AI poses a major threat to cybersecurity
The human vulnerability and social engineering are the biggest target in the majority of cybercrimes and AI can assist cyber criminals by hitting the key weakness, human vulnerabilities with an AI styled attack, both the human and cybersecurity products would fail to detect it. AI technology can both enhance cybersecurity measures and pose a threat to them. On the one hand, AI can be used to detect and prevent cyber attacks, as well as analyze vast amounts of data to identify potential threats. However, on the other hand, AI can also be used by cybercriminals to carry out attacks that are more sophisticated and harder to detect. One way that scammers can leverage AI is through the use of "deepfake" technology. Deepfakes are videos or audio recordings that have been manipulated using AI to make them appear authentic, even though they are not. Scammers can use deepfakes to create fake videos or audio recordings of individuals, such as CEOs or government officials, and then use those recordings to trick people into giving them sensitive information or money.
Another way that scammers can use AI is through the use of "chatbots." Chatbots are computer programs that are designed to mimic human conversation. Scammers can use chatbots to engage with people online, pretending to be a legitimate company or organization, and then use the conversation to extract sensitive information from their targets.
The more serious threat is AI can also be used to automate and scale phishing attacks. By using AI algorithms to craft convincing phishing emails and messages, cyber criminals and scammers can send out a large volume of messages with a high degree of personalization, making it more likely that their targets will fall for the scam. AI can be used to carry out "credential stuffing" attacks. In a credential stuffing attack, scammers use automated bots to try out lists of usernames and passwords on different websites until they find a match. By using AI to generate these lists and automate the attack, scammers can carry out attacks on a much larger scale than would be possible manually.
Overall, AI technology can be both a powerful tool for enhancing cybersecurity measures and a potent weapon in the hands of cybercriminals. As the technology continues to advance, it is likely that both the benefits and the risks will continue to grow. DIGITPOL believes that governments should take action now (March 2023) to rapidly regulate the use of AI as the threats are enormous to security if not handled.
The key points to focus on:
- AI can also be used to carry out Distributed Denial of Service (DDoS) attacks. By using AI to direct an army of bots to attack a specific target, scammers can overwhelm the target's servers and effectively take them offline.
- AI can be used to bypass security measures such as firewalls, intrusion detection systems, and antivirus software. By training AI algorithms to identify and exploit vulnerabilities in these systems, attackers can gain unauthorized access to sensitive information.
- AI can be used to automate the process of discovering and exploiting new vulnerabilities. By analyzing vast amounts of data and identifying patterns, AI can quickly discover new vulnerabilities and exploit them before they can be patched.
- AI can be used to carry out advanced persistent threats (APTs), which are long-term, targeted attacks designed to gain access to sensitive information. By using AI to automate the process of reconnaissance, scammers can gather information on their targets and then use that information to launch targeted attacks.
- AI can be used to create "zero-day" exploits, which are attacks that take advantage of previously unknown vulnerabilities in software or hardware. By using AI to analyze and reverse engineer software, scammers can discover these vulnerabilities and create exploits before they are discovered by the software's creators.
- AI can be used to create more convincing fake websites and social media profiles, making it easier to carry out phishing attacks and other types of social engineering scams.
- AI can be used to carry out "fuzzing" attacks, which involve inputting large amounts of random or invalid data into an application or system in order to trigger errors or crashes. By using AI to generate and input this data, scammers can quickly identify vulnerabilities that may be missed by traditional testing methods.
- AI can be used to generate and distribute malware, including ransomware and trojans. By using AI to analyze and identify vulnerabilities in target systems, scammers can create malware that is more effective at bypassing security measures and spreading undetected.
- AI can be used to carry out "living off the land" attacks, which involve using legitimate tools and software already installed on a system to carry out malicious activities. By using AI to automate these attacks, scammers can make them more efficient and difficult to detect.
- AI can be used to carry out "adversarial attacks" on machine learning models used in cybersecurity. By using AI to generate malicious input data, scammers can cause these models to produce incorrect results, leading to false positives or false negatives and potentially allowing attackers to bypass security measures.
- AI can be used to carry out "cyber-physical attacks," which involve manipulating physical systems such as industrial control systems or critical infrastructure. By using AI to identify vulnerabilities in these systems and create targeted attacks, scammers can cause significant damage or disruption.
DIGITPOL states the number one crime that will increase with AI technology is email scams and phishing attacks will rise to a new level with AI automating a high degree of personalisation meaning victims will fall easier to such fraudulent mails, AI’s offensive capabilities are built from experience-based learning and self-learning therefore, AI can increase cybercrimes if cyber criminals can leverage the technology, we can be certain of it. Social engineering is an easy target for AI related attacks.
As AI continues to advance, it is likely that we will see new and more sophisticated ways in which it can be used to pose threats to cybersecurity. It is important for cybersecurity professionals to stay up-to-date on these developments and to develop new tools and strategies to detect and prevent AI-enabled attacks. DIGITPOL states that it is vital cyber security vendors advance their detection signatures to identify AI styled attacks.
Since December 2022, Digitpol is developing a machine learning AI plugin to learn and identify specific patterns and signatures associated with criminal use of code, such as malware or botnets, and flag them for investigation. Digitpol states that machine learning algorithms can be trained to recognise patterns and behaviours associated with malicious code, and this can help detect and prevent cyber attacks by using AI to flag suspicious code, human analysts can then investigate and take appropriate actions to mitigate the threat.
The AI market is a rapidly growing industry, with an estimated value of $62.35 billion in 2021 and projected to reach $733.7 billion by 2027, according to a report by MarketsandMarkets. This growth is driven by increasing demand for AI technologies in various industries such as healthcare, finance, and retail, as well as the development of new AI applications and the integration of AI into existing systems.
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