Cybersecurity and AI: Secure against Evolving Threats
Introduction to Cybersecurity and AI Integration
Cybersecurity refers to secure digital world through software algorithms. The use of Artificial Intelligence technology in cybersecurity accelerates security defenses. The security teams of today face several challenges from sophisticated cyber-attackers, an explosion of data and growing infrastructure complexity, and an expanding attack surface. These challenges hinder the ability to safeguard data, manage user access, and quickly detect and respond to cybersecurity threats. The AI-powered solutions to these cybersecurity challenges optimize the time of analysts by accelerated threat detection, expediting resources and responses, and protecting datasets.
Integrating AI into cybersecurity systems can protect data across hybrid cloud environments. The Artificial Intelligence Technology solutions identify shadow data while monitoring for abnormalities in data access. The AI alerts cybersecurity professionals about potential threats of anyone accessing the data for sensitive information. The technology saves valuable time in detecting and remediating issues in real-time. A risk analysis done by AI on cybersecurity elements can unearth and produce incident summaries for high-fidelity alerts that automate incident responses. The AI technology integrated into cybersecurity accelerates alert investigations. Artificial Intelligence helps identify vulnerabilities to defend against cybercriminals and cybercrime.
The AI technology balances user needs and cybersecurity measures. AI models help balance cybersecurity with user experience by analyzing the risk of each login attempt while verifying users through behavioral data. It simplifies access for verified users and reduces the cost of fraud by a high margin, up to 88 to 90%. The AI systems prevent phishing, malware, and other malicious activities that ensure and guarantee a high security posture.
Common Cyber Security Threats
In cybersecurity, the threats always keep evolving, which makes professionals look for better ways to tackle the threats and malicious activities. The never-ending cat-and-mouse game with hackers keeps the cybersecurity personnel on their toes as they recruit AI as a threat analyzer.
In early summer 2023, a Russian hacker group used the platform of Microsoft Teams to launch phishing attacks. The cybersecurity officials of Microsoft Threat Intelligence identified the hackers as Midnight Blizzard, who used Microsoft 365 tenants owned by small businesses compromised in previous attacks to host and launch new social engineering attacks. Phishing remains one of the most common cyber threat and cyber attack. The 2023 Comcast Business Cybersecurity Threat Report found that 90% to breach the network of customers starts with a phish attempt. Recently, the volume and velocity of cyberattacks have increased along with the costs incurred by victims. The cost of cyber crimes is projected to touch a whooping 10.5 Trillion AUD by 2025. Emerging cyber threats include data poisoning, SEO poisoning, and AI-enabled threats.
Adversarial AI and Cyber Attacks
Adversaries deliberately confuse and poison AI systems to make them malfunction. Until now, there is no foolproof defense mechanism against such cyber attacks. There are four major types of attacks such as evasion, poisoning, privacy, and abusive attacks. These cyber attacks get classified based on multiple criteria like the nefarious goals and objectives of the attackers.
Evasion attack occurs after the deployment of an AI system. It attempts to alter an input to change how the AI system responds to cyber attacks. Poisoning attacks occur during the training phase of AI by introducing poisonous data. For example, slipping numerous instances of inappropriate language to conversation records makes the chatbot to identify them as common usages in communication. Privacy attacks occur during deployment of AI and these are multiple attempts to learn sensitive information about the AI or data it was trained on. AI misuses the data and becomes a cyber attack. Abuse attacks happen through insertion of incorrect information into a source, which the AI absorbs for its future use. The abuse attacks happen from a legitimate but compromised source and the AI gets fed with incorrect pieces of information.
The AI technology gets hijacked as hackers could use the chatbots of an organization against them. The hackers hack into chatbot systems and compromise them. The compromised chatbots then get used as conduits to spread malware and interact with other systems in nefarious ways. Hackers could use generative AI to spread malicious packages into developer’s environment.
The data and SEO poisoning happens through the attackers tampering or corrupting the data used to train Machine Learning and Deep-Learning Models used to train AI. The attack aims to derail the accuracy of the AI’s decision making and outputs. The algorithms get manipulated through data poisoning. The Search Engine Optimization (SEO) poisoning involves the manipulation of search engine rankings to redirect users to malicious websites, which install malware on the customer devices.
Conclusion
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