Artificial Account Hacking Detection System
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Solution Overview
Problem
Current cyber-hacking detection methods often fail to detect breaches in a timely manner, struggle to identify the cause and extent of the breach, and may be ineffective due to latency issues, especially when relying on active user accounts or honey pot techniques.
Innovation Solution
The system generates artificial accounts to mimic actual accounts, learns hacking behaviors, and detects cyber-hacks by monitoring activity in these artificial accounts, allowing for early detection and differentiation between general and specific types of cyber-hacks based on account types and managing entities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If active user accounts or honey pot techniques are used for cyber-hacking detection, then detection capability is provided, but latency issues occur that reduce effectiveness
Solution Approach 1:
The system performs preliminary actions by generating artificial accounts before actual hacking attempts occur. These artificial accounts are pre-configured with various vulnerabilities and characteristics representing different account types. By having these accounts ready in advance, the system can immediately detect hacking attempts without the latency associated with creating detection mechanisms in real-time or waiting for honey pots to be triggered.
Solution Approach 2:
The system creates copies of actual user accounts in the form of artificial accounts that replicate account structures, vulnerabilities, and characteristics. These artificial accounts serve as safe replicas that can be monitored for hacking attempts without risking real user data or experiencing the delays of traditional honey pot deployment. The copying approach allows parallel monitoring of multiple account types simultaneously.
2Reliability
If traditional detection methods are used, then some hacking attempts are detected, but the cause and extent of the breach cannot be determined
Solution Approach 1:
The system segments the detection process into multiple specialized artificial accounts, each representing different account types (e.g., financial accounts, email accounts, social media accounts) with specific vulnerabilities. When a hacking attempt occurs, the segmentation allows the system to identify which specific account type was targeted, what vulnerability was exploited, and the extent of the breach based on the characteristics of the compromised artificial account.
Solution Approach 2:
The artificial accounts serve as intermediaries between actual user accounts and potential hackers. When hackers target these artificial accounts, the system gains valuable information about hacking techniques, vulnerabilities, and attack patterns without exposing real user data. The intermediaries provide detailed breach information including the cause and extent of attacks that would otherwise remain hidden.
3Reliability
If monitoring of actual user accounts is performed, then hacking attempts can be detected, but user privacy is compromised
Solution Approach 1:
The system uses artificial accounts as copies that replicate the structural and vulnerability characteristics of actual user accounts without containing real user data. This copying approach enables comprehensive monitoring and detection of hacking attempts while completely preserving user privacy, as no actual personal information is exposed or accessed during the detection process.
Solution Approach 2:
The artificial accounts act as intermediaries that absorb and isolate monitoring activities from actual user accounts. All detection operations, data collection, and analysis are performed on these intermediary artificial accounts, creating a protective barrier that maintains user privacy while still providing effective hacking detection capabilities.
Data Source
AI summary
Methods and systems for cyber-hacking detection are provided. One method includes generating, by a processor, one or more artificial accounts for a type of actual account, learning one or more hacking behaviors for the type of actual account, and detecting cyber-hacks in activity in the one or more artificial accounts based on the one or more hacking behaviors. Systems and computer program products for performing the above method are also provided.