Unfolding Data Entry Forms for Bidirectional Learning
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Solution Overview
Problem
Conventional approaches to understanding and securing system architecture are prone to errors and inefficiencies due to ad hoc processes, which are not easily comprehensible to both security experts and product team members, leading to suboptimal knowledge transfer and inadequate consideration of security impacts.
Innovation Solution
A system architecture definition module that unfolds data entry forms into sequential milestones, allowing for gradual and systematic learning, with modules for milestone management, data entry, and visualization, enabling the identification of proper context and eliminating the need for iterative data collection, and using machine learning to infer relationships and suggest attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If ad hoc processes are used for security expert interviews and architecture understanding, then flexibility and intuitive methodology are improved, but error rate and resource waste increase
Solution Approach 1:
The patent segments the architecture understanding process into discrete milestones (e.g., milestone 302-312) with specific objectives. Each milestone breaks down complex security analysis into manageable tasks such as defining components, trust zones, interfaces, and data security characteristics separately. This segmentation reduces errors by providing structured guidance while maintaining flexibility in execution.
Solution Approach 2:
The patent implements preliminary action by pre-defining milestone frameworks, data collection templates, and security assessment criteria before the actual security analysis begins. The system prepares milestone definitions, object attribute structures, and data collection forms in advance, allowing security experts to follow predetermined reliable processes while adapting to specific architecture contexts.
2Loss of information
If comprehensive data collection is performed in conventional ad hoc manner, then complete architecture understanding is achieved, but iterative data collection and time consumption increase
Solution Approach 1:
The patent divides comprehensive data collection into milestone-specific data collection phases. Each milestone (302-312) has defined data collection requirements for specific objects and attributes. This segmented approach ensures complete architecture understanding by systematically covering all aspects while eliminating iterative back-and-forth by collecting the right data at the right time.
Solution Approach 2:
The system performs preliminary action by pre-configuring data collection templates and milestone frameworks that specify what data needs to be collected at each stage. This prevents incomplete data collection and reduces iterative revisions by establishing comprehensive data requirements upfront while organizing collection efforts efficiently.
3Measurement precision
If security expert methodologies are used, then security analysis depth is improved, but comprehensibility to product team members deteriorates
Solution Approach 1:
The patent introduces an intermediary framework of standardized milestones and object models that bridge security expert methodologies and product team understanding. The milestone structure (302-312) and defined objects (components, interfaces, trust zones) serve as a common language that preserves security analysis depth while making the process comprehensible to product team members through structured, familiar terminology.
4Measurement precision
If detailed architecture analysis is performed, then security impact assessment accuracy is improved, but process complexity increases
Solution Approach 1:
The patent segments detailed architecture analysis into milestone-specific analytical tasks. Each milestone focuses on specific objects and attributes (e.g., milestone 304 for components, 306 for trust zones, 308 for interfaces). This segmentation maintains security impact assessment accuracy by ensuring thorough analysis of each aspect while reducing overall process complexity through structured organization and clear milestone boundaries.
Data Source
AI summary
Various embodiments of the present technology can include systems, methods, and non-transitory computer readable media configured to receive milestones to define objects and attributes associated with the objects. The objects and the attributes can define an architecture of a system. A first table associated with a first milestone can be provided. The first table can be configured to receive a first set of objects associated with the first milestone. The first set of objects and a corresponding set of attributes for the first set of objects can be received. An indication to advance to a second milestone that follows the first milestone can be received. A second table associated with the second milestone can be provided. The second table can be configured to receive a second set of objects associated with the second milestone.