The Nаtiоnаl Drоne Operаtiоns Management System (NDOMS) coordinates civilian and governmental drones for infrastructure inspection, medical delivery, and emergency operations. It comprises the following services: Drone Control API – issues flight commands and ingests telemetry. Mission Planning Service – allocates missions and stores operational data. Analytics Service – processes flight recordings and incident logs. Operator Portal – web interface for pilots, regulators, and maintenance teams. Regulatory Gateway – connects to national aviation databases for flight approvals. Audit findings (current state): Each service maintains its own local login store and bespoke access checks. Credentials are stored in plaintext withi`n configuration files. Compromise of Analytics Service enables issuing flight commands (lateral movement to Drone Control API). No consistent audit trail of access to mission/regulatory data. Field operators report workflow friction from multiple independent logins. Change constraints (must be met in your design): Single sign-on for humans and consistent authentication for service-to-service calls. Support for MFA for human operators who can work online and with intermittent connectivity at remote sites. Centralized token issuance and verification without sharing passwords with downstream services (tokens/assertions only). A single enforcement point before protected business logic for every incoming request (human or service). Fine-grained authorization that combines role semantics with contextual attributes such as operator region, mission state (planned/active/emergency), and device class. Encrypted channels for all inter-service and external links; machine identity must be verifiable. You are not required to draw a diagram. Your answer must articulate where each pattern lives, how it is invoked, and how components interact at runtime. Question As a cybersecurity engineer, propose a complete redesign of the access and authentication architecture for NDOMS by applying the security patterns taught in class. Answer each item separately (6.1 - 6.3). Do not merge them into a single essay. 6.1. Weakness–Pattern MappingIdentify the concrete weaknesses in the current state and map each to the specific pattern(s) you will apply. 6.2 Pattern Application – Where and HowApply at least three of the patterns learned in the course, specifying placement and mechanics: For each chosen pattern, detail interfaces, tokens/claims, lifetimes/scopes, and validation steps. 6.3. Trade-offs and Operational ImpactsDiscuss maintainability, performance, and UX trade-offs and how you will address them. Provide concrete justifications tied to NDOMS workflows. Notes for Students Depth matters: name the artifacts (e.g., token claims, role names, example ABAC rule, mTLS certificate subject), and explain the enforcement sequence. "What checks what, before, and what" Provide a specific and separate answer for each question. Do not combine all responses into a single, unified answer. Rubric Criterion Excellent (Full Credit) Proficient (Partial Credit) Developing (Minimal Credit) (a) Weakness–Pattern Mapping Clearly identifies at least 3 weaknesses and maps each to one or more appropriate security patterns. Demonstrates insight into why each pattern mitigates the specific issue. Uses terminology correctly and references pattern properties (scope, type, enforcement) (10 points). Identifies 1-2 weaknesses and links them to generally appropriate patterns, but the mapping lacks precision or justification. Some misalignment between the problem and the chosen pattern (5 points). Lists weaknesses and patterns with little or no explanation of how they relate or mitigate risk (1 point) (b) Pattern Application – Where and How Applies at least three distinct patterns with correct architectural placement and detailed explanation of how each is invoked at runtime. Describes interfaces (e.g., API Gateway, AuthN service), tokens/claims (e.g., JWT contents, lifetimes), and validation steps (e.g., signature verification, token scope). Shows understanding of how human and service-to-service authentication differ. Integration between components is coherent and technically sound. (15 points) Applies 1-2 patterns correctly but with limited runtime detail or missing interactions (e.g., token flow unclear). Explanations may be conceptually sound but lack depth in enforcement sequence or configuration examples (7 points). Applies fewer than three patterns, or explanations are vague, inconsistent, or technically incorrect. Little evidence of understanding system-level enforcement (1 point). (c) Trade-offs and Operational Impacts Thoughtfully analyzes trade-offs among security strength, usability, performance, and maintainability. Identifies specific operational contexts (e.g., drone connectivity limits, token caching, MFA offline drift, Gatekeeper latency). Proposes realistic mitigations (redundancy, token lifetimes, fallback strategies). Demonstrates evaluative reasoning and balanced argument. (10 points) Discusses trade-offs generally (e.g., “performance vs. security”) without contextual grounding in NDOMS operations or without proposing mitigations. Mentions trade-offs superficially or only restates generic pros/cons without analysis or operational tie-in. Technical Accuracy and Terminology Uses precise cybersecurity and pattern terminology (e.g., “JWT audience claim validation,” “mutual TLS with X.509 certificates,” “short-lived scoped token,” “dynamic ABAC rule”). No conceptual or factual errors. Demonstrates mastery of course content. (5 points) Minor technical inaccuracies or imprecise use of pattern terminology, but overall sound understanding (2 points). Multiple technical errors, incorrect definitions, or confusion between authentication and authorization (1 point). Analytical Depth and Originality Goes beyond class examples: contextualizes design choices, anticipates attack paths, or introduces justified extensions (e.g., redundant Authenticator replicas, auditing through Gatekeeper logs). Integrates multiple course concepts into a coherent defense-in-depth argument (5 points). Provides correct but straightforward answers limited to what was covered in class: some independent reasoning but minimal innovation (2 points). Merely repeats class definitions without applying them to the scenario (1 point). Organization and Clarity Each sub-question (a–c) is answered separately and clearly labeled—logical structure, concise paragraphs, correct grammar, and spelling. Arguments flow naturally and support each conclusion (5 points). Unclear, disorganized, or merged answers; hard to follow reasoning (0 points).
Scenаriо The Smаrt Highwаy Operatiоns Management Platfоrm (SHOMP) coordinates IoT sensors, roadside units, and control centers across a national smart-road network. It enables real-time traffic monitoring, automated tolling, and emergency response coordination. The system integrates heterogeneous subsystems operated by multiple agencies and vendors. Main services: Traffic Sensor Gateway – collects data from roadside cameras, LIDARs, and weather stations. Incident Response Service – dispatches road patrols and alerts maintenance units. Toll Management System – validates vehicle identifiers and processes transactions. Operations Dashboard – provides control-room operators and administrators with situational views. External Partner API – allows third-party analytics vendors and navigation apps to query non-sensitive traffic data. Audit findings (current state): Each subsystem implements its own authentication mechanism (API keys, static credentials). Certificates and secrets are shared across vendors without lifecycle control. The Incident Response Service can directly invoke privileged commands on roadside devices through unauthenticated REST calls. No audit trail exists to verify which operator or contractor issued configuration changes. Maintenance staff experience frequent session expirations when switching between mobile devices and the central dashboard. Change constraints (must be met in your design): Unified identity for all human operators, roadside devices, and third-party APIs. MFA for human users, compatible with field-deployed mobile devices operating under intermittent connectivity. Centralized token-based authentication; no password replication among services. Single enforcement layer validating tokens and authorizations before any roadside command or transaction is executed. Granular authorization combining role semantics (operator, contractor, regulator) with contextual attributes such as region, asset type, and maintenance window. Encrypted communication channels (mTLS) for every inter-service and external connection, supporting device-level identity verification. You are not required to draw a diagram. Your answer must articulate where each pattern resides, how it is invoked, and how components interact at runtime. Question As a cybersecurity engineer, propose a complete redesign of the access and authentication architecture for SHOMP by applying the security patterns taught in class.Answer each item separately (6.1 - 6.3). Do not merge them into a single essay. 6.1. Weakness–Pattern MappingIdentify the concrete weaknesses in the current state and map each to the specific pattern(s) you will apply. 6.2 Pattern Application – Where and HowApply at least three of the patterns learned in the course, specifying placement and mechanics: For each chosen pattern, detail interfaces, tokens/claims, lifetimes/scopes, and validation steps. 6.3. Trade-offs and Operational ImpactsDiscuss maintainability, performance, and UX trade-offs and how you will address them. Provide concrete justifications tied to SHOMP workflows. Notes for Students Depth matters: name the artifacts (e.g., token claims, role names, example ABAC rule, mTLS certificate subject), and explain the enforcement sequence. "What checks what, before, and what" Provide a specific and separate answer for each question. Do not combine all responses into a single, unified answer. Rubric Criterion Excellent (Full Credit) Proficient (Partial Credit) Developing (Minimal Credit) (a) Weakness–Pattern Mapping Clearly identifies at least 3 weaknesses and maps each to one or more appropriate security patterns. Demonstrates insight into why each pattern mitigates the specific issue. Uses terminology correctly and references pattern properties (scope, type, enforcement) (10 points). Identifies 1-2 weaknesses and links them to generally appropriate patterns, but the mapping lacks precision or justification. Some misalignment between the problem and the chosen pattern (5 points). Lists weaknesses and patterns with little or no explanation of how they relate or mitigate risk (1 point) (b) Pattern Application – Where and How Applies at least three distinct patterns with correct architectural placement and detailed explanation of how each is invoked at runtime. Describes interfaces (e.g., API Gateway, AuthN service), tokens/claims (e.g., JWT contents, lifetimes), and validation steps (e.g., signature verification, token scope). Shows understanding of how human and service-to-service authentication differ. Integration between components is coherent and technically sound. (15 points) Applies 1-2 patterns correctly but with limited runtime detail or missing interactions (e.g., token flow unclear). Explanations may be conceptually sound but lack depth in enforcement sequence or configuration examples (7 points). Applies fewer than three patterns, or explanations are vague, inconsistent, or technically incorrect. Little evidence of understanding system-level enforcement (1 point). (c) Trade-offs and Operational Impacts Thoughtfully analyzes trade-offs among security strength, usability, performance, and maintainability. Identifies specific operational contexts (e.g., drone connectivity limits, token caching, MFA offline drift, Gatekeeper latency). Proposes realistic mitigations (redundancy, token lifetimes, fallback strategies). Demonstrates evaluative reasoning and balanced argument. (10 points) Discusses trade-offs generally (e.g., “performance vs. security”) without contextual grounding in NDOMS operations or without proposing mitigations. Mentions trade-offs superficially or only restates generic pros/cons without analysis or operational tie-in. Technical Accuracy and Terminology Uses precise cybersecurity and pattern terminology (e.g., “JWT audience claim validation,” “mutual TLS with X.509 certificates,” “short-lived scoped token,” “dynamic ABAC rule”). No conceptual or factual errors. Demonstrates mastery of course content. (5 points) Minor technical inaccuracies or imprecise use of pattern terminology, but overall sound understanding (2 points). Multiple technical errors, incorrect definitions, or confusion between authentication and authorization (1 point). Analytical Depth and Originality Goes beyond class examples: contextualizes design choices, anticipates attack paths, or introduces justified extensions (e.g., redundant Authenticator replicas, auditing through Gatekeeper logs). Integrates multiple course concepts into a coherent defense-in-depth argument (5 points). Provides correct but straightforward answers limited to what was covered in class: some independent reasoning but minimal innovation (2 points). Merely repeats class definitions without applying them to the scenario (1 point). Organization and Clarity Each sub-question (a–c) is answered separately and clearly labeled—logical structure, concise paragraphs, correct grammar, and spelling. Arguments flow naturally and support each conclusion (5 points). Unclear, disorganized, or merged answers; hard to follow reasoning (0 points).