Cybersecurity threats are inevitable in a world that’s becoming more interconnected. Phishing attempts, ransomware, DDoS attacks, spyware, and supply chain attacks are more prevalent than they’ve ever been. Technologies like artificial intelligence and machine learning have also introduced new threats, such as deepfake and automated malware attacks. Fortunately, the same tech advancements offer new opportunities and solutions for legacy and emerging cybersecurity threats. Here’s an overview of new developments in cybersecurity technology and how effective they are at combating modern threats:
Behavioral Biometrics
While still in its infancy, behavioral biometrics offers a unique potential to boost cybersecurity. The technology uses machine learning to analyze user behavior, patterns, and interactions, including typing speed, cursor movement, and navigation. By learning how a user interacts with an account, the technology can detect suspicious activity when hackers gain access to the account, prompting instant OTP verifications and user notifications. The technology can be implemented across multiple digital platforms, including websites and mobile apps.
For instance, casino apps and websites can analyze user interactions after logging in. Most users will visit specific parts of the casinos, such as slots, roulettes, and other games they like, bonuses and promotions, or the cashier section. If a new person logs into the account, behavioral biometrics algorithms can quickly analyze the interaction and compare it with normal user activity. This helps to detect and combat unauthorized access autonomously. Behavioral biometrics can be implemented in any online platform or system involving user accounts.
Artificial Intelligence
Since 2023, the world has seen a proliferation of AI-powered tools that analyze massive amounts of data to detect patterns and make human-like decisions. With just a few prompts, generative AI can create codes, summaries, new content, images, and even videos in seconds. Machine learning analyzes existing records and real-time user interactions to learn the patterns, preferences, and decisions people make. Natural language processing allows machines to decipher and process human communications more efficiently.
AI technologies work together to analyze and predict potential threats much faster than humans and legacy solutions. AI-powered tools can also be programmed to notify authentic users, execute instant prompts, block traffic, and log users out of an account automatically. These actions enable prompt autonomous mitigation when someone hacks an account. Technologies like behavioral metrics analytics depend on AI and machine learning. AI can also make more accurate predictions and provide more accurate analysis and recommendations.
Blockchain Technology
Blockchain is still widely associated with cryptocurrencies because it is the foundational technology on which crypto coins are created. However, the technology has outgrown cryptocurrencies and is being used to democratize various services and operations, including cybersecurity. In fact, blockchain is one of the core tenets of Web 3.0, which is all about democratizing the internet. Blockchain creates decentralized databases that support the secure storage of data. The ledgers are also immutable, so no activity can be erased.
Blockchain can be used to develop cybersecurity tools that autonomously monitor networks to detect, flag, and block unauthorized activity. This is demonstrated by Certihash from Sentinel Node, a tool that takes snapshots of computer networks and files and then timestamps them to the BSV blockchain. By creating this database, the tool can detect unauthorized alterations and notify admins. Blockchain databases are also immutable, so hackers can’t erase their trail. This shortens the intrusion duration, which is important in mitigating the impact of cyberattacks.
Other Cybersecurity Technologies
Cybersecurity teams have many other technologies they can leverage to combat modern threats. Examples include post-quantum cryptography, zero trust architecture, and access control. Post-quantum cryptography allows users to leverage the augmented processing power of quantum computers without compromising RSA and ECC encryptions. Quantum computers use quantum mechanics to process data and solve complex problems at unprecedented speeds. This helps to facilitate the heavy-duty work done by cybersecurity systems and applications. However, quantum computing may pose encryption vulnerabilities.
Using quantum-resistant algorithms solves the problem, offering users faster speeds and secure communications in the same package. The zero-trust architecture also supports cybersecurity as it involves strict identity verification steps for users and devices trying to access a network. The model assumes no one can be trusted by default, even if they work within the company’s network. Access control uses tools like multi-factor authentications, such as OTP codes and email verifications, to protect user accounts. Other cybersecurity technologies include tools that can provide autonomous network audits, robust 5G network security, identity and access management, and data loss prevention.
Key Takeaways
Emerging technologies have the potential to resolve various cybersecurity issues. Technologies like artificial intelligence and blockchain are already being deployed to protect specific assets and resources from cyberattacks. However, most of these systems are novel and come with challenges of their own. Modern hackers can leverage the same AI capabilities to optimize and automate attacks, resulting in more sophisticated malware. For businesses and cybersecurity solutions providers, the challenge is to stay ahead of nefarious actors. This requires deploying robust security systems and automating updates to keep up with the latest threats.
