Secure Ultra-Low Latency Data Paths: A Hybrid Architecture for High Speed Networking under Adversarial Conditions

The need to satisfy the line rate and deterministic latency requirements of next generation industrial networks is imperative for blistering 400G/800G Ethernet backbones, optical transport networks, and breaking new ground in 5G/6G infrastructures. Animals News: Other solutions limit attention towards detection accuracy or throughput separately without providing a discriminative systems-level architecture, leaving out bounded latency, scalable security as well as hardware-efficient adaptivity in an adversarial environment. We present a latency-constrained hardware-pipelined co-design framework, dubbed High Speed Secure Networking Architecture (HSSNA), capable of integrating probabilistic pre-filtering, adaptive lightweight cryptography, neural anomaly inference, and SDN-based routing into a single deterministic processing graph. In contrast to compositional security stacks, HSSNA defines the security-performance coupling as a constrained optimization problem that seeks to minimize the total processing delay without sacrificing the robustness of intrusion detection. Our contributions include (1) cross-layer security orchestration, which is embedded within the data path, (2) provable adversarial resilience guarantees, as a result of formally defined security properties, and (3) a parallel FPGA–GPU execution pipeline, which also removes sequential security bottlenecks. Through experiments conducted on a hybrid Mininet–NS3–FPGA/GPU testbed, we observe 60–77% lower latency, > 190 Gbps more throughput, and better robustness to real-time detection compared to conventional CPU-centric deployments. Our results prove HSSNA is systems-level re-architecture, high-speed secure networking, not a composition of prior art tools.

@article{Banga2026,
  title     = {Secure Ultra-Low Latency Data Paths: A Hybrid Architecture for High Speed Networking under Adversarial Conditions},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {17},
  number    = {2},
  year      = {2026},
  publisher = {The Science and Information Organization},
  author    = {Abdulbasid Banga},
  doi       = {10.14569/IJACSA.2026.0170247},
  url       = {https://doi.org/10.14569/IJACSA.2026.0170247}
}