Vulnerable Implementation for Unordered Map
A simple code snippet illustrates the vulnerability by measuring execution time for different primes:
#include <ctime>
#include <iostream>
#include <unordered_map>
const int N = 2e5;
void insert_numbers(long long x)
{
clock_t begin = clock();
std::unordered_map<long long, int> numbers;
for (int i = 1; i <= N; i++)
numbers[i * x] = i;
long long sum = 0;
for (const auto& entry : numbers)
sum += (entry.first / x) * entry.second;
std::cout << "x = " << x << ": " << std::fixed
<< static_cast<double>(clock() - begin) / CLOCKS_PER_SEC
<< " seconds, sum = " << sum << "\n";
}
int main()
{
insert_numbers(107897);
insert_numbers(126271);
return 0;
}
// Note: differences in language semantics, standard libraries, data structure
//implementations, and time measurement mechanisms can lead to
//variations in execution time and output.
import java.util.HashMap;
import java.util.Map;
public class Main {
static final int N = 200000;
static void insertNumbers(long x) {
long startTime = System.nanoTime();
Map<Long, Integer> numbers = new HashMap<>();
for (int i = 1; i <= N; i++) {
numbers.put((long) i * x, i);
}
long sum = 0;
for (Map.Entry<Long, Integer> entry : numbers.entrySet()) {
sum += (entry.getKey() / x) * entry.getValue();
}
double elapsedTime = (System.nanoTime() - startTime) / 1e9;
System.out.printf("x = %d: %.6f seconds, sum = %d%n", x, elapsedTime, sum);
}
public static void main(String[] args) {
insertNumbers(107897);
insertNumbers(126271);
}
}
// Note: differences in language semantics, standard libraries, data structure
//implementations, and time measurement mechanisms can lead to
//variations in execution time and output.
import time
N = int(2e5)
def insert_numbers(x):
# Measure the start time
begin = time.time()
# Initialize an empty dictionary to store numbers and their corresponding indices
numbers = {}
# Populate the dictionary with numbers and their indices
for i in range(1, N + 1):
numbers[i * x] = i
# Initialize sum
sum_val = 0
# Calculate the sum by iterating through the dictionary
for key, value in numbers.items():
sum_val += (key // x) * value
# Calculate the time taken and print the result using the format method
print("x = {}: {:.6f} seconds, sum = {}".format(x, time.time() - begin, sum_val))
def main():
# Call insert_numbers function with different values of x
insert_numbers(107897)
insert_numbers(126271)
if __name__ == "__main__":
main()
# Note: differences in language semantics, standard libraries, data structure
# implementations, and time measurement mechanisms can lead to
# variations in execution time and output.
using System;
using System.Collections.Generic;
using System.Diagnostics;
public class Program
{
const int N = 200000;
// Method to insert numbers into a dictionary and calculate sum
static void InsertNumbers(long x)
{
// Start measuring time
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
// Dictionary to store key-value pairs
Dictionary<long, int> numbers = new Dictionary<long, int>();
// Insert numbers into the dictionary
for (int i = 1; i <= N; i++)
{
numbers[i * x] = i;
}
// Variable to store the sum
long sum = 0;
// Calculate sum using dictionary entries
foreach (var entry in numbers)
{
sum += (entry.Key / x) * entry.Value;
}
// Stop measuring time
stopwatch.Stop();
// Output the result
Console.WriteLine($"x = {x}: {stopwatch.Elapsed.TotalSeconds} seconds, sum = {sum}");
}
// Main method, entry point of the program
public static void Main(string[] args)
{
// Call InsertNumbers method with different values
InsertNumbers(107897);
InsertNumbers(126271);
}
}
// Note: differences in language semantics, standard libraries, data structure
//implementations, and time measurement mechanisms can lead to
//variations in execution time and output.
// Import the 'performance-now' module to measure time in milliseconds
const { performance } = require('perf_hooks');
const N = 2e5;
// Function to insert numbers into a dictionary and calculate their sum
function insertNumbers(x) {
// Measure the start time
const begin = performance.now();
// Initialize an empty object to store numbers and their corresponding indices
const numbers = {};
// Populate the object with numbers and their indices
for (let i = 1; i <= N; i++) {
numbers[i * x] = i;
}
// Initialize sum
let sum = 0;
// Calculate the sum by iterating through the object
for (const key in numbers) {
sum += Math.floor(key / x) * numbers[key];
}
// Calculate the time taken and print the result using the 'toFixed' method
console.log(`x = ${x}: ${(performance.now() - begin).toFixed(6)} milliseconds, sum = ${sum}`);
}
// Main function
function main() {
// Call insertNumbers function with different values of x
insertNumbers(107897);
insertNumbers(126271);
}
// Call the main function to execute the code
main();
// Note: differences in language semantics, standard libraries, data structure
//implementations, and time measurement mechanisms can lead to
//variations in execution time and output.
Output:
x = 107897: 0.062000 seconds, sum = 2666686666700000
x = 126271: 56.123000 seconds, sum = 2666686666700000
Optimization for Unordered Map O(1) operations
C++ provides convenient data structures like std::set and std::map, tree-based structures with operations taking O(log n) time. With C++11, hash-based alternatives were introduced: std::unordered_set and std::unordered_map. However, concerns arise regarding potential vulnerabilities and efficiency in real-world scenarios. In this article, we’re going to explore strategies to optimize unordered maps for O(1) operations and address security issues.
Table of Content
- Implementation of Unordered Map
- Understanding Vulnerabilities of Unordered Map
- Vulnerable Implementation for Unordered Map
- Secure Unordered Map from Collision Attacks
- Better Implementation of Unordered Map
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