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The document covers foundational concepts in blockchain and cryptography, including symmetric and asymmetric cryptography, hash functions, and consensus algorithms like Proof-of-Work and Proof-of-Stake. It also discusses smart contracts, security concerns, and applications of blockchain beyond cryptocurrency. Additionally, it explores advanced algorithms and complexity theory, including algorithm design paradigms, graph algorithms, NP-completeness, and an introduction to quantum algorithms.

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6 views2 pages

Paragraph 4

The document covers foundational concepts in blockchain and cryptography, including symmetric and asymmetric cryptography, hash functions, and consensus algorithms like Proof-of-Work and Proof-of-Stake. It also discusses smart contracts, security concerns, and applications of blockchain beyond cryptocurrency. Additionally, it explores advanced algorithms and complexity theory, including algorithm design paradigms, graph algorithms, NP-completeness, and an introduction to quantum algorithms.

Uploaded by

asifrr.research
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© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Blockchain and Cryptography

4.1 Cryptographic Foundations

 Symmetric vs asymmetric cryptography.


 Hash functions (SHA-256), digital signatures (RSA, ECDSA).

4.2 Blockchain Basics

 Structure of a block, hash chaining.


 Distributed ledger and consensus.

4.3 Consensus Algorithms

 Proof-of-Work (PoW), Proof-of-Stake (PoS).


 Byzantine fault tolerance.

4.4 Smart Contracts

 Ethereum, Solidity programming.


 Decentralized applications (dApps).

4.5 Security and Privacy

 51% attacks, Sybil attacks.


 Zero-knowledge proofs, zk-SNARKs.

4.6 Applications Beyond Cryptocurrency

 Supply chain, healthcare, identity verification.

Advanced Algorithms and Complexity Theory

5.1 Algorithm Design Paradigms

 Greedy, divide-and-conquer, dynamic programming, backtracking.

5.2 Graph Algorithms

 BFS, DFS, Dijkstra, A*, Floyd-Warshall.


 Minimum spanning trees: Kruskal, Prim.

5.3 Approximation and Randomized Algorithms

 PTAS, FPTAS.
 Monte Carlo, Las Vegas algorithms.
5.4 NP-Completeness

 P vs NP, NP-complete and NP-hard problems.


 Reductions and Cook-Levin theorem.

5.5 Parameterized Complexity

 Fixed parameter tractability (FPT).


 Kernelization.

5.6 Online Algorithms and Streaming

 Competitive analysis.
 Count-min sketch, Bloom filters.

5.7 Quantum Algorithms (Intro)

 Qubits, superposition, Grover’s and Shor’s algorithms.

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