2026· IEEE Transactions on Networking· Vol 34, pp. 6013-6028· 0 citations· 47 references
Computer Science
Abstract
Evasion attacks pose a significant threat to Network Intrusion Detection Systems (NIDS) by manipulating packets to bypass their defensive strategies. This paper presents a novel black-box evasion attack framework, BlackSlit, tailored against NIDS for encrypted traffic. Unlike traditional “buffer-and-perturb” pipelines that incur significant latency, BlackSlit enables live evasion by generating universal perturbations for incoming encrypted traffic without prior knowledge. To ensure practical applicability, BlackSlit generates packet-level perturbation sequences and imposes manipulability constraints on encrypted packet features, ensuring that the perturbations are executable at the packet level. BlackSlit comprises two core components, the Generator and the Simulator, which operate in a complementary manner. The Generator iteratively produces packet-level universal perturbations, while the Simulator mimics the behavior of black-box target NIDS to guide the update process of the Generator. Both components employ a hierarchical time-series Transformer (TST)-based architecture to account for temporal correlations intrinsic to encrypted traffic, aligning with the focus of state-of-the-art (SOTA) NIDS. This architecture ensures that temporal dependencies are effectively modeled during both perturbation generation and target system simulation, thereby enhancing the overall efficacy of evasion attacks. Evaluations are conducted on 3 real-world datasets, benchmarked against 6 leading evasion attack baselines and 9 NIDS. Results demonstrate that BlackSlit consistently outperforms state-of-the-art methods across all benchmarks. Moreover, experiments against defended NIDS confirm that BlackSlit maintains robustness.
Threat-Reactive Encryption (TRE), a four-layer framework that couples a real-time ML threat scorer to a PKCS#11-compatible key management pipeline, closing the gap between threat detection and cryptographic response, is presented.
Mohammed El-hajj· International Conference on...· 0 citations
This paper introduces donor-based mimicry injection, in which the access point injects a replica of a paired device’s authentic traffic into each device’s stream, and proposes a game-theoretic framework for evaluating Wi-Fi MAC-layer cover-traffic injection defenses.
Abdulmajeed Alghamdi, Mnassar Alyami, Inad Alqurashi et al.· Italian National Conference...· 0 citations
LogSanitizer is proposed, a family of input sanitization defenses operating at two levels: a pre-prompt log-transformation pipeline that disrupts trigger patterns in the structured log representation, and a post-tokenizer perturbation strategy that corrupts trigger-bearing token configurations before they reach the mod...
Leszek Wronski, Bogdan Ksiezopolski· International Conference on...· 0 citations
Vehicle-to-Everything (V2X) communication enables vehicles to exchange safety-critical messages, but its reliance on temporary pseudonymous identities makes it vulnerable to Sybil attacks, where a single attacker fabricates multiple identities to inject false information into the network. This paper presents a lightwei...
Maher Fayyad, Abdullah Awad, Edison Pignaton De Freitas et al.· International Conference on...· 0 citations
This paper concludes by identifying promising future research directions in targeted obfuscation and urges a pivot away from mathematically flawless encryption toward hardware-accelerated, latency-aware detection topologies that secure proprietary trading signals without sacrificing line-speed threat mitigation.
Safety classifiers ("guards") are the dominant black-box defense for vision-language models, yet a guard judges an input's surface form, not its meaning: a harmful request re-encoded as set theory, formal logic, a classical language, code, or text rendered inside an image slips past a guard that would block it in plain...
Haoyu Zhang, Zhuo-Xiang Wang, Shi-Bo Zheng et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.