While current internet standards implement TLS 1.3 (Transport Layer Security), we’ve made significant strides in securing communication over the internet. The journey began with the development of SSL (Secure Sockets Layer) 1.0, which was never publicly released due to serious flaws. This was followed by SSL 2.0, which introduced a handshake protocol before establishing a connection between the client and server. Every protocol has its own vulnerabilities, and to this day, no single protocol provides a completely secure solution. However, in cybersecurity, we continuously strive to develop ‘better’ solutions, recognising that while these may not be perfect, they are the best options available at present.
The SSL 2.0 handshake protocol aims to send ‘ClientHello’ from the client and ‘ServerHello’ from the server over an insecure channel, typically over a Transmission Control Protocol (TCP) connection. The purpose of these messages is to establish the parameters for the secure session that will follow, including negotiating the encryption methods and exchanging the necessary cryptographic data. This includes a ‘cipher suite’ which is a list of encryption algorithms such as RC4-MD5, DES-CBC-MD5, and RC2CBC-MD5 sent to the server to choose the most secure algorithm that both machines support, as shown in Figure 1.
The server responds with a ‘ServerHello’ message including the selected cipher suite, another random value (nonce), and the server’s certificate containing its public key. After these initial messages are exchanged, the process of key exchange and session establishment begins, and eventually, the communication is encrypted using the session key derived from the handshake process. This encryption secures subsequent data exchanges.
Key exchange methods
Esta historia es de la edición October 2024 de Open Source For You.
Comience su prueba gratuita de Magzter GOLD de 7 días para acceder a miles de historias premium seleccionadas y a más de 9,000 revistas y periódicos.
Ya eres suscriptor ? Conectar
Esta historia es de la edición October 2024 de Open Source For You.
Comience su prueba gratuita de Magzter GOLD de 7 días para acceder a miles de historias premium seleccionadas y a más de 9,000 revistas y periódicos.
Ya eres suscriptor? Conectar
Amazon Bedrock: A Boon for the Financial Services Industry
Amazon Bedrock is a fully managed service that provides access to foundation models from top AI providers, enabling organisations to build and scale generative AI applications. It is specifically designed to bring AI solutions to the financial sector. Let's explore all that it can do...
Quantum-Safe VPNs: The Future of Secure Communication
As quantum computing continues to advance, it poses a significant threat to traditional cryptographic algorithms that secure our digital communications. Virtual private networks (VPNs), which rely heavily on encryption, are particularly vulnerable. Quantum-safe VPNs utilise post-quantum cryptographic algorithms to protect against quantum attacks.
Popular Open Source Toolkits for Quantum Machine Learning
Quantum machine learning is becoming increasingly popular due to its ability to solve the complex problems of the AI age. Here are a few open source libraries and frameworks that help with quantum computations.
Quantum Computing: Harnessing Open Source for Innovation and Accessibility
We explore how open source initiatives are shaping the future of quantum computing, making it more accessible and driving innovation through collaboration.
How Quantum Computing Differs from Classical Computing
Despite being in its infancy, quantum computing has numerous potential applications in modelling, cybersecurity, AI/ML, and other fields. But how do quantum and classical computing compare with each other? Let's find out...
From Bits to Qubits: The Growth Story of Quantum Computing
Quantum computing may still be in the early stages of evolution, but its potential impact on everyday life is significant. We delve into the key concepts behind it, the reasons for its rapid growth, and how global advancements are shaping its future.
Pytket: A Comprehensive Guide to Quantum Circuit Design
Pytket stands out as a powerful toolkit in the realm of quantum computing, offering a suite of features that cater to both researchers and industry practitioners. Its key strengths include optimisation, platform-agnostic support, flexible quantum circuit design and hybrid algorithm support. These features make Pytket a versatile tool for various quantum computing applications, from machine learning and cryptography to optimisation problems in industrial settings.
Cirq: The Open Source Framework for Programming Quantum Computers
Explore the key features, capabilities, and impact of Cirq, an open source quantum computing framework developed by Google, on the quantum programming landscape.
The Role of Open Source in Accelerating Quantum AI
Here's an overview of how open source frameworks are being utilised to build quantum machine learning models, including quantum neural networks and quantum kernel methods. The challenges and future directions in the quantum AI landscape are also discussed.
Quantum Machine Learning: An Overview
Quantum machine learning (QML) is a burgeoning field at the intersection of quantum computing and artificial intelligence. In recent years, the integration of quantum mechanics with machine learning algorithms has sparked substantial interest among researchers and technologists alike. Here's a quick look at the essentials of creating quantum algorithms for AI models, their practical use cases on open source platforms, and best practices for implementing these advanced algorithms.
