.1.1), com.airbus-cyber-security.graylog:graylog-plugin-alert-wizard (>=1.0.0 <=5.2.1) +12 more potentially affected by CVE-2025-46827 via org.graylog2:graylog2-server (>=1.0.0-beta.3 <=6.0.13)

org.graylog2:graylog2-server MAVEN version =1.0.0-beta.3, =1.1.0, =1.0.0, =1.1.0, =1.0.0, =1.0.0, =1.0.0, =1.0.1, =2.2.0, =1.1.0, =2.2.0, =2.2.0, =1.0.3, =1.0.0, =1.2.0, =1.3.4 Source cves: CVE-2025-46827 Source advisory: OSV:GHSA-76VF-MPMX-777J...

FedRE: Robust and Effective Federated Learning with Privacy Preference

Despite Federated Learning FL employing gradient aggregation at the server for distributed training to prevent the privacy leakage of raw data, private information can still be divulged through the analysis of uploaded gradients from clients. Substantial efforts have been made to integrate local...

DEBIAN-CVE-2023-53134

In the Linux kernel, the following vulnerability has been resolved: bnxten: Avoid order-5 memory allocation for TPA data The driver needs to keep track of all the possible concurrent TPA GRO/LRO completions on the aggregation ring. On P5 chips, the maximum number of concurrent TPA is 256 and the...

CVE-2023-53134

In the Linux kernel, the following vulnerability has been resolved: bnxten: Avoid order-5 memory allocation for TPA data The driver needs to keep track of all the possible concurrent TPA GRO/LRO completions on the aggregation ring. On P5 chips, the maximum number of concurrent TPA is 256 and the...

UBUNTU-CVE-2023-53134

In the Linux kernel, the following vulnerability has been resolved: bnxten: Avoid order-5 memory allocation for TPA data The driver needs to keep track of all the possible concurrent TPA GRO/LRO completions on the aggregation ring. On P5 chips, the maximum number of concurrent TPA is 256 and the...

Graph Privacy: a Heterogeneous Federated GNN for Trans-Border Financial Data Circulation

The sharing of external data has become a strong demand of financial institutions, but the privacy issue has led to the difficulty of interconnecting different platforms and the low degree of data openness. To effectively solve the privacy problem of financial data in trans-border flow and sharin...

FLARE: Feature-Based Lightweight Aggregation for Robust Evaluation of IoT Intrusion Detection

The proliferation of Internet of Things IoT devices has expanded the attack surface, necessitating efficient intrusion detection systems IDSs for network protection. This paper presents FLARE, a feature-based lightweight aggregation for robust evaluation of IoT intrusion detection to address the...

FLSSM: a Federated Learning Storage Security Model with Homomorphic Encryption

Federated learning based on homomorphic encryption has received widespread attention due to its high security and enhanced protection of user data privacy. However, the characteristics of encrypted computation lead to three challenging problems: "computation-efficiency", "attack-tracing" and...

SUSE CVE-2025-21970

In the Linux kernel, the following vulnerability has been resolved: net/mlx5: Bridge, fix the crash caused by LAG state check When removing LAG device from bridge, NETDEVCHANGEUPPER event is triggered. Driver finds the lower devices PFs to flush all the offloaded entries. And mlx5lagissharedfdb i...