Navigating AI in Cybersecurity: Balancing Innovation and Risk – Security Boulevard

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Global organizations are rapidly adopting artificial intelligence (AI) and machine learning (ML) to help enhance their business and operations. Research by IBM shows that over 35% have already adopted AI into their existing processes, and over 60%, on average, globally, have some capacity for AI or plan to add it. 

With as many organizations embracing AI, there are still many more holding back due to concerns about creating exposure for their organization. With existing shortages in cybersecurity skills, it’s sensible to be cautious about new sources of risk; however, avoiding the power of AI to entirely avoid this risk is not practical. 

In this article, we explore some legitimate challenges that organizations face from AI and provide solutions to help prepare.

AI Threats Haunt Businesses

It’s not that organizations are scared of AI as a whole, but rather the potential it poses when misused. With AI’s rapid evolution and adoption, news headlines showing its benefits and risks have become commonplace, but the abusive use of AI is the most striking. Looming threats of automated attack platforms, AI-enhanced malware, and the rapid discovery of vulnerabilities has created tangible fears that the cyber-threat landscape will only worsen with time. With AI’s ability to function at a large scale and high velocity, cyber attacks may become more extensive and inflict more damage in a much shorter time frame, making AI threats particularly daunting.

Automated Attacks

One of the primary fears is that AI will automate sophisticated cyber attacks. AI’s capability to execute large-scale operations like phishing campaigns or network intrusions autonomously adds complexity. These AI-powered attacks can employ diverse tactics simultaneously, making it harder for traditional defenses to keep up. This problem worsens with AI’s ability to learn and adapt based on the defensive measures they encounter, constantly evolving their strategies to bypass security protocols.

This adaptability is compounded by the unsupervised nature of AI operations. Once deployed, these AI-driven attacks can function independently, requiring minimal oversight from attackers. This autonomy increases the efficiency of cyber attacks, allowing cybercriminals to disassociate themselves from the direct execution of them, making it more challenging to trace and counteract them. 

AI-Enhanced Malware Permutations

Some AI platforms help enhance coding and streamline processes for developers. Organizations fear that these tools can be subverted, allowing AI to enhance malware or speed up the development of novel strains. Rather than spending costly developer time to create malware permutations, AI can rapidly change code and behavior to evade traditional signature-based detection methods. Such adaptability renders many conventional antivirus solutions less effective and is leading organizations to seek more proactive solutions.

In addition to its adaptive nature, AI-enhanced malware can exhibit self-repair and resilience features. If such malware is partially disabled or damaged by security measures, it has the potential to self-repair, restoring its functionality and prolonging its presence in infected systems. This resilience makes it more challenging to eradicate the malware, allowing it to persist over extended periods, causing more significant damage and posing a more persistent threat to cybersecurity infrastructures.

Targeted Attacks

AI in targeted cyber attacks also poses a significant threat as it allows for analyzing vast amounts of data to pinpoint vulnerabilities in specific systems or networks. This leads to more precise and effective malware attacks. AI enhances the personalization of phishing attacks, tailoring them to individual targets and significantly increasing their likelihood of success. 

Moreover, by analyzing user behavior, AI can determine the most opportune moments and attack methods. Perhaps most insidiously, AI can enable malicious activities to mimic normal network behavior, bypassing anomaly-based detection systems. This capability makes AI-driven attacks particularly hard to detect and counteract, further complicating the landscape.

Developing Solutions

While the threats from AI make cybersecurity harder, there is no reason to assume that it is impossible to prevent threats. They are not fundamentally different from existing threats like Advanced Persistent Threats (APTs) and organized cybercrime. The innovation and creativity of seasoned cybercriminals have long been a concern, and while AI brings derivative capabilities, it still falls short of human ingenuity. The focus should remain on building robust and effective security systems and embracing the power of AI to improve operations.

Adhere to Best Practices

Adhering to best practices in cybersecurity is a critical first step in mitigating AI-related threats. AI threats take advantage of existing vulnerabilities, so taking the following steps will help form the foundation to make AI attacks less likely to succeed: 

  • Implement Regular Security Audits – Conduct frequent assessments to identify vulnerabilities and enhance security measures.
  • Continual Staff Training – Educate staff about the latest cybersecurity trends and threats, especially phishing, to make them harder targets.
  • Backup and Recovery Procedures – Establish robust data backup and recovery protocols to minimize breach damage.
  • Use of Multi-Factor Authentication (MFA) – Enhance security by requiring additional forms of verification before access is allowed.
  • Stay Updated with Threat Intelligence – Keep abreast of the latest threat intelligence to anticipate and prepare for emerging threats.
  • Network Segmentation – Divide networks into segments to contain and limit the impact of any breach.
  • Incident Response Planning – Develop and regularly update a comprehensive incident response plan.

Prepare for All Malware

Addressing AI-driven malware threats is no different than combatting other malware. It necessitates a multi-layered approach. Traditional antivirus (AV) solutions are critical for eliminating known threats that might be part of AI-driven attack campaigns. They are fast, efficient, and can address conventional and AI-enhanced threats, creating a solid first line of defense.

However, AV solutions may not initially detect unique and new malware variants as it takes time for signature files to update.

Content Disarm and Reconstruction (CDR) technology addresses this gap. CDR steps in where antivirus solutions might fall short by using a sanitization process that rebuilds files from known-safe components. This method effectively eliminates unique malware variants that might slip through AV defenses. Hence, even if a phishing attempt bypasses initial security layers, the malware embedded within can still be neutralized, ensuring a more comprehensive defense.

Manage Attack Surfaces

Effectively managing attack surfaces is another critical strategy in combating AI-powered cyber threats. Attack surface management takes a deep dive into reviewing your organization to discover and prioritize all assets, their organizational value, and potential exposures they have. This process involves thoroughly assessing the IT infrastructure to identify and mitigate vulnerabilities. Organizations can effectively prioritize their security efforts by understanding the value and risks associated with each asset. This proactive approach minimizes potential attack vectors, reducing the opportunity for AI-powered cyber threats to exploit these vulnerabilities. 

Votiro Helps Defend Against Advanced AI Threats

Not only does Votiro provide proactive file-borne threat detection, mitigation, and (sanitized) file reconstruction, Votiro is revolutionizing cybersecurity with its advanced threat analytics dashboard, enabling organizations to tackle advanced AI-driven cyber threats more efficiently. 

This tool streamlines the investigation process by focusing on true positives, minimizing false positives, and thereby reducing alert fatigue.

The in-depth threat analytics dashboard also enhances cybersecurity by providing teams with actionable insights into suspicious file content, including true-typing, macro analysis, and external actions. Combined with its CDR capabilities and antivirus protection, Votiro is able to provide multiple advantages: safeguarding against known threats while equipping organizations with tools to effectively understand and manage potential vulnerabilities.

Contact us today to learn more about how Votiro provides the visibility your organization needs to efficiently stop hidden threats in files, including those designed by AI.

*** This is a Security Bloggers Network syndicated blog from Votiro authored by Votiro Team. Read the original post at: https://votiro.com/blog/navigating-ai-in-cybersecurity/

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