Ways AI can Support Cybersecurity Leaders

by Sean Williamson Writer

With the rapid increase in cybercrime in recent years, no business in the world should consider itself safe from an onslaught. As attacks have become sophisticated they have also exponentially increased in volume. Around 80 percent of all cyberattacks are carried out by technically advanced criminal organizations to collect and share data and other information, according to the UN. 

According to estimates, the global economy will be hit by cybercrime to the tune of more than $2 trillion by 2021. Companies should take note and make an unwavering effort to improve cybersecurity in their work environment. If you’re in Omaha and want to enhance your business’s cybersecurity get Cox Omaha for a reliable and secure internet connection with minimum downtime.

Skill Sets, Perception, and Speed

Businesses need technical insights to make smart and quick decisions against a perceived cyber threat. However, as the cybersecurity panorama grows it becomes more uncertain; there isn’t sufficient time to access or process the required data before it adjusts again. The bottom line is there aren’t enough qualified people fully equipped to engage with and manage the tools needed to combat cybercriminals as they have also increased in complexity. What enterprises need is professionals with relevant updated skill sets in keeping with the evolving cybersecurity landscape.

These days, cyberattacks are occurring at a faster rate, so we need to respond just as quickly. There’s a four-hour notification timeframe in some states by law while GDPR requires 72-hour notification with serious consequences for not responding promptly to cyberattacks.

Predictive Analytics

AI-enabled analytics and machine learning are helping businesses to minimize the impact of an attack before it happens.

Analytics gathers intelligence and technical information for enterprises to make correct and timely decisions when a cyber threat occurs. With the induction of the Internet of Things (IoT), AI can be used to process large-scale natural language processing (NLP); this will help collect information so that security analysts can work more efficiently.

Predictive analytics is a tool with which cyber professionals can detect network glitches and malware as well as suspicious human the behavior to find users within an enterprise who can be perceived as a threat or seen to hold potential for fraud. With AI they can pinpoint the user based on keyboard strokes, mouse clicks and their mobile device to improve security.

AI as a Trusted Advisor

AI and analytics can be used to mitigate threats, respond in a timely manner to attacks, and detect low-level alerts. Everyone needs a trusted advisor. AI can offer best practices amidst taking necessary action when a suspicious user is detected by either blocking or suspending the culprit. It can save time by taking action on low-risk alerts allowing the security personnel to focus on high-risk access certifications.

With continuous interaction between cyber professionals along with the hand given by AI and machine learning, it is the combination that businesses need to help with threat detection as well as prioritizing the most important alerts.

Anti-Money Laundering and Fraud Detection Solutions

A company called Feedzai offers customizable data science software, OpenML Engine, for banks, acquirers and merchants to detect money laundering and fraud.

OpenML Engine integrates with the core system and can alert human fraud with risk analysis speeding up the fraud detection process. The software was deployed at the banks’ own data centers for verification of identity and checking fraud assessments in real-time.

Accumulating Security Data

Banks need to detect cybersecurity threats to save on long-term security costs and avoid data leaks. Moreover, banks and financial institutions can benefit from automating their cybersecurity and cyber compliance using DefenseStorm software.

Tools like PatternScout and Threat Match help banks detect cybersecurity threats to save on long-term security costs and avoid data leaks. SaaS solutions allow IT personnel to monitor security-related data on a single dashboard for a rapid response.

Monitoring and Preventing Cyber Attacks

Enterprises need to deploy cybersecurity software to detect threats on a cloud, virtualized networks, IoT and industrial control systems. Darktrace’s Enterprise Immune System software integrates with networks of financial institutions and offers tools like the Darktrace Threat Visualizer, a dashboard that can be used by IT security personnel to monitor cyber threats in real-time.

Enterprise Immune System technology uses machine learning to monitor user data patterns, devices and the network-specific to financial services firm Ipreo’s IT system in order to better monitor vulnerabilities within its network.

PatternEx

By employing AI, PatternEx’s software can identify suspicious user intent allowing businesses to predict and prevent cyberattacks. Using machine learning its Virtual Analyst System analyzes IP addresses, users and sessions to detect suspicious activity.

Information security analysts assess the data pattern to determine which events are real and which ones are false. The response from security analysts is then updated into its models for the next set of data analysis.

The Takeaway

Cyberattacks pose an enormous risk as they have become more refined and grown by leaps and bounds. This makes it crucial for enterprises to make a concerted effort to tighten their cybersecurity. Thus, companies need AI-driven solutions that are diverse and unbiased to deal with developing cybersecurity threats. Cybersecurity leaders should bear in mind that attackers have also become wise to AI solutions and are exploiting it to overcome security systems. As we continue to develop AI cybersecurity platforms we must remain vigilant when it comes to secure and insecure AI. The cybersecurity industry must deploy best practices to protect against malignant applications of AI by cybercriminals. Companies offering fraud detection or anti-money laundering solutions seem the most effective solution for enterprises and cybersecurity leaders to secure themselves in terms of protecting critical organizational data.

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Created on Sep 17th 2019 00:53. Viewed 450 times.

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