The Unlikely Entanglements Between Web3, DDoS and AI

They are all tech terms. This is probably what most people would say when asked about the connections between Web3, AI, and DDoS. These are some of the most common terms in modern IT. The first two are often mentioned as part of the pitches for innovative products. The third is a common term in the field of cybersecurity.

These three buzzwords are entangled in an uncouth web that may not be what you would expect. The connections are not that apparent, but they are worth examining to be ready for the risks that come at the intersection of Web3, artificial intelligence, and DDoS.

The Unlikely Entanglements Between Web3, DDoS and AI

Web3 and DDoS

Web3 represents an evolution of the internet mainly characterized by the use of new technologies and paradigms that are different from what was conventional. It involves the use of blockchain technology, token-based economics, and decentralized transactions and control over the major tech assets.

For context, the internet started with static web pages (Web 1.0) then advanced to an internet with greater user interactions through social media platforms, video streaming, and the ability to post user-generated content (Web 2.0), Web3 promises greater user control, the democratization of processes, and more advanced technologies.

There may be some misconception that decentralization in Web3 makes it less prone to a DDoS attack. However, in reality, Web3 systems are just as prone to DDoS as other online systems being offered to the public.

The front-end or customer-facing systems of Web3 organizations (the website or app) are the same as those of conventional operations. Hence, they are affected by and defended against DDoS in the same way.

The bigger problem is that there is a tendency among Web3 companies to be less secure since they are still acclimating to new technologies and processes. They are likely to focus more on their operations, so they end up with security issues particularly when it comes to security visibility and attack surface management.

Sophisticated cybercriminals can employ DDoS as a smokescreen to launch more critical attacks such as account takeovers and the introduction of ransomware.

It is also possible for Web3 organizations to have vulnerabilities in their systems that allow threat actors to install malware into devices and turn these devices into DDoS botnets.

In other words, a DDoS attack can be used as a concealment to discreetly make an organization’s devices part of a DDoS botnet.

There are still no documented incidents of this relationship between Web3 and DDoS but this theoretical scheme is indubitably viable. There were already reported cases of DDoS being used as a smokescreen attack.

Meanwhile, some pundits are raising concerns over Web3 projects allegedly not taking cybersecurity seriously. It’s only a matter of time before the risks intertwine and spoil the progress of Web3 adoption.

Web3 and AI

Artificial intelligence is usually not named as one of the technologies involved in Web3. However, it can be easily integrated to enhance various Web3 projects. For example, AI is the tech behind autonomous agents used to enhance smart contracts.

These agents automate complex processes, execute transactions, and provide personalized services autonomously. They can also engage in negotiations, minimizing the need for intermediaries.

Additionally, AI can be used to create personalized interactions in games, marketplaces, and other platforms where users can interact with smart bots to conduct transactions.

The Ethereum-based decentralized Web3 market prediction service Augur, for example, uses AI to analyze data and provide insights or guides to users to help them make informed decisions on their trades.

Similarly, the “tokenized AI and data” site Ocean Protocol facilitates the development of decentralized autonomous organizations (DAOs) to automate processes for businesses like in the case of identifying process bottlenecks and demand predictions.

Also, Medibloc, a Web3 healthcare platform, utilizes smart contracts with AI to provide personalized treatment advice, data analysis, and a secure way for healthcare data sharing.

It is also worth noting that AI plays an important role in the security and privacy of Web3 systems. AI enhances cybersecurity tools to detect and prevent threats beyond threat signatures or threat intelligence.

It can analyze behaviors or activity patterns to spot potentially malicious actions. It can also bolster security visibility through automated and continuous security scans or vulnerability detection routines.

However, AI can also be a tool for threat actors. It can automate vulnerability detection and exploitation. It can be used to rapidly create malware and come up with modified versions of existing malware to evade detection.

Additionally, artificial intelligence can be used to optimize DDoS attacks, enable botnets to dynamically adjust their attack strategies, undertake stealthy reconnaissance, and coordinate attacks.

Navigating the entanglement

Web3, AI, and DDoS appear to be an unlikely ménage à trois, but in reality, the encounters among them are quite common.

The relatively fledgling Web3 ecosystem is still learning the ropes of proper security and privacy, which makes them a target of threat actors. To boost their security and enhance the efficiency of their operations, many Web3 organizations are turning to AI solutions.

DDoS attacks against Web3 operations are not uncommon. Early this year, a massive DDoS attack peaking at 1.025 Tbps was reported just before the SEC’s scheduled approval of Bitcoin ETF, the first bitcoin exchange-traded funds listed in the US stocks exchange.

The attack involved a large group of botnet network resources but it was successfully quelled with the help of artificial intelligence, which proactively analyzed the attack and allowed the security team to implement the necessary mitigating actions.

This attack on Bitcoin ETF is just one of the many possible entanglements between Web3, AI, and DDoS. It is not the exact scenario described above, but it shows that the perceived unlikely confluence of Web3, AI, and DDoS happens.

The point in mentioning all these is that a rather common cyber attack like DDoS can pose serious threats in the absence of adequate cyber defenses, which tends to happen when organizations are still getting the hang of working with new technologies.

Also, it is important to highlight how AI can be both a friend and a foe. It can be integrated with cybersecurity solutions to bolster cyber defenses, especially against zero-days and attacks that have not been profiled yet.

Conversely, threat actors can leverage artificial intelligence to rapidly seek out vulnerabilities, aid in strategizing attacks, and quickly generate new malware.

In summary, the entanglements between Web3, AI, and DDoS show a glimpse of why it is important to emphasize adequate cybersecurity while adopting and adapting to new technologies. Also, AI is inevitable and should be put to good use instead of letting threat actors monopolize its benefits.

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