Hash-based signatures are quantum-resistant but have larger signature sizes.
- True
- False
Answer: True
SPHINCS+ uses hash functions believed quantum-resistant. Trade-off: larger signatures.
Hard Level – GK Questions
Free practice for SSC, UPSC, Banking & Railway exams. No login required.
Category
Difficulty
Type
Per page
The technique that enables training on encrypted data is called ________ Encryption.
- Bio-molecular / DNA
- Object
- Homomorphic
- Multimodal
Answer: Homomorphic
Homomorphic Encryption enables computation on ciphertext.
Which framework provides guidelines for securing IoT deployments?
- NIST IR 8259
- ETSI EN 303 645
- Both A and B
- Neither
Answer: Both A and B
NIST IR 8259 and ETSI EN 303 645 provide IoT security baselines: secure boot, updates, data protection.
Which DeFi risk arises from impermanent loss when providing liquidity to volatile trading pairs?
- Impermanent Loss
- Smart Contract Risk
- Oracle Manipulation
- All of these
Answer: Impermanent Loss
Impermanent loss occurs when token prices diverge, reducing value vs holding tokens. Critical risk for liquidity providers.
Which brain-inspired feature enables neuromorphic chips to process sparse data efficiently?
- Event-Driven Computation
- Spiking Neurons
- Both A and B
- Neither
Answer: Both A and B
Event-driven computation and spiking neurons enable efficient processing of sparse, temporal data.
The technology that uses cellular processes for computation is called ________ Computing.
- Cellular / Biological
- Multi-Task
- Homomorphic
- Edge
Answer: Cellular / Biological
Cellular computing uses biochemical reactions in cells for parallel computation. Early research stage.
Quantum annealing is suitable for optimization problems but not for general-purpose quantum computing.
- True
- False
Answer: True
Quantum annealing specializes in optimization via quantum tunneling. Different from gate-based universal quantum computing.
The technique that enables training on decentralized data without sharing raw datasets is called ________ Learning.
- Green
- Federated
- Artifact
- Microservices / RESTful
Answer: Federated
Federated Learning trains models across devices/servers holding local data, sharing only model updates.
Which DeFi mechanism enables borrowing against crypto collateral without credit checks?
- Yield Farming
- Collateralized Lending
- Liquidity Mining
- Staking
Answer: Collateralized Lending
Collateralized lending protocols allow borrowing by locking crypto collateral, with automatic liquidation if collateral value drops.
Which advantage do neuromorphic chips offer for always-on edge AI applications?
- High Precision
- Ultra-Low Power
- Large Memory
- Fast Clock
Answer: Ultra-Low Power
Neuromorphic chips achieve ultra-low power via event-driven, sparse computation. Critical for battery-powered edge AI.
The technology that uses neural networks implemented in biological tissue is called ________ Computing.
- End-to-End / Comprehensive
- Edge
- Wetware / Biological
- Searchable / Homomorphic
Answer: Wetware / Biological
Wetware computing uses biological neurons for computation. Early research stage with potential for ultra-low power AI.
The technique that enables training on encrypted data without decryption is called ________ Encryption.
- Protein / Molecular
- Homomorphic
- Multi-Task
- Wetware
Answer: Homomorphic
Homomorphic Encryption enables computation on ciphertext, producing encrypted results that decrypt to correct output.
The pattern that enables event-driven communication between microservices using message brokers is called ________ Architecture.
- Federated
- Event-Driven
- Green
- Inversion
Answer: Event-Driven
Event-driven architecture uses message brokers for asynchronous, decoupled service communication.
Which DeFi risk arises from price oracle manipulation that can trigger liquidations?
- Impermanent Loss
- Oracle Manipulation
- Smart Contract Risk
- All of these
Answer: Oracle Manipulation
Oracle manipulation feeds false prices to DeFi protocols, triggering incorrect liquidations or arbitrage. Critical vulnerability requiring decentralized, robust oracles.
Which application benefits most from neuromorphic computing's event-driven processing?
- Batch Data Processing
- Real-time Sensor Processing
- Offline Analytics
- Database Queries
Answer: Real-time Sensor Processing
Neuromorphic chips excel at processing sparse, event-driven data from sensors: vision, audio, IoT. Critical for edge AI with low power budgets.
The computing paradigm that uses DNA strands for parallel computation is called ________ Computing.
- End-to-End
- Cellular / Biological
- DNA / Molecular
- Edge
Answer: DNA / Molecular
DNA computing uses biochemical reactions for massive parallelism. Research stage with potential for solving complex combinatorial problems.
The technique that enables verification of model integrity without revealing model weights is called Zero-________ Proofs.
- Knowledge
- Model
- BharatKosh / e-Payments
- Code / Policy as Code
Answer: Knowledge
Zero-Knowledge Proofs enable proving model properties without revealing weights. Critical for privacy-preserving model verification.
Which DeFi mechanism allows users to earn yield by providing liquidity to trading pairs?
- Yield Farming
- Liquidity Mining
- Both A and B
- Neither
Answer: Both A and B
Yield farming/liquidity mining rewards users with tokens for providing liquidity to DEX pools. Critical DeFi incentive mechanism with impermanent loss risks.
Which brain-inspired feature do neuromorphic chips use for energy-efficient processing?
- Spiking Neurons
- Event-Driven Computation
- Both A and B
- Neither
Answer: Both A and B
Neuromorphic chips use spiking neurons that fire only when needed, and event-driven computation that processes only changes. Critical for edge AI efficiency.
The technology that uses proteins for computational tasks is called ________ Computing.
- Green / Energy-Efficient
- Compressed Air Energy / CAES
- Multimodal
- Protein / Molecular
Answer: Protein / Molecular
Protein computing uses biomolecular interactions for parallel computation. Research stage with potential for ultra-low power, massive parallelism.