Network Packet Processing and Optimization
67 papers on this topic
MEMHD: Memory-Efficient Multi-Centroid Hyperdimensional Computing for Fully-Utilized In-Memory Computing Architectures
The implementation of Hyperdimensional Computing (HDC) on In-Memory Computing (IMC) architectures faces significant challenges due to the mismatch between highdimensional vectors and IMC array...
Advancing DDoS Attack Detection: A Synergistic Approach Using Deep Residual Neural Networks and Synthetic Oversampling
Distributed Denial of Service (DDoS) attacks pose a significant threat to the stability and reliability of online systems. Effective and early detection of such attacks is pivotal for safeguarding...
Energy-Efficient Cryogenic Ternary Content Addressable Memory using Ferroelectric SQUID
Ternary content addressable memories (TCAMs) are useful for certain computing tasks since they allow us to compare a search query with a whole dataset stored in the memory array. They can also...
MULTI-LF: A Continuous Learning Framework for Real-Time Malicious Traffic Detection in Multi-Environment Networks
Multi-environment (M-En) networks integrate diverse traffic sources, including Internet of Things (IoT) and traditional computing systems, creating complex and evolving conditions for malicious...
MFTIQ: Multi-Flow Tracker with Independent Matching Quality Estimation
In this work, we present MFTIQ, a novel dense long-term tracking model that advances the Multi-Flow Tracker (MFT) framework to address challenges in point-level visual tracking in video sequences....
Natural Language Interface for Firewall Configuration
This paper presents the design and prototype implementation of a natural language interface for configuring enterprise firewalls. The framework allows administrators to express access control...
Enhancing Biologically Inspired Hierarchical Temporal Memory with Hardware-Accelerated Reflex Memory
The rapid expansion of the Internet of Things (IoT) generates zettabytes of data that demand efficient unsupervised learning systems. Hierarchical Temporal Memory (HTM), a third-generation...
PiDRAM: A Holistic End-to-end FPGA-based Framework for Processing-in-DRAM
Processing-using-memory (PuM) techniques leverage the analog operation of memory cells to perform computation. Several recent works have demonstrated PuM techniques in off-the-shelf DRAM devices....
Intrusion Detection based on Federated Learning: a systematic review
The evolution of cybersecurity is undoubtedly associated and intertwined with the development and improvement of artificial intelligence (AI). As a key tool for realizing more cybersecure...
Multi-Strided Access Patterns to Boost Hardware Prefetching
Important memory-bound kernels, such as linear algebra, convolutions, and stencils, rely on SIMD instructions as well as optimizations targeting improved vectorized data traversal and data re-use...
ByteStack-ID: Integrated Stacked Model Leveraging Payload Byte Frequency for Grayscale Image-based Network Intrusion Detection
In the ever-evolving realm of network security, the swift and accurate identification of diverse attack classes within network traffic is of paramount importance. This paper introduces...
A method based on hierarchical spatiotemporal features for trojan traffic detection
Trojans are one of the most threatening network attacks currently. HTTP-based Trojan, in particular, accounts for a considerable proportion of them. Moreover, as the network environment becomes...
Rust Barefoot Runtime (RBFRT): Fast Runtime Control for the Intel Tofino
Data plane programming enables the programmability of network devices with domain-specific programming languages, like P4. One commonly used P4-programmable hardware target is the Intel Tofino...
Intrusion Detection: A Deep Learning Approach
Network intrusions are a significant problem in all industries today. A critical part of the solution is being able to effectively detect intrusions. With recent advances in artificial...
DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection
Machine Learning (ML) approaches have been used to enhance the detection capabilities of Network Intrusion Detection Systems (NIDSs). Recent work has achieved near-perfect performance by following...
Autoencoder-based Unsupervised Intrusion Detection using Multi-Scale Convolutional Recurrent Networks
The massive growth of network traffic data leads to a large volume of datasets. Labeling these datasets for identifying intrusion attacks is very laborious and error-prone. Furthermore, network...
TSNZeek: An Open-source Intrusion Detection System for IEEE 802.1 Time-sensitive Networking
IEEE 802.1 Time-sensitive Networking~(TSN) standards are envisioned to replace legacy network protocols in critical domains to ensure reliable and deterministic communication over off-the-shelf...
Sliding Window Sum Algorithms for Deep Neural Networks
Sliding window sums are widely used for string indexing, hashing and time series analysis. We have developed a family of the generic vectorized sliding sum algorithms that provide speedup of...