How to Become a Cybersecurity Engineer: Complete Career Guide 2025 [₹12L Average Salary]

Portfolio Strategy and Structure

Cybersecurity Portfolio Objectives:

1. Demonstrate Technical Proficiency – Show mastery of security tools, frameworks, and methodologies
2. Highlight Risk Management – Quantify security improvements and risk reduction achievements
3. Showcase Compliance Knowledge – Display understanding of regulatory requirements and implementation
4. Present Incident Response – Document security incident handling and forensic analysis capabilities

Foundation Level Projects (Months 1-3)

1. Comprehensive Security Assessment and Remediation

• Scope: Complete security audit of small-medium business infrastructure including network, systems, and applications
• Technical Implementation: Vulnerability scanning, penetration testing, configuration review, policy assessment
• Deliverables: Executive summary, technical findings, risk assessment, remediation roadmap, cost-benefit analysis
• Business Impact: Identify and prioritize security risks, provide actionable recommendations, estimate risk reduction
• Documentation: Professional security assessment report with executive and technical sections

Security Assessment Implementation:

#!/bin/bash
# Automated Security Assessment Script

# Network Discovery and Port Scanning
echo “Starting Network Discovery…”
nmap -sn 192.168.1.0/24 > network_hosts.txt
nmap -sS -O -sV -A -T4 -iL network_hosts.txt -oA network_scan

# Vulnerability Scanning with OpenVAS
echo “Launching Vulnerability Scan…”
omp –username admin –password admin –host localhost \
    –xml “<create_target><name>Assessment_Target</name><hosts>192.168.1.0/24</hosts></create_target>”

# Web Application Security Testing
echo “Testing Web Applications…”
nikto -h http://target-web-app.com -o nikto_results.txt
sqlmap -u “http://target-app.com/login.php” –forms –dbs –batch

# System Configuration Review
echo “Auditing System Configurations…”
# Windows systems
wmic qfe list
net user
net localgroup administrators

# Linux systems
sudo lynis audit system –quick
sudo chkrootkit
sudo rkhunter –check –skip-keypress

# Generate Comprehensive Report
echo “Generating Security Assessment Report…”
python3 generate_security_report.py \
    –network-scan network_scan.xml \
    –vulnerability-scan vuln_results.xml \
    –web-app-scan nikto_results.txt \
    –config-audit lynis_report.dat \
    –output security_assessment_report.pdf

2. Security Operations Center (SOC) Implementation

• Business Challenge: Organization needs 24/7 security monitoring and incident response capabilities
• Technical Solution: Design and implement comprehensive SOC using open-source tools (ELK stack, Wazuh, TheHive)
• Advanced Features: Custom correlation rules, automated alerting, threat intelligence integration, incident workflow
• Metrics: Mean time to detection (MTTD), mean time to response (MTTR), false positive rate, coverage assessment
• Business Value: Proactive threat detection, reduced incident impact, compliance demonstration

Intermediate Level Projects (Months 3-5)

3. Cloud Security Architecture Design

• Challenge: Multi-cloud environment requiring unified security architecture and compliance framework
• Solution: Comprehensive cloud security design spanning AWS, Azure, and Google Cloud with automated compliance monitoring
• Technical Components: Identity federation, network security, data encryption, logging, monitoring, incident response
• Advanced Implementation: Infrastructure as code, automated security scanning, compliance reporting, cost optimization
• Business Impact: Unified security posture, regulatory compliance, reduced operational overhead

Cloud Security Architecture Example:

# Terraform configuration for multi-cloud security
# AWS Security Configuration
provider “aws” {
  region = “us-east-1”
}

# VPC with security groups
resource “aws_vpc” “secure_vpc” {
  cidr_block           = “10.0.0.0/16”
  enable_dns_hostnames = true
  enable_dns_support   = true
 
  tags = {
    Name        = “SecureVPC”
    Environment = “Production”
    Compliance  = “PCI-DSS”
  }
}

# Security groups with least privilege
resource “aws_security_group” “web_sg” {
  name_prefix = “web-sg”
  vpc_id      = aws_vpc.secure_vpc.id

  ingress {
    from_port   = 443
    to_port     = 443
    protocol    = “tcp”
    cidr_blocks = [“0.0.0.0/0”]
  }

  ingress {
    from_port   = 80
    to_port     = 80
    protocol    = “tcp”
    cidr_blocks = [“0.0.0.0/0”]
  }

  egress {
    from_port   = 0
    to_port     = 0
    protocol    = “-1”
    cidr_blocks = [“10.0.0.0/16”]  # Internal traffic only
  }

  tags = {
    Name = “WebSecurityGroup”
    Type = “DMZ”
  }
}

# CloudTrail for audit logging
resource “aws_cloudtrail” “security_audit” {
  name                         = “security-audit-trail”
  s3_bucket_name              = aws_s3_bucket.audit_logs.bucket
  include_global_service_events = true
  is_multi_region_trail       = true
  enable_logging              = true

  event_selector {
    read_write_type                 = “All”
    include_management_events       = true
    data_resource {
      type   = “AWS::S3::Object”
      values = [“arn:aws:s3:::${aws_s3_bucket.audit_logs.bucket}/*”]
    }
  }
}

# GuardDuty for threat detection
resource “aws_guardduty_detector” “security_detector” {
  enable = true
 
  datasources {
    s3_logs {
      enable = true
    }
    kubernetes {
      audit_logs {
        enable = true
      }
    }
  }

  tags = {
    Name = “SecurityDetector”
    Purpose = “ThreatDetection”
  }
}

# Azure Security Configuration
provider “azurerm” {
  features {}
}

# Network Security Group
resource “azurerm_network_security_group” “web_nsg” {
  name                = “web-nsg”
  location            = azurerm_resource_group.security_rg.location
  resource_group_name = azurerm_resource_group.security_rg.name

  security_rule {
    name                       = “HTTPS”
    priority                   = 1001
    direction                  = “Inbound”
    access                     = “Allow”
    protocol                   = “Tcp”
    source_port_range          = “*”
    destination_port_range     = “443”
    source_address_prefix      = “*”
    destination_address_prefix = “*”
  }

  security_rule {
    name                       = “SSH”
    priority                   = 1002
    direction                  = “Inbound”
    access                     = “Allow”
    protocol                   = “Tcp”
    source_port_range          = “*”
    destination_port_range     = “22”
    source_address_prefix      = “10.0.0.0/16”  # Internal only
    destination_address_prefix = “*”
  }
}

# Azure Security Center
resource “azurerm_security_center_subscription_pricing” “security_pricing” {
  tier          = “Standard”
  resource_type = “VirtualMachines”
}

# Key Vault for secrets management
resource “azurerm_key_vault” “security_kv” {
  name                = “security-keyvault”
  location            = azurerm_resource_group.security_rg.location
  resource_group_name = azurerm_resource_group.security_rg.name
  tenant_id           = data.azurerm_client_config.current.tenant_id
  sku_name            = “standard”

  access_policy {
    tenant_id = data.azurerm_client_config.current.tenant_id
    object_id = data.azurerm_client_config.current.object_id

    secret_permissions = [
      “get”, “list”, “set”, “delete”, “recover”, “backup”, “restore”
    ]
  }

  network_acls {
    default_action = “Deny”
    bypass         = “AzureServices”
   
    virtual_network_subnet_ids = [
      azurerm_subnet.security_subnet.id
    ]
  }
}

Advanced Level Projects (Months 5-6)

4. Advanced Persistent Threat (APT) Simulation and Detection

• Sophisticated Challenge: Design and execute red team exercise simulating nation-state attack against enterprise environment
• Technical Complexity: Multi-stage attack chain, living-off-the-land techniques, custom malware development, evasion techniques
• Blue Team Response: Advanced threat hunting, behavioral analysis, machine learning detection, incident containment
• Metrics: Detection coverage, response time, containment effectiveness, lessons learned integration
• Business Impact: Validate security controls, identify gaps, improve incident response capabilities

5. Zero Trust Architecture Implementation

• Enterprise Challenge: Legacy network-based security model insufficient for modern threat landscape and remote work
• Comprehensive Solution: Complete zero trust implementation including identity, device, network, and application layers
• Advanced Technologies: Software-defined perimeters, micro-segmentation, continuous verification, risk-based authentication
• Integration Complexity: Legacy system integration, user experience optimization, performance monitoring
• Measurable Outcomes: 90% reduction in lateral movement, 60% improvement in breach detection time

Portfolio Presentation Standards

Professional Documentation Framework:

Cybersecurity Project Documentation Template:

Executive Summary:
– Security challenge and business risk assessment
– Solution approach and architectural decisions
– Risk reduction achieved and compliance status
– Implementation timeline and resource requirements

Technical Architecture:
– Security framework and control mapping
– Technology stack and integration architecture
– Threat model and attack surface analysis
– Performance and scalability considerations

Implementation Details:
– Configuration standards and hardening guides
– Custom scripts and automation workflows
– Monitoring and alerting configuration
– Incident response procedures and playbooks

Risk and Compliance:
– Risk assessment methodology and results
– Regulatory compliance demonstration
– Security metrics and KPI tracking
– Continuous improvement recommendations

Business Impact:
– Risk reduction quantification
– Compliance cost avoidance
– Operational efficiency improvements
– Return on security investment (ROSI)

Live Demonstration Environment:

• Home Security Lab – Virtualized environment for hands-on security testing and incident response
• Cloud Security Showcase – Multi-cloud security implementation with real-time monitoring
• Incident Response Simulation – Documented incident response exercises with lessons learned
• Threat Intelligence Platform – Custom threat intelligence gathering and analysis tools

Challenge 1: Staying Current with Rapidly Evolving Threat Landscape

Problem: Cybersecurity threats evolve constantly, making it difficult to stay current with new attack techniques and defense strategies
Impact: Outdated knowledge, ineffective security controls, missed threat detection, career stagnation
Symptoms: Unfamiliarity with recent attack campaigns, outdated security tools, limited threat intelligence awareness

Continuous Learning Strategy:

Threat Intelligence Integration:

#!/usr/bin/env python3
“””
Automated Threat Intelligence Aggregation System
Collects threat intelligence from multiple sources and generates actionable insights
“””

import requests
import json
import csv
from datetime import datetime, timedelta
import hashlib

class ThreatIntelligenceAggregator:
    def __init__(self):
        self.sources = {
            ‘mitre_attack’: ‘https://raw.githubusercontent.com/mitre/cti/master/enterprise-attack/enterprise-attack.json’,
            ‘cisa_alerts’: ‘https://www.cisa.gov/cybersecurity-advisories/aa22-047a’,
            ‘sans_isc’: ‘https://isc.sans.edu/api/threats’,
            ‘otx_alienvault’: ‘https://otx.alienvault.com/api/v1/indicators/export’
        }
        self.indicators = []
        self.techniques = []
       
    def collect_mitre_techniques(self):
        “””Collect MITRE ATT&CK techniques and tactics”””
        try:
            response = requests.get(self.sources[‘mitre_attack’], timeout=30)
            attack_data = response.json()
           
            for obj in attack_data.get(‘objects’, []):
                if obj.get(‘type’) == ‘attack-pattern’:
                    technique = {
                        ‘id’: obj.get(‘external_references’, [{}])[0].get(‘external_id’),
                        ‘name’: obj.get(‘name’),
                        ‘description’: obj.get(‘description’, ”),
                        ‘tactics’: [phase[‘phase_name’] for phase in obj.get(‘kill_chain_phases’, [])],
                        ‘updated’: datetime.now().isoformat()
                    }
                    self.techniques.append(technique)
                   
        except Exception as e:
            print(f”Error collecting MITRE data: {e}”)
   
    def collect_threat_indicators(self):
        “””Collect indicators of compromise from various sources”””
        # Implement IOC collection from multiple threat intelligence feeds
        indicators = [
            {
                ‘type’: ‘domain’,
                ‘value’: ‘malicious-domain.com’,
                ‘confidence’: ‘high’,
                ‘source’: ‘manual_analysis’,
                ‘first_seen’: datetime.now().isoformat(),
                ‘tags’: [‘malware’, ‘c2’]
            }
        ]
        self.indicators.extend(indicators)
   
    def generate_daily_brief(self):
        “””Generate daily threat intelligence brief”””
        brief = {
            ‘date’: datetime.now().strftime(‘%Y-%m-%d’),
            ‘new_techniques’: len([t for t in self.techniques if
                                datetime.fromisoformat(t[‘updated’]).date() == datetime.now().date()]),
            ‘new_indicators’: len([i for i in self.indicators if
                                datetime.fromisoformat(i[‘first_seen’]).date() == datetime.now().date()]),
            ‘top_threats’: self._analyze_trending_threats(),
            ‘recommendations’: self._generate_recommendations()
        }
       
        return brief
   
    def _analyze_trending_threats(self):
        “””Analyze trending threat patterns”””
        # Implement threat trend analysis
        return [‘Ransomware targeting healthcare’, ‘Supply chain attacks’, ‘Cloud misconfigurations’]
   
    def _generate_recommendations(self):
        “””Generate actionable security recommendations”””
        return [
            ‘Update incident response procedures for ransomware’,
            ‘Review third-party vendor security assessments’,
            ‘Audit cloud security configurations’
        ]

# Usage
if __name__ == “__main__”:
    aggregator = ThreatIntelligenceAggregator()
    aggregator.collect_mitre_techniques()
    aggregator.collect_threat_indicators()
   
    daily_brief = aggregator.generate_daily_brief()
   
    # Email brief to security team
    with open(f”threat_brief_{datetime.now().strftime(‘%Y%m%d’)}.json”, ‘w’) as f:
        json.dump(daily_brief, f, indent=2)

Professional Development Framework:

• Daily Learning Routine – 30 minutes daily reading security news, threat reports, vulnerability disclosures
• Weekly Deep Dives – One hour weekly studying new attack techniques, security tools, or compliance updates
• Monthly Hands-On Practice – Dedicated lab time practicing new tools, techniques, or technologies
• Quarterly Skill Assessment – Evaluate knowledge gaps and plan learning priorities for next quarter

Challenge 2: Building Practical Experience Without Access to Enterprise Security Tools

Problem: Many security tools and scenarios require enterprise environments that individuals cannot afford or access
Challenge: Difficulty gaining hands-on experience with commercial tools, real incident response, enterprise scale
Solution: Strategic use of free tools, cloud credits, and simulation environments

Practical Experience Development Strategy:

Home Security Lab Setup:

#!/bin/bash
# Comprehensive Security Lab Setup Script

# Create isolated network environment
sudo apt update && sudo apt upgrade -y

# Install virtualization platform
sudo apt install -y virtualbox vagrant docker.io docker-compose

# Security tools installation
echo “Installing security tools…”

# SIEM and log analysis
docker run -d –name splunk -p 8000:8000 -e SPLUNK_START_ARGS=’–accept-license’ splunk/splunk:latest
docker run -d –name elasticsearch -p 9200:9200 -e “discovery.type=single-node” docker.elastic.co/elasticsearch/elasticsearch:7.15.0
docker run -d –name kibana -p 5601:5601 docker.elastic.co/kibana/kibana:7.15.0

# Vulnerability scanning
wget https://www.tenable.com/downloads/api/v1/public/pages/nessus/downloads/12345/download?i_agree_to_tenable_license_agreement=true -O nessus.deb
sudo dpkg -i nessus.deb
sudo systemctl start nessusd

# Network security tools
sudo apt install -y nmap wireshark tcpdump nikto dirb gobuster

# Web application security
sudo apt install -y burpsuite zaproxy sqlmap

# Penetration testing framework
git clone https://github.com/rapid7/metasploit-framework.git
cd metasploit-framework && bundle install

# Digital forensics
sudo apt install -y autopsy sleuthkit volatility

# Create vulnerable applications for practice
git clone https://github.com/WebGoat/WebGoat.git
git clone https://github.com/bkimminich/juice-shop.git
docker run -d -p 3000:3000 bkimminich/juice-shop

# Malware analysis environment
sudo apt install -y clamav rkhunter chkrootkit
git clone https://github.com/cuckoosandbox/cuckoo.git

# Create practice scenarios
mkdir -p ~/security-lab/{scenarios,reports,scripts}

# Generate sample log data for SIEM practice
python3 -c “
import random
import datetime
import json

# Generate sample security events
events = []
for i in range(1000):
    event = {
        ‘timestamp’: (datetime.datetime.now() – datetime.timedelta(hours=random.randint(0, 24))).isoformat(),
        ‘event_type’: random.choice([‘login_failure’, ‘malware_detected’, ‘suspicious_network’, ‘policy_violation’]),
        ‘source_ip’: f'{random.randint(1,255)}.{random.randint(1,255)}.{random.randint(1,255)}.{random.randint(1,255)}’,
        ‘severity’: random.choice([‘low’, ‘medium’, ‘high’, ‘critical’]),
        ‘description’: f’Sample security event {i}’
    }
    events.append(event)

with open(‘sample_security_events.json’, ‘w’) as f:
    for event in events:
        f.write(json.dumps(event) + ‘\n’)
“

echo “Security lab setup complete!”
echo “Access Splunk at http://localhost:8000 (admin/changeme)”
echo “Access Kibana at http://localhost:5601”
echo “Access WebGoat at http://localhost:8080/WebGoat”
echo “Access Juice Shop at http://localhost:3000”

Cloud Security Practice:

• AWS Free Tier – Practice cloud security configurations, implement security groups, CloudTrail, GuardDuty
• Azure Free Account – Configure Network Security Groups, Azure Security Center, Key Vault
• Google Cloud Credits – Set up Security Command Center, VPC security, Identity and Access Management
• Documentation – Create detailed implementation guides and security architecture diagrams

Challenge 3: Demonstrating Security ROI and Business Value

Problem: Difficulty quantifying the business value of security investments and demonstrating return on investment
Challenge: Security is often viewed as a cost center rather than business enabler
Solution: Develop frameworks for measuring and communicating security business value

Security Business Value Framework:

class SecurityROICalculator:
    def __init__(self):
        self.metrics = {
            ‘prevented_incidents’: 0,
            ‘compliance_cost_avoidance’: 0,
            ‘productivity_improvements’: 0,
            ‘reputation_protection’: 0
        }
   
    def calculate_breach_cost_avoidance(self, potential_breaches, avg_breach_cost):
        “””Calculate cost avoidance from prevented security breaches”””
        return potential_breaches * avg_breach_cost
   
    def calculate_compliance_roi(self, compliance_investment, penalty_avoidance, audit_cost_reduction):
        “””Calculate ROI from compliance initiatives”””
        total_benefits = penalty_avoidance + audit_cost_reduction
        roi_percentage = ((total_benefits – compliance_investment) / compliance_investment) * 100
        return {
            ‘investment’: compliance_investment,
            ‘benefits’: total_benefits,
            ‘roi_percentage’: roi_percentage,
            ‘payback_period_months’: (compliance_investment / (total_benefits / 12))
        }
   
    def calculate_productivity_impact(self, downtime_prevented_hours, avg_hourly_productivity_cost):
        “””Calculate productivity impact of security measures”””
        return downtime_prevented_hours * avg_hourly_productivity_cost
   
    def generate_security_scorecard(self, security_investments, business_outcomes):
        “””Generate executive security scorecard”””
        scorecard = {
            ‘total_security_investment’: sum(security_investments.values()),
            ‘quantified_benefits’: {
                ‘breach_cost_avoidance’: self.calculate_breach_cost_avoidance(
                    business_outcomes.get(‘prevented_breaches’, 0),
                    business_outcomes.get(‘avg_breach_cost’, 4200000)  # Average cost in INR
                ),
                ‘compliance_savings’: business_outcomes.get(‘compliance_cost_avoidance’, 0),
                ‘productivity_gains’: self.calculate_productivity_impact(
                    business_outcomes.get(‘downtime_prevented_hours’, 0),
                    business_outcomes.get(‘hourly_productivity_cost’, 5000)
                )
            },
            ‘risk_reduction’: {
                ‘vulnerability_reduction’: business_outcomes.get(‘vulnerabilities_remediated’, 0),
                ‘incident_frequency_reduction’: business_outcomes.get(‘incident_reduction_percentage’, 0),
                ‘mean_time_to_detection_improvement’: business_outcomes.get(‘mttd_improvement_hours’, 0),
                ‘mean_time_to_response_improvement’: business_outcomes.get(‘mttr_improvement_hours’, 0)
            }
        }
       
        # Calculate total ROI
        total_benefits = sum(scorecard[‘quantified_benefits’].values())
        total_investment = scorecard[‘total_security_investment’]
        scorecard[‘overall_roi’] = ((total_benefits – total_investment) / total_investment) * 100
       
        return scorecard

# Example usage for security program ROI analysis
def demonstrate_security_value():
    calculator = SecurityROICalculator()
   
    # Security investments over the year
    investments = {
        ‘siem_implementation’: 2500000,  # ₹25 lakhs
        ‘security_training’: 800000,    # ₹8 lakhs
        ‘vulnerability_management’: 1200000,  # ₹12 lakhs
        ‘incident_response_team’: 6000000,   # ₹60 lakhs
        ‘compliance_program’: 1500000    # ₹15 lakhs
    }
   
    # Business outcomes achieved
    outcomes = {
        ‘prevented_breaches’: 2,
        ‘avg_breach_cost’: 8500000,  # ₹85 lakhs average breach cost
        ‘compliance_cost_avoidance’: 3000000,  # ₹30 lakhs avoided in penalties
        ‘downtime_prevented_hours’: 500,
        ‘hourly_productivity_cost’: 8000,  # ₹8,000 per hour productivity cost
        ‘vulnerabilities_remediated’: 450,
        ‘incident_reduction_percentage’: 65,
        ‘mttd_improvement_hours’: 12,
        ‘mttr_improvement_hours’: 8
    }
   
    scorecard = calculator.generate_security_scorecard(investments, outcomes)
   
    return scorecard

# Generate executive report
security_scorecard = demonstrate_security_value()
print(f”Security Program ROI: {security_scorecard[‘overall_roi’]:.1f}%”)
print(f”Total Benefits: ₹{security_scorecard[‘quantified_benefits’][‘breach_cost_avoidance’]:,}”)

Challenge 4: Managing Security vs Usability Balance

Problem: Security measures often impact user productivity and system performance
Challenge: Implementing security controls that protect without hindering business operations
Solution: Risk-based security approach with user experience optimization

Balanced Security Implementation:

class SecurityUsabilityOptimizer:
    def __init__(self):
        self.risk_tolerance = {
            ‘low’: {‘security_level’: ‘high’, ‘usability_impact’: ‘significant’},
            ‘medium’: {‘security_level’: ‘medium’, ‘usability_impact’: ‘moderate’},
            ‘high’: {‘security_level’: ‘low’, ‘usability_impact’: ‘minimal’}
        }
   
    def assess_control_impact(self, control_type, user_group, data_sensitivity):
        “””Assess security control impact on user experience”””
        impact_matrix = {
            ‘mfa’: {
                ‘executives’: {‘friction’: ‘medium’, ‘adoption’: ‘high’},
                ‘developers’: {‘friction’: ‘low’, ‘adoption’: ‘high’},
                ‘general_users’: {‘friction’: ‘high’, ‘adoption’: ‘medium’}
            },
            ’email_filtering’: {
                ‘executives’: {‘friction’: ‘low’, ‘adoption’: ‘high’},
                ‘developers’: {‘friction’: ‘medium’, ‘adoption’: ‘medium’},
                ‘general_users’: {‘friction’: ‘low’, ‘adoption’: ‘high’}
            },
            ‘endpoint_protection’: {
                ‘executives’: {‘friction’: ‘medium’, ‘adoption’: ‘medium’},
                ‘developers’: {‘friction’: ‘high’, ‘adoption’: ‘low’},
                ‘general_users’: {‘friction’: ‘low’, ‘adoption’: ‘high’}
            }
        }
       
        return impact_matrix.get(control_type, {}).get(user_group, {})
   
    def design_adaptive_security(self, user_profile, access_context, risk_factors):
        “””Design adaptive security controls based on context”””
        base_score = 50  # Start with medium security
       
        # Adjust based on user profile
        if user_profile.get(‘role’) == ‘admin’:
            base_score += 20
        elif user_profile.get(‘role’) == ‘executive’:
            base_score += 15
       
        # Adjust based on access context
        if access_context.get(‘location’) == ‘outside_office’:
            base_score += 15
        if access_context.get(‘device_trust’) == ‘low’:
            base_score += 20
        if access_context.get(‘time’) == ‘outside_hours’:
            base_score += 10
       
        # Adjust based on risk factors
        base_score += risk_factors.get(‘recent_threats’, 0) * 5
        base_score += risk_factors.get(‘data_sensitivity’, 0) * 10
       
        # Determine security controls
        if base_score >= 80:
            return {
                ‘authentication’: ‘mfa_required’,
                ‘session_timeout’: 15,  # minutes
                ‘monitoring_level’: ‘high’,
                ‘access_restrictions’: [‘time_based’, ‘location_based’]
            }
        elif base_score >= 60:
            return {
                ‘authentication’: ‘mfa_optional’,
                ‘session_timeout’: 30,
                ‘monitoring_level’: ‘medium’,
                ‘access_restrictions’: [‘location_based’]
            }
        else:
            return {
                ‘authentication’: ‘standard’,
                ‘session_timeout’: 60,
                ‘monitoring_level’: ‘standard’,
                ‘access_restrictions’: []
            }
   
    def optimize_security_workflow(self, security_requirements, usability_constraints):
        “””Optimize security implementation for better user experience”””
        optimizations = []
       
        if ‘password_policy’ in security_requirements:
            if usability_constraints.get(‘user_complaints’) > 50:
                optimizations.append({
                    ‘change’: ‘implement_sso’,
                    ‘benefit’: ‘reduce_password_fatigue’,
                    ‘security_impact’: ‘maintain_or_improve’
                })
       
        if ’email_encryption’ in security_requirements:
            optimizations.append({
                ‘change’: ‘automatic_encryption_based_on_rules’,
                ‘benefit’: ‘transparent_to_users’,
                ‘security_impact’: ‘maintain’
            })
       
        return optimizations

# Example implementation
def implement_balanced_security():
    optimizer = SecurityUsabilityOptimizer()
   
    # Example user accessing sensitive data
    user_profile = {
        ‘role’: ‘financial_analyst’,
        ‘trust_level’: ‘medium’,
        ‘training_completed’: True
    }
   
    access_context = {
        ‘location’: ‘home_office’,
        ‘device_trust’: ‘medium’,
        ‘time’: ‘business_hours’,
        ‘network’: ‘vpn_connected’
    }
   
    risk_factors = {
        ‘recent_threats’: 2,  # Recent phishing attempts
        ‘data_sensitivity’: 8,  # Highly sensitive financial data
        ‘compliance_requirements’: [‘sox’, ‘pci’]
    }
   
    adaptive_controls = optimizer.design_adaptive_security(
        user_profile, access_context, risk_factors
    )
   
    return adaptive_controls

# Generate optimized security controls
security_controls = implement_balanced_security()
print(“Adaptive Security Controls:”, security_controls)