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US-20260129055-A1 - Adaptive AI Cybersecurity System for Threat Identification, Prevention, and Device Monitoring

US20260129055A1US 20260129055 A1US20260129055 A1US 20260129055A1US-20260129055-A1

Abstract

The present invention relates to an AI-driven cybersecurity system that provides adaptive protection by identifying, mitigating, and preventing cyber threats in real-time. The system leverages advanced machine learning algorithms to detect anomalies in network traffic, enabling the identification of potential threats, which are then neutralized through automatic adjustments to firewall rules and network configurations. The system includes a tracing module capable of locating the source of cyberattacks by analyzing IP addresses and other network metadata, allowing for comprehensive incident reporting. Additionally, the invention logs and monitors all devices connecting to the network, both via Wi-Fi and hardline access, ensuring security compliance and detecting unauthorized activity. The system's adaptive approach ensures continuous protection by automatically updating security measures and reporting detailed findings to security personnel for future prevention.

Inventors

  • Alexander Davis

Assignees

  • Alexander Davis

Dates

Publication Date
20260507
Application Date
20241103

Claims (10)

  1. 1 . A system for providing adaptive cybersecurity protection comprising: a. An application-specific integrated circuit (ASIC) for an artificial neural network connected to a communications network, the ASIC comprising: a plurality of neurons organized in an array, wherein each neuron comprises a register, a processing element and at least one input, and a plurality of synaptic circuits, each synaptic circuit including a memory for storing a synaptic weight, wherein each neuron is connected to at least one other neuron via one of the plurality of synaptic circuits configured to identify one or more cybersecurity threats through pattern recognition of anomaly detection across network traffic; b. A network communication device with an associated processor configured to: dynamically adjust firewall rules, access permissions, and network configurations to neutralize the identified threat; and configured to locate the origin of the identified threat by tracking the IP address and related metadata; and c. A display device configured to display an incident report containing threat type, origin, potential system vulnerabilities exploited, and, optionally, preventative measure taken.
  2. 2 . The system of claim 1 , wherein the threat detection module utilizes deep learning algorithms to continuously monitor incoming and outgoing network traffic for abnormal behaviors indicative of potential cyber threats.
  3. 3 . The system of claim 2 , wherein the adaptive response mechanism automatically patches vulnerabilities identified during the cyberattack in real time to prevent the recurrence of the exploit.
  4. 4 . The system of claim 3 , wherein the tracing module is capable of identifying the geographic location and device type of the threat origin by analyzing IP address details, network layers, and device signatures.
  5. 5 . The system of claim 4 , wherein the reporting module produces incident reports in real-time and transmits the reports to designated security personnel, including step-by-step breakdowns of incident response actions taken.
  6. 6 . The system of claim 1 , further comprising: a. A logging module configured to record every device connecting to the network via Wi-Fi or hardline connections. b. A device identification system configured to profile each device based on unique identifiers, such as MAC addresses, IP addresses, and device metadata. c. A compliance system configured to monitor and enforce security policies based on the type and identity of the devices accessing the network.
  7. 7 . The system of claim 6 , wherein the logging module continuously monitors hardline connections to ensure that wired network access is subject to the same level of scrutiny as wireless access.
  8. 8 . The system of claim 7 , wherein the device identification system profiles devices and assigns a risk score based on the device's behavior history and security posture.
  9. 9 . The system of claim 8 , wherein the compliance system automatically restricts or quarantines devices that do not meet predetermined security thresholds.
  10. 10 . The system of claim 1 , wherein the network communication device with an associated processor is configured for operations further comprising: a. Responding to the identified threats by automatically adapting network security policies and patching vulnerabilities; b. Tracking the origin of the threats by analyzing network traffic and identifying source IP addresses; and c. Generating a report outlining recommendations for future threat prevention with respect to the source IP addresses.

Description

BACKGROUND OF THE INVENTION Field of Invention The present invention relates to the field of cybersecurity, specifically to adaptive, AI-driven systems that autonomously detect, mitigate, and prevent cyber threats. The invention utilizes machine learning algorithms to identify security vulnerabilities, respond in real-time by adapting and patching potential entry points, and track the origins of cyber threats by tracing IP addresses. Additionally, the system generates detailed reports documenting each threat and the applied solutions, ensuring ongoing improvement in threat prevention. The invention also includes a comprehensive security measure that logs and monitors all devices accessing a network, whether via Wi-Fi or hardline, providing robust, real-time device access management. This is particularly critical for securing physical network connections, which often receive less oversight than wireless networks. The invention's approach provides a holistic, adaptive, and traceable cybersecurity solution for protecting digital infrastructures from emerging and persistent threats. BRIEF SUMMARY OF THE INVENTION The present invention provides an advanced AI-driven cybersecurity system designed to detect, adapt to, and mitigate cyber threats in real-time. By employing machine learning, the system identifies vulnerabilities and proactively adjusts network defenses, preventing future attacks. It traces the origins of threats, such as IP addresses, and generates comprehensive incident reports, documenting how each threat was managed and how similar risks will be addressed moving forward. Additionally, the invention includes a robust monitoring tool that logs all devices accessing a network via Wi-Fi or hardline, ensuring complete oversight and increased security of both wireless and wired network access points. This integrated approach enhances protection by dynamically responding to threats while providing traceable, actionable data for continuous improvement. BRIEF DESCRIPTION OF THE FIGURES FIG. 1:7-step collaborative process where the AI detects and blocks threats, generates reports for human review, adapts from human feedback, and continuously improves threat detection and mitigation through an ongoing learning cycle. DETAILED DESCRIPTION The present invention is an AI-driven cybersecurity system that revolutionizes the way digital environments are protected against emerging threats. This section offers a detailed description of the invention by breaking down its various components, functionalities, and operational methods, providing an in-depth understanding of who benefits from it, what it accomplishes, how it works, and why it is necessary. This AI cybersecurity system is intended for a wide range of users across various industries. Primary beneficiaries include: Corporations: Enterprises dealing with sensitive information, such as finance, healthcare, or defense, are key users. These organizations need robust security measures to protect their data against cyberattacks, phishing schemes, malware, and more.Small-to-Medium Enterprises (SMEs): As smaller entities increasingly face the same cyber threats as larger organizations, they also require a scalable, adaptive cybersecurity solution.Government Agencies: With their sensitive data at constant risk of espionage, governmental bodies can utilize the AI's ability to dynamically respond to sophisticated threats.Home Users and IoT Environments: As smart homes and IoT devices proliferate, individuals face cyber risks. This invention addresses these challenges by ensuring security for all devices accessing home networks, either through Wi-Fi or hardwired connections.Cybersecurity Professionals: The system also serves cybersecurity experts, providing them with detailed reports and insights into cyber incidents to help improve future defenses. The system provides comprehensive protection against known and unknown cybersecurity threats by: Identifying Threats: The system continuously scans and monitors network traffic to detect suspicious activity and potential vulnerabilities, using machine learning algorithms to identify evolving threats like malware, ransomware, and phishing attempts.Adapting to Threats: Upon detecting a threat, the system dynamically adjusts its security parameters to close any vulnerabilities in the network. The AI-powered system learns from each interaction, creating more robust defenses over time.Tracing the Origin of Threats: Once a cyber threat is detected, the system traces its origin by analyzing network packets, tracking IP addresses, and identifying the geographic and virtual origin of the attack.Generating Incident Reports: For every security incident, the system generates a detailed report. This includes an overview of the threat, how it entered the system, the actions taken to mitigate the risk, and recommendations for preventing future attacks.Logging and Monitoring Devices: In an age where network security encompasses more than ju