RISC-V / SHAKTI Embedded Edge Platform

Overview

Our embedded platform leverages the open-source and sovereign capabilities of the SHAKTI RISC-V processors developed in India to create secure, AI-capable edge computing modules. Designed for harsh and mission-critical environments, this platform serves as the backbone for applications in aerospace, defense, industrial IoT, and space systems.

Core Capabilities

• Based on modular SHAKTI cores (E-class, C-class, I-class) enabling fine-grained control over power and performance.
• Supports lightweight AI inference (e.g., transformer variants for encryption, classification, and anomaly detection).
• Integrates secure boot, OTP memory, and JTAG lockdown for tamper-resistant firmware execution.
• Embedded hardware interfaces for I2C, UART, SPI, CAN, and PCIe to integrate seamlessly with edge sensors and systems.
• Optional cryptographic accelerators and secure co-processors for PQC, AES-256, SHA3, and RNG operations.

Use Cases

• Flight-critical edge compute modules in UAVs and combat aircraft.
• Secure battlefield IoT nodes with PUF-based identity and PQC-secured channels.
• Onboard telemetry processors in launch vehicles and satellites with fault-tolerant designs.
• Industrial automation nodes with edge analytics and encrypted machine-to-machine (M2M) communication.
• Cryptographic accelerators for sealed devices like CRYPTONIX, managing PUF keygen + AI sealing in hardware.

Why SHAKTI + RISC-V?

SHAKTI is India’s homegrown RISC-V processor family developed by IIT Madras. Its open instruction set architecture allows us to implement:

• Custom instruction extensions for AI and crypto
• Side-channel resistant logic for secure enclaves
• Deterministic, real-time operation with minimal power usage
• Nationally auditable, fully transparent hardware designs

Hardware Variants

• Edge Core Modules: SHAKTI I-class with 512KB RAM, crypto coprocessor, and Wi-Fi/BLE stack
• AI Embedded Units: SHAKTI C-class + Oblivion AI for real-time inference and encryption
• Secure Mesh Nodes: PUF-bound, PQC-booted devices for secure swarm or industrial mesh networking
• Rugged Units: Radiation-tolerant packaging with fault detection for space or combat deployment

Developer Support

We provide full toolchain access for developers and security engineers:

• RISC-V GCC toolchain and LLVM for firmware and drivers
• Secure boot templates and provisioning scripts (Oblivion + PUF keygen)
• Integration with TensorFlow Lite Micro / TVM for AI inference
• Support for secure communication stacks using Kyber, Dilithium, and AES-GCM

Roadmap: AI-Based Secure Key Distribution Device Using Shakti Processor

Leveraging India’s open-source Shakti RISC-V processor ecosystem enables the creation of fully indigenous, secure, and auditable cryptographic devices tailored for military and strategic communication. This section outlines how a key distribution node with embedded AI and hardware-level tamper protection can be built using Shakti SoCs.

Project Roadmap & Architecture

• Phase 1 – Feasibility & Simulation (0–2 months): Set up RTL simulations of Shakti C-Class or E-Class cores. Evaluate performance benchmarks for TinyML inference and TRNG handling.
• Phase 2 – Hardware Prototype (3–6 months): Use FPGA board or silicon-proven Shakti SoC (e.g., RIMO or VEGA board) to integrate TRNGs, AI model runtime, and secure storage modules.
• Phase 3 – Firmware & Encryption Stack (6–9 months): Build or port a lightweight RTOS (e.g., FreeRTOS or TockOS), implement symmetric encryption pipeline (AES-256, SHA-3, HMAC), and develop AI-based entropy validators (e.g., quantized LSTM).
• Phase 4 – Security Hardening (9–12 months): Add Secure Boot, PUF-based key storage, tamper sensors, power analysis resistance, and thermal obfuscation hardware.
• Phase 5 – Field Testing & Certification (12–18 months): Test for EMSEC, MIL-STD ruggedness, and battlefield survivability.

Software & Encryption Pipeline

• RTOS: TockOS or FreeRTOS customized for Shakti MMU-less or MMU-enabled cores.
• AI Runtime: TVM or TinyML runtime for quantized LSTM entropy estimators and anomaly classifiers.
• Crypto Libraries: Custom or audited libraries implementing AES-256, SHA-3, Blake2, Curve25519, and HMAC. OpenSSL-lite or BearSSL ports.
• Key Management Daemon: Handles generation, validation, storage, and expiration of symmetric keys based on AI risk scoring.
• Secure Bootloader: Verified chain of trust starting from ROM to kernel.

Hardware Hardening Features

• Tamper Sensors: Integrated light, temperature, voltage, and EM sensors detect intrusion and trigger secure key wipe.
• PUF Key Storage: Keys derived dynamically from SRAM or ring oscillator PUFs — never stored at rest.
• Secure Element Integration: Optional Indian-made SE or TPM with SPI interface for isolated key operations.
• Obfuscated PCB Design: Power-line encryption, decoy tracks, and non-uniform trace width for side-channel resistance.
• Redundant Watchdogs: Monitors for instruction injection or unexpected stack corruption.

Estimated Budget (Prototype Scale)

This AI-augmented secure key distribution node can become a foundational building block for indigenous defense-grade encryption systems, enabling secure mesh networks, unmanned combat platforms, and satellite uplinks — all on trusted silicon.