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cs.CR updates on arXiv.org

Agentic Vulnerability Reasoning on Windows COM Binaries From Beats to Breaches:How Offensive AI Infers Sensitive User Information from Playlists Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems Token-Efficient Change Detection in LLM APIs Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verification Trident: Improving Malware Detection with LLMs and Behavioral Features When Alignment Isn't Enough: Response-Path Attacks on LLM Agents RefusalGuard: Geometry-Preserving Fine-Tuning for Safety in LLMs Checkerboard: A Simple, Effective, Efficient and Learning-free Clean Label Backdoor Attack with Low Poisoning Budget Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking Secret Stealing Attacks on Local LLM Fine-Tuning through Supply-Chain Model Code Backdoors Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents Defusing the Trigger: Plug-and-Play Defense for Backdoored LLMs via Tail-Risk Intrinsic Geometric Smoothing Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards Behavioral Canaries: Auditing Private Retrieved Context Usage in RL Fine-Tuning FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models Text Steganography with Dynamic Codebook and Multimodal Large Language Model An AI Agent Execution Environment to Safeguard User Data TwoHamsters: Benchmarking Multi-Concept Compositional Unsafety in Text-to-Image Models Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility Hardening x402: PII-Safe Agentic Payments via Pre-Execution Metadata Filtering QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits Hijacking Text Heritage: Hiding the Human Signature through Homoglyphic Substitution Like a Hammer, It Can Build, It Can Break: Large Language Model Uses, Perceptions, and Adoption in Cybersecurity Operations on Reddit Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation One Word at a Time: Incremental Completion Decomposition Breaks LLM Safety Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review
New Hashing Algorithm for Use in TCP Reassembly Module of...
Sankalp Bagaria · 2015-01-09 · via cs.CR updates on arXiv.org

Since last decade, IDS/ IPS has gained popularity in protecting large networks. They can employ signature based techniques and/or flow-based techniques to prevent intrusion from outside/ inside the network they are trying to protect. Signature based IDS/ IPS can be stateless or stateful. Stateful IDS can store the state of the protocol and use it for better detection of malware. In the case of TCP/IP networks, an attacker can also launch an attack such that the malicious code is distributed over many packets. These packets pass through the traditional IDS/ IPS and reassemble inside the network. Once re-assembled inside the network by the TCP/IP layer, the malicious code launches an attack. The TCP state and a copy of last few packets for each active connection has to be maintained in IDS/IPS. In TCP re-assembly, packets are re-assembled at IDS/IPS and searched for signature matches. A connection table has to be maintained for active connections and their list of last few (atmost 11) packets that have already arrived. We need data structures for searching the connection that the latest incoming packet belongs to. Popular hashing algorithms like CRC, XOR, summing tuple, taking modulus are inefficient as hash keys are not evenly distributed in hash-key space. Thus we show how an algorithm based on cryptography concepts can be used for efficient hashing in network connection management. We also show how to use full four tuple for calculating hash key instead of simply summing the tuple and taking the modulus of the sum.