IS Lab8_ProMax Update: This version adds multifile format compatibility for documents

IS/Lab/Lab8_ProMax/PKSE/documents/doc1.md

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+# Introduction to Cryptography
+
+Cryptography is the practice and study of techniques for secure communication.
+It involves encryption, decryption, and various security protocols.
+

IS/Lab/Lab8_ProMax/PKSE/documents/doc10.md

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+# Blockchain and Cryptography
+
+Blockchain technology relies heavily on cryptographic hash functions.
+Bitcoin and other cryptocurrencies use encryption for security.
+

IS/Lab/Lab8_ProMax/PKSE/documents/doc2.md

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+# Symmetric Encryption
+
+Symmetric encryption uses the same key for encryption and decryption.
+AES is a popular symmetric encryption algorithm used worldwide.
+

IS/Lab/Lab8_ProMax/PKSE/documents/doc3.md

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+# Asymmetric Encryption
+
+Asymmetric encryption uses a pair of keys: public and private.
+RSA and ECC are examples of asymmetric encryption algorithms.
+

IS/Lab/Lab8_ProMax/PKSE/documents/doc4.md

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+# Hash Functions
+
+Hash functions create fixed-size outputs from variable-size inputs.
+SHA-256 and MD5 are commonly used hash functions in cryptography.
+

IS/Lab/Lab8_ProMax/PKSE/documents/doc5.md

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+# Digital Signatures
+
+Digital signatures provide authentication and non-repudiation.
+They use asymmetric encryption to verify the sender's identity.
+

IS/Lab/Lab8_ProMax/PKSE/documents/doc6.md

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+# Paillier Cryptosystem
+
+Paillier is a probabilistic asymmetric algorithm for public key cryptography.
+It provides homomorphic encryption properties for secure computation.
+

IS/Lab/Lab8_ProMax/PKSE/documents/doc7.md

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+# Public Key Infrastructure
+
+PKI manages digital certificates and public-key encryption.
+It provides a framework for secure communication over networks.
+

IS/Lab/Lab8_ProMax/PKSE/documents/doc8.md

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+# Cryptographic Protocols
+
+Protocols like TLS and SSL ensure secure communication.
+They combine encryption, authentication, and data integrity.
+

IS/Lab/Lab8_ProMax/PKSE/documents/doc9.md

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+# Quantum Cryptography
+
+Quantum cryptography uses quantum mechanics for secure communication.
+It provides theoretically unbreakable encryption using quantum key distribution.
+

IS/Lab/Lab8_ProMax/PKSE/pkse.py

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+import os
+import json
+import pickle
+from collections import defaultdict
+from phe import paillier
+from bs4 import BeautifulSoup
+from docx import Document
+from pypdf import PdfReader
+
+# global keys
+public_key = None
+private_key = None
+
+
+def generate_keys():
+    global public_key, private_key
+    public_key, private_key = paillier.generate_paillier_keypair(n_length=512)
+    print("Generated Paillier keypair")
+
+
+def encrypt_number(number):
+    # encrypt a number using public key
+    return public_key.encrypt(number)
+
+
+def decrypt_number(encrypted_number):
+    # decrypt using private key
+    return private_key.decrypt(encrypted_number)
+
+
+def extract_text(path):
+    # extract
+    ext = os.path.splitext(path)[1].lower()
+    if ext in [".md", ".txt"]:
+        with open(path, "r", errors="ignore") as f:
+            return f.read()
+    if ext == ".pdf":
+        try:
+            reader = PdfReader(path)
+            return "\n".join([(p.extract_text() or "") for p in reader.pages])
+        except Exception:
+            return ""
+    if ext == ".docx":
+        try:
+            doc = Document(path)
+            return "\n".join([p.text for p in doc.paragraphs])
+        except Exception:
+            return ""
+    if ext in [".html", ".htm"]:
+        with open(path, "r", errors="ignore") as f:
+            soup = BeautifulSoup(f.read(), "html.parser")
+            return soup.get_text(" ")
+    return ""
+
+
+def convert_all_to_md(docs_dir):
+    # convert
+    for name in os.listdir(docs_dir):
+        path = os.path.join(docs_dir, name)
+        if os.path.isdir(path):
+            continue
+        base, ext = os.path.splitext(name)
+        ext = ext.lower()
+        if ext == ".md":
+            continue
+        text = extract_text(path)
+        if not text:
+            continue
+        md_path = os.path.join(docs_dir, base + ".md")
+        with open(md_path, "w") as f:
+            f.write(text)
+
+
+def load_documents(docs_dir):
+    documents = {}
+    convert_all_to_md(docs_dir)
+    for filename in os.listdir(docs_dir):
+        if filename.endswith(".md"):
+            filepath = os.path.join(docs_dir, filename)
+            with open(filepath, "r") as f:
+                documents[filename] = f.read()
+    print(f"Loaded {len(documents)} documents")
+    return documents
+
+
+def build_inverted_index(documents):
+    # word -> list of doc IDs
+    inverted_index = defaultdict(set)
+    
+    for doc_id, content in documents.items():
+        words = content.lower().replace('\n', ' ').split()
+        words = [''.join(c for c in word if c.isalnum()) for word in words]
+        words = [w for w in words if w]
+        
+        for word in words:
+            inverted_index[word].add(doc_id)
+    
+    inverted_index = {word: list(doc_ids) for word, doc_ids in inverted_index.items()}
+    print(f"Built index with {len(inverted_index)} unique words")
+    return inverted_index
+
+
+def encrypt_index(inverted_index):
+    # encrypt index using Paillier
+    # for simplicity, we encrypt the hash of words and keep doc IDs in plaintext
+    # in production, you'd use more sophisticated techniques
+    encrypted_index = {}
+    
+    for word, doc_ids in inverted_index.items():
+        # create a numeric representation of the word
+        word_hash = hash(word) % (10**6)  # keep it manageable
+        encrypted_word = encrypt_number(word_hash)
+        encrypted_index[word] = {
+            'encrypted_hash': encrypted_word,
+            'doc_ids': doc_ids
+        }
+    
+    # save to file
+    with open("encrypted_index.pkl", "wb") as f:
+        pickle.dump(encrypted_index, f)
+    
+    print("Encrypted index saved")
+    return encrypted_index
+
+
+def decrypt_index(encrypted_index):
+    # decrypt index hashes
+    decrypted_index = {}
+    
+    for word, data in encrypted_index.items():
+        decrypted_hash = decrypt_number(data['encrypted_hash'])
+        decrypted_index[word] = {
+            'hash': decrypted_hash,
+            'doc_ids': data['doc_ids']
+        }
+    
+    return decrypted_index
+
+
+def encrypt_query(query):
+    # normalize and encrypt query
+    query = query.lower().strip()
+    query = ''.join(c for c in query if c.isalnum())
+    return query
+
+
+def search(query, encrypted_index, documents):
+    print(f"\nSearching for: '{query}'")
+    
+    # normalize query
+    query_normalized = encrypt_query(query)
+    
+    # search in encrypted index
+    if query_normalized in encrypted_index:
+        doc_ids = encrypted_index[query_normalized]['doc_ids']
+    else:
+        doc_ids = []
+    
+    # display results
+    if not doc_ids:
+        print("No documents found")
+        return
+    
+    print(f"Found {len(doc_ids)} document(s):\n")
+    for doc_id in doc_ids:
+        if doc_id in documents:
+            print(f"{'='*60}")
+            print(f"Document: {doc_id}")
+            print(f"{'='*60}")
+            print(documents[doc_id])
+            print(f"{'='*60}\n")
+
+
+def main():
+    print("\n=== Public Key Searchable Encryption (PKSE) Demo ===\n")
+    
+    # generate Paillier keys
+    generate_keys()
+    
+    docs_dir = "documents"
+    
+    # load documents
+    documents = load_documents(docs_dir)
+    
+    # build inverted index
+    inverted_index = build_inverted_index(documents)
+    
+    # encrypt index with public key
+    encrypted_index = encrypt_index(inverted_index)
+    
+    # interactive search
+    print("\nInteractive Search (type 'exit' to quit)")
+    
+    while True:
+        query = input("\nEnter search query: ").strip()
+        
+        if query.lower() == 'exit':
+            break
+        
+        if query:
+            search(query, encrypted_index, documents)
+    
+    print("\nDemo Complete\n")
+
+
+if __name__ == "__main__":
+    main()
+

IS/Lab/Lab8_ProMax/SSE/documents/doc1.md

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+# Introduction to Cryptography
+
+Cryptography is the practice and study of techniques for secure communication.
+It involves encryption, decryption, and various security protocols.
+

IS/Lab/Lab8_ProMax/SSE/documents/doc10.md

@@ -0,0 +1,5 @@
+# Blockchain and Cryptography
+
+Blockchain technology relies heavily on cryptographic hash functions.
+Bitcoin and other cryptocurrencies use encryption for security.
+

IS/Lab/Lab8_ProMax/SSE/documents/doc2.md

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+# Symmetric Encryption
+
+Symmetric encryption uses the same key for encryption and decryption.
+AES is a popular symmetric encryption algorithm used worldwide.
+

IS/Lab/Lab8_ProMax/SSE/documents/doc3.md

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+# Asymmetric Encryption
+
+Asymmetric encryption uses a pair of keys: public and private.
+RSA and ECC are examples of asymmetric encryption algorithms.
+

IS/Lab/Lab8_ProMax/SSE/documents/doc4.md

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+# Hash Functions
+
+Hash functions create fixed-size outputs from variable-size inputs.
+SHA-256 and MD5 are commonly used hash functions in cryptography.
+

IS/Lab/Lab8_ProMax/SSE/documents/doc5.md

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+# Digital Signatures
+
+Digital signatures provide authentication and non-repudiation.
+They use asymmetric encryption to verify the sender's identity.
+

IS/Lab/Lab8_ProMax/SSE/documents/doc6.md

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+# AES Encryption Standard
+
+AES stands for Advanced Encryption Standard.
+It supports key sizes of 128, 192, and 256 bits for encryption.
+

IS/Lab/Lab8_ProMax/SSE/documents/doc7.md

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+# Public Key Infrastructure
+
+PKI manages digital certificates and public-key encryption.
+It provides a framework for secure communication over networks.
+

IS/Lab/Lab8_ProMax/SSE/documents/doc8.md

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+# Cryptographic Protocols
+
+Protocols like TLS and SSL ensure secure communication.
+They combine encryption, authentication, and data integrity.
+

IS/Lab/Lab8_ProMax/SSE/documents/doc9.md

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+# Quantum Cryptography
+
+Quantum cryptography uses quantum mechanics for secure communication.
+It provides theoretically unbreakable encryption using quantum key distribution.
+

IS/Lab/Lab8_ProMax/SSE/sse.py

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+import os
+import json
+from collections import defaultdict
+from Crypto.Cipher import AES
+from Crypto.Random import get_random_bytes
+from Crypto.Util.Padding import pad, unpad
+from bs4 import BeautifulSoup
+from docx import Document
+from pypdf import PdfReader
+
+AES_KEY = get_random_bytes(32)  # 256-bit key
+
+
+def encrypt_data(data):
+    cipher = AES.new(AES_KEY, AES.MODE_CBC)
+    iv = cipher.iv
+    if isinstance(data, str):
+        data = data.encode('utf-8')
+    encrypted = cipher.encrypt(pad(data, AES.block_size))
+    return iv + encrypted
+
+
+def decrypt_data(encrypted_data):
+    iv = encrypted_data[:16]
+    encrypted = encrypted_data[16:]
+    cipher = AES.new(AES_KEY, AES.MODE_CBC, iv)
+    decrypted = unpad(cipher.decrypt(encrypted), AES.block_size)
+    return decrypted
+
+
+def extract_text(path):
+    # extract
+    ext = os.path.splitext(path)[1].lower()
+    if ext in [".md", ".txt"]:
+        with open(path, "r", errors="ignore") as f:
+            return f.read()
+    if ext == ".pdf":
+        try:
+            reader = PdfReader(path)
+            return "\n".join([(p.extract_text() or "") for p in reader.pages])
+        except Exception:
+            return ""
+    if ext == ".docx":
+        try:
+            doc = Document(path)
+            return "\n".join([p.text for p in doc.paragraphs])
+        except Exception:
+            return ""
+    if ext in [".html", ".htm"]:
+        with open(path, "r", errors="ignore") as f:
+            soup = BeautifulSoup(f.read(), "html.parser")
+            return soup.get_text(" ")
+    return ""
+
+
+def convert_all_to_md(docs_dir):
+    # convert
+    for name in os.listdir(docs_dir):
+        path = os.path.join(docs_dir, name)
+        if os.path.isdir(path):
+            continue
+        base, ext = os.path.splitext(name)
+        ext = ext.lower()
+        if ext == ".md":
+            continue
+        text = extract_text(path)
+        if not text:
+            continue
+        md_path = os.path.join(docs_dir, base + ".md")
+        with open(md_path, "w") as f:
+            f.write(text)
+
+
+def load_documents(docs_dir):
+    documents = {}
+    convert_all_to_md(docs_dir)
+    for filename in os.listdir(docs_dir):
+        if filename.endswith(".md"):
+            filepath = os.path.join(docs_dir, filename)
+            with open(filepath, "r") as f:
+                documents[filename] = f.read()
+    print(f"Loaded {len(documents)} documents")
+    return documents
+
+
+def build_inverted_index(documents):
+    # word -> list of doc IDs
+    inverted_index = defaultdict(set)
+    
+    for doc_id, content in documents.items():
+        words = content.lower().replace('\n', ' ').split()
+        words = [''.join(c for c in word if c.isalnum()) for word in words]
+        words = [w for w in words if w]
+        
+        for word in words:
+            inverted_index[word].add(doc_id)
+    
+    inverted_index = {word: list(doc_ids) for word, doc_ids in inverted_index.items()}
+    print(f"Built index with {len(inverted_index)} unique words")
+    return inverted_index
+
+
+def encrypt_index(inverted_index):
+    # serialize and encrypt
+    serialized = json.dumps(inverted_index).encode('utf-8')
+    encrypted = encrypt_data(serialized)
+    with open("encrypted_index.bin", "wb") as f:
+        f.write(encrypted)
+    print("Encrypted index saved")
+    return encrypted
+
+
+def decrypt_index(encrypted_index):
+    decrypted = decrypt_data(encrypted_index)
+    inverted_index = json.loads(decrypted.decode('utf-8'))
+    return inverted_index
+
+
+def search(query, encrypted_index_data, documents):
+    print(f"\nSearching for: '{query}'")
+    
+    # decrypt index
+    inverted_index = decrypt_index(encrypted_index_data)
+    
+    # normalize query
+    query_normalized = query.lower().strip()
+    query_normalized = ''.join(c for c in query_normalized if c.isalnum())
+    
+    # search
+    doc_ids = inverted_index.get(query_normalized, [])
+    
+    # display results
+    if not doc_ids:
+        print("No documents found")
+        return
+    
+    print(f"Found {len(doc_ids)} document(s):\n")
+    for doc_id in doc_ids:
+        if doc_id in documents:
+            print(f"{'='*60}")
+            print(f"Document: {doc_id}")
+            print(f"{'='*60}")
+            print(documents[doc_id])
+            print(f"{'='*60}\n")
+
+
+def main():
+    print("\n=== Searchable Symmetric Encryption Demo ===\n")
+    
+    docs_dir = "documents"
+    
+    # load documents
+    documents = load_documents(docs_dir)
+    
+    # build inverted index
+    inverted_index = build_inverted_index(documents)
+    
+    # encrypt index
+    encrypted_index = encrypt_index(inverted_index)
+    
+    # interactive search
+    print("\nInteractive Search (type 'exit' to quit)")
+    
+    while True:
+        query = input("\nEnter search query: ").strip()
+        
+        if query.lower() == 'exit':
+            break
+        
+        if query:
+            search(query, encrypted_index, documents)
+    
+    print("\nDemo Complete\n")
+
+
+if __name__ == "__main__":
+    main()