GK Questions

NIST SP 800-207 provides comprehensive Zero Trust guidance: identity verification, device trust, network segmentation, continuous monitoring.

Digital India Act aims to address: platform accountability, user rights, emerging tech governance, algorithmic transparency. Complements DPDP Act and IT Rules.

Panchamrit (five nectars) announced at COP26 includes: 500 GW non-fossil capacity, 50% energy from renewables, 1 billion tonne CO2 reduction, net-zero by 2070.

Chandrayaan-3's Vikram lander and Pragyan rover analyzed lunar soil near south pole, searching for water ice and studying surface composition.

UPI's success driven by interoperability, zero MDR, and innovation. Inspired similar systems globally: Singapore PayNow, UAE, France discussions.

Neuromorphic chips use spiking neurons that fire only when needed, and event-driven computation that processes only changes. Critical for edge AI with tight power budgets.

DNA data storage offers extreme density (exabytes/gram) and longevity (thousands of years). Research ongoing at IITs and global labs for archival applications.

QKD uses no-cloning theorem and measurement disturbance to detect eavesdropping. Provides provable security unlike computational security of classical cryptography.

Shor's Algorithm factors integers in polynomial time on quantum computers, threatening RSA encryption. Requires fault-tolerant quantum computers not yet available at scale.

DPDP Act 2023 establishes framework for processing digital personal data in India, with rights for data principals and obligations for data fiduciaries.

Right to Erasure (Article 17 GDPR) allows individuals to request deletion when data is no longer necessary, consent withdrawn, or processing unlawful. Critical privacy right.

GDPR requires explicit consent for special category data; ePrivacy Directive covers electronic communications. Both emphasize user control and transparency in data processing.

DP-SGD adds noise to gradients during training, providing mathematical privacy guarantees. Critical for training ML models on sensitive data while preventing membership inference.

Model inversion exploits model confidence scores to infer sensitive attributes of training data. Mitigation: differential privacy, output perturbation, access controls.

Adversarial defenses: adversarial training includes perturbed examples, defensive distillation smooths outputs, randomized smoothing adds noise. All improve robustness against adversarial attacks.

Container image scanning identifies known vulnerabilities, misconfigurations, and secrets in images before deployment. Critical for secure CI/CD pipelines in cloud-native environments.

Service mesh (Istio, Linkerd) automatically encrypts service-to-service traffic with mTLS, provides authentication, authorization, and observability without application code changes.

Kubernetes security: Pod Security Policies restrict privileges, Network Policies control traffic, Resource Limits prevent DoS. Combined for defense-in-depth in container environments.

Device posture assessment evaluates endpoint security: OS patches, antivirus status, encryption, compliance. Critical for Zero Trust access decisions in hybrid environments.

Micro-segmentation creates granular security policies around individual workloads/applications, containing breaches and preventing attackers from moving laterally across the network.