Adaptive Deception Framework with Behavioral Analysis for Enhanced Cybersecurity Defense

This paper presents CADL Cognitive-Adaptive Deception Layer, an adaptive deception framework achieving 99.88% detection rate with 0.13% false positive rate on the CICIDS2017 dataset. The framework employs ensemble machine learning Random Forest, XGBoost, Neural Networks combined with behavioral...

When AD Gets Breached: Detecting NTDS.dit Dumps and Exfiltration with Trellix NDR

When AD Gets Breached: Detecting NTDS.dit Dumps and Exfiltration with Trellix NDR By Maulik Maheta · September 25, 2025 Executive summary Active Directory AD stores the digital keys to an organization's kingdom. When attackers gain access to a network, they often target the NTDS.dit file, which...

Cyber Attack Mitigation Framework for Denial of Service (DoS) Attacks in Fog Computing

Innovative solutions to cyber security issues are shaped by the ever-changing landscape of cyber threats. Automating the mitigation of these threats can be achieved through a new methodology that addresses the domain of mitigation automation, which is often overlooked. This literature overview...

The Signalgate Case Is Waiving a Red Flag to All Organizational and Behavioral Cybersecurity Leaders, Practitioners, and Researchers: Are We Receiving the Signal Amidst the Noise?

The Signalgate incident of March 2025, wherein senior US national security officials inadvertently disclosed sensitive military operational details via the encrypted messaging platform Signal, highlights critical vulnerabilities in organizational security arising from human error, governance gaps...

CVE-2024-13065

Improper Enforcement of Behavioral Workflow, Uncontrolled Resource Consumption vulnerability in Akinsoft MyRezzta allows Input Data Manipulation, CAPEC - 125 - Flooding.This issue affects MyRezzta: from s2.02.02 before v2.05.01...

CVE-2024-13065

Improper Enforcement of Behavioral Workflow, Uncontrolled Resource Consumption vulnerability in Akinsoft MyRezzta allows Input Data Manipulation, CAPEC - 125 - Flooding. This issue affects MyRezzta: from s2.02.02 before v2.05.01...

CVE-2024-13065

Improper Enforcement of Behavioral Workflow, Uncontrolled Resource Consumption vulnerability in Akinsoft MyRezzta allows Input Data Manipulation, CAPEC - 125 - Flooding. This issue affects MyRezzta: from s2.02.02 before v2.05.01...

Addressing Weak Authentication like RFID, NFC in EVs and EVCs Using AI-Powered Adaptive Authentication

The rapid expansion of the Electric Vehicles EVs and Electric Vehicle Charging Systems EVCs has introduced new cybersecurity challenges, specifically in authentication protocols that protect vehicles, users, and energy infrastructure. Although widely adopted for convenience, traditional...

Fortifying the Agentic Web: a Unified Zero-Trust Architecture against Logic-Layer Threats

This paper presents a Unified Security Architecture that fortifies the Agentic Web through a Zero-Trust IAM framework. This architecture is built on a foundation of rich, verifiable agent identities using Decentralized Identifiers DIDs and Verifiable Credentials VCs, with discovery managed by a...

Whispering Agents: an Event-Driven Covert Communication Protocol for the Internet of Agents

The emergence of the Internet of Agents IoA introduces critical challenges for communication privacy in sensitive, high-stakes domains. While standard Agent-to-Agent A2A protocols secure message content, they are not designed to protect the act of communication itself, leaving agents vulnerable t...

PT-2025-31774 · Undefined · Undefined

hey @Microsoft when Defender started scanning for non-malicious documents like pandemic compliance forms, it crossed from security into behavioral monitoring. Microsoft's transparency failures around this documented in CVE-2020-16883 validated many professionals' concerns...

A Crowdsensing Intrusion Detection Dataset for Decentralized Federated Learning Models

This paper introduces a dataset and experimental study for decentralized federated learning DFL applied to IoT crowdsensing malware detection. The dataset comprises behavioral records from benign and eight malware families. A total of 21,582,484 original records were collected from system calls,...

PHASE: Passive Human Activity Simulation Evaluation

Cybersecurity simulation environments, such as cyber ranges, honeypots, and sandboxes, require realistic human behavior to be effective, yet no quantitative method exists to assess the behavioral fidelity of synthetic user personas. This paper presents PHASE Passive Human Activity Simulation...

LLM-Stackelberg Games: Conjectural Reasoning Equilibria and Their Applications to Spearphishing

We introduce the framework of LLM-Stackelberg games, a class of sequential decision-making models that integrate large language models LLMs into strategic interactions between a leader and a follower. Departing from classical Stackelberg assumptions of complete information and rational agents, ou...

Towards Reliable Forgetting: a Survey on Machine Unlearning Verification, Challenges, and Future Directions

With growing demands for privacy protection, security, and legal compliance e.g., GDPR, machine unlearning has emerged as a critical technique for ensuring the controllability and regulatory alignment of machine learning models. However, a fundamental challenge in this field lies in effectively...

The data on denying social media for kids (re-air) (Lock and Code S06E12)

This week on the Lock and Code podcast … Complex problems often assume complex solutions, but recent observations about increased levels of anxiety and depression, increased reports of loneliness, and lower rates of in-person friendships for teens and children in America today have led some schoo...

MalGEN: a Generative Agent Framework for Modeling Malicious Software in Cybersecurity

The dual use nature of Large Language Models LLMs presents a growing challenge in cybersecurity. While LLM enhances automation and reasoning for defenders, they also introduce new risks, particularly their potential to be misused for generating evasive, AI crafted malware. Despite this emerging...

Zero-Trust Foundation Models: a New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things

This paper focuses on Zero-Trust Foundation Models ZTFMs, a novel paradigm that embeds zero-trust security principles into the lifecycle of foundation models FMs for Internet of Things IoT systems. By integrating core tenets, such as continuous verification, least privilege access LPA, data...

RADEP: a Resilient Adaptive Defense Framework against Model Extraction Attacks

Machine Learning as a Service MLaaS enables users to leverage powerful machine learning models through cloud-based APIs, offering scalability and ease of deployment. However, these services are vulnerable to model extraction attacks, where adversaries repeatedly query the application programming...

Key Takeaways from the Take Command Summit 2025: Inside the Mind of an Attacker

In one of the most anticipated sessions of Take Command 2025, Raj Samani, Chief Scientist at Rapid7, sat down with Trent Teyema, former FBI Special Agent and President of CSG Strategies, for a candid conversation on how threat actors are evolving and what defenders must do to keep up. Moderated b...