World Conference on Cybersecurity, IoT, and Cloud Solutions LCICS on December 09-11, 2026 in Lisbon, Portugal
- Short Name: LCICS
- Event Type: Conference
- Website URL: https://ureng.urst.org/conference/185
- Contact E-mail: [email protected]
- Location: Lisbon, Portugal
- Date: December 09-11, 2026
- Organization: URENG
- Conference Tags: cloud computing cloud iot industrial cybersecurity cybersecurity
43rd LISBON World Conference on Cybersecurity, IoT, and Cloud Solutions (LCICS-26) scheduled on Dec. 9-11, 2026 Lisbon (Portugal) is for the scientists, scholars, engineers and students from the Universities all around the world and the industry to present ongoing research activities, and hence to foster research relations between the Universities and the industry. This conference provides opportunities for the delegates to exchange new ideas and application experiences face to face, to establish business or research relations and to find global partners for future collaboration. The conference is sponsored by Universal Researchers in Science & Technology (URST). All the submitted conference papers will be peer reviewed by the program/technical committees of the Conference.
Call for Papers: LCICS-26
All Abstracts, Reviews, short articles, Full articles, Posters are welcomed related with any of the following research fields:
1. Independent Core Topics
These represent the foundational pillars of each domain before they are integrated into a single solution.
A. Cybersecurity (The Shield)
Cryptography: Symmetric/asymmetric encryption, hashing, and digital signatures.
Network Security: Firewalls, VPNs, and Intrusion Detection/Prevention Systems (IDS/IPS).
Identity & Access Management (IAM): Multi-factor authentication (MFA) and Role-Based Access Control (RBAC).
Governance & Compliance: GDPR, HIPAA, and NIST frameworks.
Incident Response: Threat hunting, digital forensics, and disaster recovery.
B. Internet of Things (The Edge)
Hardware Architecture: Microcontrollers (MCUs), sensors, and actuators.
Connectivity Protocols: Zigbee, LoRaWAN, MQTT, and CoAP.
Embedded Systems: Real-time operating systems (RTOS) and firmware development.
Edge Computing: Local data processing to reduce latency before sending to the cloud.
C. Cloud Solutions (The Core)
Service Models: IaaS (Infrastructure), PaaS (Platform), and SaaS (Software).
Deployment Models: Public, Private, Hybrid, and Multi-Cloud.
Virtualization: Hypervisors, containers (Docker), and orchestration (Kubernetes).
Serverless Computing: Function-as-a-Service (FaaS) for scaling on-demand.
2. Interrelated & Convergent Subtopics
These are the specialized areas where the three fields overlap, creating unique challenges and solutions.
I. Secure Cloud-to-Thing Integration
Device Shadows & Digital Twins: Managing the virtual representation of an IoT device in the cloud securely.
Zero-Touch Provisioning: Automatically and securely onboarding thousands of devices to a cloud platform without manual intervention.
Certificate-Based Authentication: Using X.509 certificates to ensure that only authorized devices can talk to the cloud.
II. Advanced Threat Landscapes
IoT Botnets (e.g., Mirai): How compromised IoT devices are used to launch massive DDoS attacks against cloud infrastructures.
Side-Channel Attacks: Stealing encryption keys from IoT hardware by monitoring power consumption or electromagnetic leaks.
Cloud Misconfiguration: How a simple "open" S3 bucket can leak sensitive data collected by millions of IoT sensors.
III. Data Sovereignty & Privacy
End-to-End Encryption (E2EE): Ensuring data is encrypted at the sensor and only decrypted at the cloud application level, remaining unreadable even to the cloud provider.
Homomorphic Encryption: Performing computations on IoT data within the cloud without ever decrypting it.
Data Minimization at the Edge: Using edge computing to strip PII (Personally Identifiable Information) before data ever reaches the cloud.
IV. Modern Security Architectures
Zero Trust for IoT: Moving away from "trusted networks" to a model where every device and cloud request must be continuously verified.
Blockchain for Decentralized Identity: Using a distributed ledger to verify IoT device identities without a central cloud authority.
AI-Driven Anomaly Detection: Using cloud-based Machine Learning to analyze IoT traffic patterns and detect "strange" behavior (e.g., a smart lightbulb suddenly trying to access a database).
Name: URENG
Website: http://ureng.urst.org/
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