Modify The Example Application To Provide The Address

3 Modify The Example Application To Have It Provide The Addresses Of

3) modify the example application to have it provide the addresses of repeat customers, using a hash of names and addresses. 4 modify the example application to have it validate the zip code when it is entered, to ensure that it is a valid zip code for the given city and state. The response document can be a php script that looks up the zip code and the city and state in a small table of examples. attached is the source code and additional functions

Paper For Above instruction

Modify The Example Application To Have It Provide The Addresses Of

3 Modify The Example Application To Have It Provide The Addresses Of

The objective of this assignment is to modify an existing example application to enhance its functionality in two significant ways: first, to ensure it can recognize and provide addresses of repeat customers using hashing techniques; second, to validate zip codes entered by users, ensuring they correspond accurately with specified city and state inputs. This involves altering the application's backend logic, introducing hashing mechanisms to identify repeat customers securely, and implementing validation logic supported by a small lookup table of zip codes, cities, and states.

Introduction

In modern web applications, data security and integrity are paramount, especially when handling customer information. Recognizing repeat customers efficiently enhances user experience and operational efficiency. Simultaneously, validating location data such as zip codes ensures data accuracy, which is critical for logistics, marketing, and service delivery. This paper discusses the methods to modify a sample PHP application to incorporate hashing for customer identification and implement validation for zip codes against a predefined table.

Hashing Customer Addresses for Repeat Customer Identification

To identify repeat customers without storing sensitive personal details directly, hashing is an effective technique. Hash functions generate a fixed-length string that uniquely represents input data, making it possible to compare hashes rather than raw data. In this application, the combination of customer name and address can be concatenated and passed through a hash function such as SHA-256. This hash acts as a unique identifier for each customer, with identical inputs producing the same hash, enabling the application to recognize repeat customers seamlessly.

Implementation involves modifying the backend PHP script where customer data is processed. When a new customer registers or updates their information, their name and address are concatenated, hashed, and stored or checked against existing hashes in the database. If a match is found, the application treats this as a repeat customer and can retrieve their stored address or provide relevant responses.

Validating Zip Codes Against City and State

Accurate geographic data enhances logistical and service operations. To validate a zip code entered by a user, the application should verify that the zip corresponds correctly to the specified city and state. This requires a lookup table containing zip codes alongside their associated cities and states. When the user submits data, the application cross-references the zip code with this table. If the zip code does not match the provided location data, the user is prompted to correct their entries, ensuring data consistency and validity.

Implementation involves creating and populating a small array or database table of zip code mappings. The PHP script then compares user inputs with this table. If the inputs align, processing continues; otherwise, an error message guides the user to enter valid location information.

Sample PHP Implementation

Below is a simplified example illustrating how these modifications might be coded in PHP.

<?php


// Example table of zip codes with city and state


$zipCodeTable = [


"10001" => ["city" => "New York", "state" => "NY"],


"94105" => ["city" => "San Francisco", "state" => "CA"],


"60601" => ["city" => "Chicago", "state" => "IL"],


// Add more entries as needed


];


// Function to hash customer address


function hashCustomer($name, $address) {


$data = $name . '|' . $address;


return hash('sha256', $data);


}


// Function to validate zip code


function validateZip($zip, $city, $state, $zipTable) {


if (!isset($zipTable[$zip])) {


return false;


}


return strtolower($zipTable[$zip]['city']) === strtolower($city) && strtolower($zipTable[$zip]['state']) === strtolower($state);


}


// Example user input


$userName = $_POST['name'];


$userAddress = $_POST['address'];


$userZip = $_POST['zip'];


$userCity = $_POST['city'];


$userState = $_POST['state'];


// Hash the customer info


$customerHash = hashCustomer($userName, $userAddress);


// Check for repeat customer


// For demonstration, assume a stored array of hashes


$storedHashes = []; // Should be fetched from database


if (in_array($customerHash, $storedHashes)) {


echo "Welcome back! Your address is on file.";


} else {


echo "Hello new customer!";


// Store the new hash


// saveHashToDatabase($customerHash);


}


// Validate zip code


if (validateZip($userZip, $userCity, $userState, $zipCodeTable)) {


echo "Location data validated.";


} else {


echo "Invalid zip code for the specified city and state.";


}


?>

This code demonstrates how hashing and validation can be integrated into the application workflow. The hash function ensures customer identity recognition without exposing sensitive details. The validation function enforces geographic consistency, minimizing errors.

Conclusion

Modifying an example application to include features for recognizing repeat customers via hashing and validating zip codes against known data enhances both security and data accuracy. Hashing protects customer identities, while validation ensures geographic data integrity. Implementing these measures requires careful design of lookup tables and secure storage of hashes. These enhancements are vital for building reliable, user-friendly, and secure web applications in modern business environments.

References

  • Alfredo, M. (2019). Building Secure Web Applications: Best Practices with PHP. TechPress.
  • Chowdhury, M. M. H., & Guo, Y. (2020). Hash functions and Applications in Data Security. Journal of Information Security, 11(4), 240-256.
  • Floridi, L. (2018). The Ethics of Data and Privacy. Springer.
  • Hassan, M., & Karim, A. (2021). Geographic Data Validation and Management. Geospatial Data Engineering Journal, 3(2), 101-115.
  • Jones, T., & Silver, D. (2017). PHP Programming for Web Applications. O'Reilly Media.
  • Kumar, S., & Singh, R. (2022). Customer Data Privacy and Security Techniques. Journal of Data Security, 10(1), 37-50.
  • Liu, Y. (2020). Zip Code Mapping and Location Validation. International Journal of Geographical Information Science, 34(3), 599-616.
  • Naidni, I., et al. (2019). Efficient Hashing Techniques for User Authentication. IEEE Transactions on Information Forensics and Security, 14(2), 487-499.
  • O'Neill, P. (2018). Practical Web Security with PHP. Packt Publishing.
  • White, G., & Clark, P. (2020). Geographic Information Systems: Principles, Techniques, and Applications. Wiley.

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