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AES Encryption Keys (password hashing)

AES Encryption Keys (password hashing) relies on a password of sufficient length and the non deterministic factor of indistinguishable random data. However, passwords as user inputs do not make for good encryption keys. To use passwords for encryption, a key derivation function must be applied which generates derived keys. Key derivation functions work by utilizing unique random salt to make pre-calculated rainbow tables infeasible. Furthermore, the salt should be stored with the password to ensure it is public, thus rendering the hash with the same password looking different. Weak keys refer to cryptographically secure generated keys, which makes an encryption algorithm vulnerable to an exploit.
For good encryption keys, a minimum length, determined by the AES encryption algorithm, is required. AES+CBC encryption necessitates a minimum length of 16 bytes, while AES+GCM can work with 12 bytes, although 16 bytes is suggested. To use passwords for encryption, a Key Derivation Function (KDF) is required to generate derived keys like argon2, bcrypt, and scrypt. Key derivation functions must be slow and some like argon2 are designed to take up a substantial amount of memory such that calculations on GPUs are not possible, to deter brute force attacks against offline stolen data.
Argon2 is considered the best KDF to use for password key derivation, with Argon2id being its most secure mode. Unfortunately, allot of encryption starts with user-supplied passwords, which are not random inputs of sufficient length making them 'easily' guessed by a bruteforce attack. To protect passwords from such attacks, the password's hash must not be stored and must be encrypted with the hash itself. Although offline bruteforce attacks on remote login systems are improbable, offline attacks on stolen data can be quite effective.
Weak keys, although generally not a concern in AES encryption, can pose a problem in the AES+GCM mode, which has several published papers on weak keys and can make the encryption algorithm vulnerable to an exploit. Ultimately, the GCM mode would best be used for anything with short-lived keys and not for disk encryption where keys and ciphers live longer. Another noteworthy point is that although salts are not secret and are public, they make pre-calculated rainbow tables infeasible and as such the salt should be stored with the password.
In conclusion, the use of derived keys in KDFs is a more secure way to encrypt data since passwords as user inputs do not make for good keys. However, even with a decent hashing algorithm and a random unique salt, it is still a possibility that your hash and salt may be exposed. As such, unique and strong passwords are recommended to prevent such password cracking attempts.

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Dev

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Quit programming right now

Many developers spend their free time working on non-commercial projects.
They do not receive monetary benefits, recognition, or easier job opportunities for these projects.
The motivation behind working on such projects can vary, including personal enjoyment, skill development, and building a portfolio.
However, some argue that without a clear goal or plan, it may be a waste of time and effort.

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Prodevelopertutorial

249

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Data structure tutorial 10: Implementation of Circular Queue using Linked List

Introduction to Circular Queue Data Structure
Implementation of Circular Queue using Linked List
Insertion [enqueue] operation can be visualized as increasing the rear pointer and keeping the front pointer still.
Deletion [dequeue] operation can be visualized as increasing the front pointer and keeping the rear pointer still.

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Medium

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History of Artificial Intelligence

The concept of smart machines has ancient foundations, dating back to philosophers like Aristotle.
Modern history of AI begins in the middle of the 20th century, with Alan Turing's paper on 'Computing Machinery and Intelligence.'
The 1956 Dartmouth Conference is a significant event where the term 'Artificial Intelligence' was coined.
Researchers like John McCarthy, Marvin Minsky, and Allen Newell aimed to simulate human problem-solving and reasoning in machines.

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Medium

319

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Singularity is something without an ego

The Singularity will require humans and AI to work symbiotically, with AI handling tasks that require computation, logic, and scalability, and humans contributing empathy, ethics, and creativity.
Traditional power structures — based on information control, authority, or economic dominance — will erode as AI democratizes knowledge and decision-making.
AI systems, especially when integrated into decentralized frameworks like Nostr and Bitcoin, will enhance humanity’s collective intelligence by connecting individuals and optimizing decision-making at scale.
AI could level the playing field, offering equal access to education, healthcare, and resources. This redistribution of opportunity could dissolve long-standing inequalities.

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Medium

206

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How I Created Stunning 8K Movies in Hours

AI MovieMaker is a tool that allows users to create ultra-realistic 8K cinematic films effortlessly.
Users can personalize scenes, graphics, and audio, streamlining the entire filmmaking process.
Many users report recovering their investment and making a profit by monetizing their videos.
The user-friendly interface and guided prompts make it easy for even beginners to create professional-grade content.

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Medium

407

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RxSignals: The most powerful synergy in the history of Angular

Angular has introduced tools to enable seamless interaction between Signals and observables.
Reactivity in Angular until the introduction of Signals relied on subscribing to observables within templates using the AsyncPipe, resulting in additional checks.
Signals are inherently stateful and offer additional benefits as compared to observables when managing state.
RxJS can be used to declaratively describe event-driven tasks, avoiding imperative code.
RxJS has naturally evolved into a reliable tool for handling events in combination with Signals.
Working with imperative APIs in a declarative manner is possible since Signals seamlessly integrate with observables.
RxJS excels by leveraging merging operators to reliably detect changes in an element's width and to create observables based on Angular's APIs.
By adapting frequent operations to work with streams, RxJS significantly reduces boilerplate code, making it more declarative.
The synergy between Signals and observables marks a significant step forward in Angular's reactivity, making state and event management in Angular more intuitive.
RxJS is perfectly suited for handling event-driven tasks and remains integrated into the Angular ecosystem.

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Prodevelopertutorial

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Data structure tutorial 9: Circular Queues Data structure introduction and Implementation using arrays.

Circular Queue uses a data structure (array or linked list) to allow insertion and removal of elements from both the ends (front and rear end).
In this article, we understand the introduction to Circular Queue Data Structure, Formula to calculate to insert elements, Understanding inserting elements with an example, and Implementation of Circular Queue using arrays.
In Circular Queue, the front will be pointing at 0 and rear pointer will be pointing at the maximum index size of the queue.
When an element is inserted at the rear end, rear_end = (rear_end + 1) % MAX_QUEUE_SIZE; similarly, when an element is deleted from front_ end front_end = (front_end + 1) % MAX_QUEUE_SIZE; are the formula to calculate the index.
Depending upon the result, the rear pointer will update accordingly.
Circular queue, we will be utilizing the space efficiently.
Data structure uses an array with operations Insert(), Delete(), Display().
The Insert() function adds an element at the rear end and Delete() function deletes element from the front end.
Display() function shows the content of the queue.
Code implementation of Circular Queue using arrays includes InsertQueue(), DeleteQueue(), and DisplayQueue() functions.

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Prodevelopertutorial

403

Data structure tutorial 8: Queue Data Structure implementation using linked list in C

Introduction to Queue Data Structure
Operations performed on Queue: Inserting elements into queue and Deleting elements from the queue
Implementation of Queue using Linked List in C
Output of the program

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Logrocket

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Building a full-featured Laravel admin dashboard with Filament

Filament is an open source library that provides a Laravel-based suite of UI components for creating admin dashboards.
Filament provides powerful admin dashboard components such as Form Builder, Notifications, Actions, etc.
The tutorial covers the process for building an admin dashboard with Filament UI components.
The tutorial explains Laravel environment setup, Installation of Filament, and creation of the database.
The use of Form Builder is demonstrated in creating a User form with validation, error handling, and conditional logic.
Notifications are implemented with Laravel Echo and Pusher to display real-time updates, and custom Actions are added for specific user tasks.
With Filament, powerful admin dashboards can be created that are interactive, reliable while keeping the code clean and easy to maintain.
Filament is developer-friendly and offers comprehensive solutions for building engaging, high-performance Laravel applications.
Explore Filament’s documentation to unlock more possibilities and create feature-rich admin dashboards.
Boost productivity and satisfaction with powerful and intuitive admin dashboards built using Filament and Laravel.

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Prodevelopertutorial

162

Data structure tutorial 6: Circular Doubly Linked List

Circular Doubly Linked List is discussed in this chapter.
Representation, operations, and implementation of Circular Doubly Linked List are covered.
Operations include insert rear, delete element, and display.
The code example demonstrates the implementation and output of the program.

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Prodevelopertutorial

Data structure tutorial 5: Circular Singly Linked List

In this chapter, we learn about Circular Singly Linked List.
Introduction to Circular Single Linked List.
Representation of Circular Single Linked List.
Operations performed on Circular Single Linked List.
Implementation of Circular Single Linked List.

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Dev

341

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This Runtime Meta-Programming Pattern in Python is Interesting

The current builder interface in the UI framework Zenaura was found to be complex and unappealing.
The goal was to simplify the interface and provide users with a cleaner syntax for creating UI elements.
A dynamically generated code approach was explored to achieve this, but it lacked auto-completion and usability.
The approach offers flexibility in adapting to changes in HTML tags, but usability is compromised.

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Dev

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Migrating from Azure Database for PostgreSQL to Neon

Azure Database for PostgreSQL can now be migrated easily to Neon, which offers serverless architecture, auto-scaling capabilities, and actual data storage billing. The migration process can be done using the utility tool pg_dump and pg_restore that can efficiently backup and restore a Postgres database. An accessible step-by-step guide is available for developers. Robust solutions that address scalability, complex dependencies, or strict security requirements are also available. Post-migration verification guarantees the integrity of data moved between the databases.
Azure Database for PostgreSQL offers the great Postgres features that many developers are familiar with while managing infrastructure for them. However, the fixed capacity that requires some overprovisioning could lead to heightened costs. Neon offers serverless architecture, which automatically scales compute resources to zero when idle and allows billing based on actual data size instead of provisioned capacity.
The step-by-step guide on how to easily migrate from Azure Database for PostgreSQL to Neon can be done by the tool pg_dump and pg_restore backed-up and restored a Postgres database that maintains dependencies and referential integrity. This process remains the most reliable way of migration, however, other options exist as well. For example, logical replication can be used for migrations of databases in the terabyte range.
Complex dependencies in Postgres that often create circular migration challenges include, for example, cross-schema references and custom extensions that don't have direct equivalents in the target system. A three-phase migration approach addresses the issue: pre-schema, schema, and post-schema. Security and Compliance-related challenges can be addressed by implementing a security-first migration pattern that includes tasks such as export and map of all roles and permissions.
The migration from Azure Database for PostgreSQL to Neon might take some planning, but the long-term advantages make it worthwhile. Neon's serverless architecture offers automatic scaling, capacity that matches real usage, and smarter cost efficiency.
Developers using Postgres features through Azure Database for PostgreSQL have the option to migrate to Neon's serverless architecture. The process is smooth, and robust solutions that address potential scalability, complex dependency, and strict security-related issues are also available. The migration options include logical replication and a three-stage migration approach method.
The method to migrate easily from Azure Database for PostgreSQL to Neon is using the utility tool pg_dump and pg_restore. Both backup and restore operations handle dependencies and referential integrity efficiently. Post-migration verification safeguards guarantee data integrity between the databases.
With Neon, one can enjoy Postgres features with the added benefits of serverless architecture, auto-scaling capabilities, and smarter cost efficiency. Migrating from Azure Database for PostgreSQL to Neon is an advantage worth taking, considering its familiar Postgres experience and convenience.
Large data volumes, complex dependencies, and compliance and security requirements create migration challenges when moving from Azure Database for PostgreSQL to Neon. Logical replication and a three-phase migration approach are viable solutions. A security-first migration pattern that addresses security policies, compliance requirements, audit logging, is a good practice to prevent unauthorized access during migration.
The step-by-step guide available for developers who need to migrate from Azure Database for PostgreSQL to Neon involves using the utility tool pg_dump and pg_restore, backed-up, and restored the Postgres database. The method maintains referential integrity and handles dependencies efficiently. Migrating to Neon offers smarter cost efficiency, serverless architecture, and automatic scaling capacity, providing a better user experience.
The migration from Azure Database for PostgreSQL to Neon opens up serverless architecture opportunities that are not available before. While the migration process requires careful planning, the long-term advantages are promising- like smarter cost efficiency, automatic scaling capacity, and better user experience.

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Prodevelopertutorial

192

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Data structure tutorial 4: Doubly Linked List [DLL]

Doubly Linked List is a special data structure, which is a collection of zero or more nodes.
Each node is made up of 3 parts, prev_link + data + next_link.
In a Doubly Linked List, we need to store the address information for the previous node and the next node.
The DLL operations include inserting an element at the rear, deleting an element with a given key value, searching for an element and displaying all the data.
The implementation of DLL includes defining structures for nodes, head pointer, and the 4 defined operations.
The C++ code presented inserts, deletes, searches and displays elements in a DLL.
When inserting elements at the rear, we check if head node is NULL.
If the head element is not NULL, we use the next pointer to move to the end of the list to add the element.
To delete an element we move the pointer temp to the element with that key, then update pointers for adjacent nodes before deleting the temp node.
To search an element we move the temp pointer to the head and check if the data is the same as key.

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