skip to main content
Volume 27, Issue 4November 2024Current Issue
Editor:
  • Michael Waidner
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
ISSN:2471-2566
EISSN:2471-2574
Reflects downloads up to 10 Oct 2024Bibliometrics
Skip Table Of Content Section
research-article
Boost Your Immunity: VACCINE for Preventing a Novel Stealthy Slice Selection Attack in 5G and Beyond

G networks can offer network slices customized according to the demands of the services to enhance the quality of their users’ experience. The time for selecting an appropriate network slice to facilitate traffic flow between users and services by the ...

research-article
Open Access
ZPredict: ML-Based IPID Side-channel Measurements

Network reconnaissance and measurements play a central role in improving Internet security and are important for understanding the current deployments and trends. Such measurements often require coordination with the measured target. This limits the ...

research-article
SPArch: A Hardware-oriented Sketch-based Architecture for High-speed Network Flow Measurements

Network flow measurement is an integral part of modern high-speed applications for network security and data-stream processing. However, processing at line rate while maintaining the required data structure within the on-chip memory of the hardware ...

research-article
Open Access
Flexichain: Flexible Payment Channel Network to Defend Against Channel Exhaustion Attack

The payment channel network (PCN) is an effective off-chain scaling solution widely recognized for reducing operational costs on permissionless blockchains. However, it still faces challenges such as lack of flexibility, channel exhaustion, and poor ...

research-article
Open Access
Specifying and Verifying Information Flow Control in SELinux Configurations

Security Enhanced Linux (SELinux) is a security architecture for Linux implementing Mandatory Access Control. It has been used in numerous security-critical contexts ranging from servers to mobile devices. However, its application is challenging as ...

research-article
DELM: Deep Ensemble Learning Model for Anomaly Detection in Malicious Network Traffic-based Adaptive Feature Aggregation and Network Optimization

With the rapid advancements in internet technology, the complexity and sophistication of network traffic attacks are increasing, making it challenging for traditional anomaly detection systems to analyze and detect malicious network attacks. The ...

Subjects

Comments