Blockchain has appeared as the revolutionary database technology to take the world by storm. Artificial Intelligence (AI), on the other hand, is slowly transforming the human interactions with tech solutions and tech-driven business realities by facilitating automation and machine-led interactions. Both are also playing a crucial role in the way for most complete and impenetrable security solutions for digital applications.
The role of Blockchain and AI in strengthening cybersecurity has already been established. Here we are going to explain the key ways AI and Blockchain together are ensuring the strongest cybersecurity measures.
Decentralized Way of Reducing Cyberattacks
Blockchain has been particularly effective in combating the most common cybersecurity attacks called DNS attacks. As soon as a user request comes to the browser, it is transmitted to other networked computers referred to as Domain Naming System (DNS). DNS works as the contact repository or phonebook for the web that helps the browser connect to the intended server. Now since DNS servers generally remain centralized, they are often targeted by malicious programs and hackers. This is where the Blockchain decentralized database system can play a savior's role by distributing the DNS systems across blocks of data.
Thanks to the decentralized database and multiple layers of Blockchain technology, the risk factors can also be reduced, and phishing attacks can be kept at bay. Moreover, the encrypted data of Blockchain that requires a strong identity verification through data mining further strengthens the security to the optimum and reduces the security vulnerabilities to a negligible level.
Blockchain for IoT Security
The Internet of Things (IoT), with its connected ecosystem of devices, emerges as one of the most attack prone and vulnerable areas for cybersecurity. The decentralized and often scattered devices spread across different premises and environments can be easy targets for cyberattacks, and this is where the Blockchain-based decentralized database management can play a significant role in safeguarding the IoT data.
To deal with this risk of accommodating distributed devices and their data, Blockchain technology comes as the solution. In more than one way, both Blockchain and IoT are complementary to each other. The former helps manage IoT data in a decentralized manner with strong encryption and tamper-proof "no rewrite" protocol. Since using IoT botnets many Distributed Denial of Server (DDoS) attacks are launched, Blockchain distributed database can play an efficient role in reducing the security risks.
Machine Learning For Detecting Cyber-Attacks and Vulnerabilities
In dealing with cyber-attacks and security vulnerabilities, time is crucial, and companies need to take advanced steps and measures before such attacks actually can penetrate deeper. Machine learning, a subset of artificial intelligence (AI) technology, has shown great promise in detecting the security threats in advance by analyzing the user behavior data.
Machine Learning technology makes computers capable of utilizing algorithms based on the data they receive and the learning they make from this data. Machine learning technology by analyzing the computer data and various metrics can easily detect the anomalies and irregularities, triggering the security risks in systems and can take proactive measures to stop these risks.
It has been that machine learning technology has been more effective and efficient in detecting security threats and vulnerabilities more precisely than other humans. While traditional security systems depend heavily on past data, machine learning algorithms are more effective as they rely more on real-time data on security glitches and loopholes.
AI-Based Smart Authentication
One of the most fragile components that keep taking center stage in the discourse on the evolving security loopholes is the passwords and user authentication that tend to be very fragile. Weak passwords have always been considered to be the most significant weak link that various cyber attackers and malicious elements utilize to their heart's content. This is where the role of AI appears to be important to strengthen authentication by using various intelligent measures.
The security loopholes corresponding to the user authentication keep taking new forms. While face recognition was earlier thought to be full-proof, the shortcomings of this technology have become too apparent. Just a change of hairstyle and just by donning a pair of sunglasses or hats can lead to the non-recognition of a registered user. The hackers can use your pic sourced from social media profiles for circumventing the barriers of face recognition.
To mitigate such security risks corresponding to the authentication, developers are noir using biometric technologies ranging from fingerprint scanning to recognizing intricate and detailed facial features through inbuilt sensors and neural engines to mapping the retina pixels of the user's eyes. As of now, these kinds of detailed biometric data remained to be secure from hackers and malicious intrusions.
AI-ML for Controlling Phishing Attacks
A common and dangerous cyberattack that security experts need to deal with is the phishing attack. In this cyber-attack method, the attackers just transfer their payload. Phishing emails are a very common source of cyber-attacks. Both AI and Machine Learning plays a great role in preventing and deterring such phishing attacks.
Thanks to the AI-ML technologies, faster detection of the malicious sources of attacks can be easily detected, and proactive measures to nullify such attacks can be taken. AI and ML technologies can easily differentiate the real email and websites from the fake ones.
Conclusion
From the above elucidation, the role of Blockchain and AI in strengthening cybersecurity and reducing security threats can easily be assessed. In the years to come, these two technologies will be the mainstay in any strategy for cybersecurity.
