The rise of AI: A Boon and a Bane for Cybersecurity

The advent of Artificial Intelligence (AI) has given rise to enormous possibilities, as well as challenges, in the domain of cybersecurity. On one hand, AI-enabled tools are helping in the early detection and prevention of security breaches. While, on the other, AI is enabling malicious actors to devise sophisticated techniques for launching attacks on IT infrastructure and applications. In this article, we will explore both these facets and discuss how organizations can leverage the power of AI to remain cybersafe.

Use of AI in Cyber-Attacks

AI is being increasingly used to automate, enhance and personalize cyber-attacks, making them more sophisticated and difficult to prevent. Such attacks leverage AI or machine learning (ML) algorithms to automate, accelerate or enhance various phases of a cyberattack. These algorithms have the ability to learn and evolve over time; hence, AI-enabled cyberattacks can adapt to avoid detection or create a pattern of attack that a security system cannot detect easily. Some of the ways in which AI is being used by cyber attackers are as follows:

• Vulnerability Identification: AI can be used to analyse networks and systems for identifying vulnerabilities and weaknesses that can be exploited by attackers.

• Social Engineering Attacks: Social engineering attacks aim to manipulate human behaviour to share sensitive data, transfer money or ownership of high-value items, or grant access to a system or application. In an AI-driven social engineering attack, an algorithm can be used to: identify a soft target who can serve as a gateway to the IT environment; develop an online presence to communicate with the attack target; and write personalized messages or create audio / video recordings to engage the target.

• Phishing Attacks: Generative AI can be used to create highly personalized and realistic emails, SMS messages, phone communication etc. to access sensitive information, gain access to a system, receive funds, or prompt a user to install a malicious file on her device. For example, in 2017, a phishing campaign was detected that utilized AI to deceive Google Docs users. Cybercriminals created a malicious application closely resembling a legitimate Google Docs tool; however, it actually collected user information and sent it to a server controlled by the cybercriminals.

• Botnets: AI-driven botnets can be used to launch large-scale Distributed Denial-of-Service (DDoS) attacks or other sophisticated cyberattacks. For example, in April 2018, over 3.75 million records of TaskRabbit were breached, and personal information and financial details of users were stolen. This was caused by a DDoS attack that used an AI-enabled botnet.

• Ransomware: AI-powered ransomware can be continuously updated and modified, making it more difficult to detect. For example, in May 2021, the United States insurance company Colonial Pipeline was attacked by the DarkSide ransomware group. They used a combination of traditional hacking tools with AI techniques to infiltrate the company’s computer system and encrypt its data. In exchange for the decryption key, the cybercriminals demanded a sum of money in Bitcoin. The attack resulted in the disruption of fuel supply across much of the East Coast of the United States.

• Adversarial Attacks: AI can be used to create attacks that specifically target and bypass security systems like voice recognition software. Besides, attackers may use adversarial AI/ML techniques (like poisoning attacks, evasion attacks, model tampering etc.) that target different areas of AI model development and operation.

• Improved Attack Vectors: AI can be used to develop new and more sophisticated attack vectors, such as deepfake impersonations. A deepfake is an AI-generated video, image or audio file that is meant to deceive people. For example, an attacker may use existing footage of a corporate leader to create a doctored voice recording or video footage. This can mimic the person’s voice and instruct an employee to take a specific action, such as transferring funds, changing a password or granting system access.

• Malware Development: AI can be used to develop advanced malware that is more difficult to detect and can evade security measures. This capability has been demonstrated in proof-of-concept malware like BlackMamba, which uses generative AI to create polymorphic code designed to bypass endpoint detection and response (EDR) systems.

  
  

Use of AI in Cybersecurity

AI technologies can be leveraged to enhance security measures by automating threat detection, analysing data and responding to incidents in real-time. This approach enables systems to learn from experience, adapt to evolving threats and proactively defend against attacks, including phishing and other cyber threats. Some of the ways in which AI can be used for cybersecurity are as follows:

• Vulnerability Management: AI can be used to scan networks for weaknesses and proactively address them, preventing security attacks.

• Threat Detection: AI algorithms can analyse large volumes of data to identify patterns indicative of cyber threats, enabling real-time detection. They can detect and prevent malware attacks by identifying and isolating malicious software.

• Behavioural Analytics: AI can analyse user behaviour patterns to identify anomalies that might indicate unauthorized access.

• Phishing Detection: AI can identify and flag suspicious emails, preventing users from falling victim to phishing and social engineering attacks.

• Automated Response: AI can automate security tasks, like incident response, patch management etc. AI-powered systems can quickly identify, analyse and respond to threats, reducing the window of opportunity for attackers.

• Secure Software Development: AI can assist in generating secure code by suggesting best practices and identifying potential vulnerabilities. AI-enabled tools can analyse code for vulnerabilities, ensuring that the developed software is secure.

  
  

How Sujosu Technology Can Help

Sujosu Technology helps organizations design and implement AI systems that prioritize data security and compliance. Our services include:

• Risk Assessments: Identifying security requirements and vulnerabilities in AI systems.

• Countermeasures and Solutions: Providing tailored strategies to prevent, detect, and recover from potential attacks.

• Training and Awareness: Equipping your team with the knowledge to address cybersecurity challenges effectively.

  
  

With Sujosu Technology’s expertise, your organization can build AI systems that are secure, compliant, and resilient against breaches. Besides, we use several AI-powered tools like Snyk Code, SonarQube and ZAP for secure software development. You can engage Sujosu’s services for the development and deployment of secure applications.

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