Artificial Intelligence in Data Security:
Nowadays, the role of artificial intelligence in the industry is crucial as the world is smarter and more connected than ever before. Many reports estimate that cyberattacks will become more tenacious as time goes by and security teams will have to rely on AI solutions to keep systems and data in check.
Threats
The first step to understanding the role of AI in data security is to learn about the various types of threats to data security:
- Social Engineering—a technique bad actors use to manipulate users into granting them access or valuable information. This technique can be combined with other types of cyberattacks. For example, attackers can disguise as legitimate sources and convince users to download and activate malware or enter malicious sites.
- Phishing—a type of social engineering, phishing is the most common threat, and it is typically performed by sending messages and emails cloaked as legitimate to trick victims into giving valuable data or downloading malware that can steal the data itself, such as trojan horses.
- Malware (malicious software)—a general term that describes any type of software designed mainly to damage networks and devices such as computers and smartphones.
- Ransomware—a form of malware designed to extort victims for money by blocking access to settings and files until a ransom is paid. To regain access and control of their system, users must pay the ransom (typically within a timeframe) and activate a decryption key they are typically (not always!) given by the bad actor after payment is due. It is important to remember that even if access is restored, the attacker still had free access for all the data in the system and could still have a copy stored in their system so valuable information is still at risk.
- Advanced Persistent Threats (APTs)—a type of attack used by actors to infiltrate the network undetected and maintain their position for long periods. This technique is efficient because it can be harder to detect since the attacker can steal valuable data without raising alerts.
- Zero-day exploit—time-sensitive attacks that leverage vulnerabilities soon after they are discovered before a patch and fix were created. These attacks are hard for security teams to mitigate and could lead to serious damage to valuable data.
- SQL injection—attackers use SQL Injection to access an SQL server and run malicious code. The idea behind this attack is to leverage a vulnerability within SQL servers and force them to reveal information hidden information.
- Denial-of-Service (DOS) attack—bad actors use this technique to overflow networks and servers with traffic so they will run out of resources and become unavailable to users.
- Insider threat—a type of attack in which organizations are targeted by people they employ directly or indirectly. There are various types of insider attacks, and they typically target valuable and sensitive data to the organization
- Data breach—a vulnerability that allows unauthorized parties to access valuable and sensitive data such as user information, passwords, credit card or any sensitive and private information.
AI-Powered Data Security Solutions
AI-driven security tools are capable of reducing the risks and even manage many of the threats to data security. They can do this either by themselves through automation and detection or by providing security teams and Security Operation Centers (SOCs) with enhanced capabilities.
- Security Information and Event Management (SIEM)—a security tool that uses rules and statistical correlations to actionable information on security events and helps security teams deal with events across the entire organizational environment. With the information provided by SIEM, SOC staff are more equipped to deal with data security threats in real-time.
- User and Entity Behavior Analytics (UEBA)—a tool that uses AI to collect, track and analyze data from computer activities to indicate suspicious behaviors. UEBA learns patterns of legitimate access usage and uses these patterns to detect complex attacks like insider threats by recognizing behaviors that indicate malicious intent and jeopardize valuable data.
- Security, Orchestration, Automation, and Response (SOAR)—a cybersecurity solution used by organizations for data collection and alerts on threats. SOAR can detect threats and automatically deal with low-level threats quickly and efficiently.
