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Fabric Management Center - SOC

Speed security operations with artificial intelligence

To keep up with the volume, sophistication, and speed of today’s cyber threats, organizations need security operations that can function at machine speed. By applying artificial intelligence as well as integration and automation, organizations can reduce risk and improve efficiency. Advanced threat detection and response capabilities along with centralized security monitoring and optimization can easily be added across the entire Fortinet Security Fabric.

Endpoint Security

Combining behavior-based endpoint protection, detection, and response offers a modern approach to endpoint security. Fortinet uses multiple machine learning and deep learning technologies to power all three functions at each endpoint.

Breach Protection

Fortinet provides a range of behavior-based detection and response capabilities that include and go beyond the endpoint. Sandbox, deception, user and entity behavior analytics work as integrated extensions of inline security controls to thwart cyberattacks.

SOC Platform

Designed to meet the needs of organizations of varying size and security maturity, a range of security options provide centralized visibility, analytics, and control across the security infrastructure.

SOC Platform

SIEM
As digital transformation sweeps through every industry, the attack surface grows dramatically (and constantly), making security management increasingly difficult. Security teams struggle to keep up with the deluge of alerts and other information generated by their multitude of security devices. And the cybersecurity skills gap only makes this more difficult.

Infrastructure, applications, and endpoints (including IoT devices) must all be secured. This requires visibility of all devices and all the infrastructure—in real time. Organizations also need to know what devices represent a threat and where.
Analytics, Reporting & Response
The digital attack surface is expanding at a rapid rate, making it increasingly difficult to protect against advanced threats. According to a recent Ponemon study, nearly 80% of organizations are introducing digital innovation faster than their ability to secure it against cyberattacks. In addition, the challenges of complex and fragmented infrastructures continue to enable a rise in cyber events and data breaches. Assorted point security products in use at some enterprises typically operate in silos, obscuring network and security operations teams from having clear and consistent insight into what is happening across the organization.

An integrated security architecture with analytics and automation capabilities can address and dramatically improve visibility and automation. As part of the Fortinet Security Fabric, FortiAnalyzer provides security fabric analytics and automation to provide better detection and response against cyber risks.
SOAR
As the digital attack surface expands, security teams must also expand their defense capabilities. Yet, adding more security monitoring tools is not always the answer. Additional monitoring tools mean more alerts for security teams to investigate and more context switching in the investigation process, among other issues. This creates a number of challenges for security teams, including alert fatigue, a lack of qualified security personnel to manage new tools, and slower response times.

Integrated into the Fortinet Security Fabric, FortiSOAR security orchestration, automation and response (SOAR) remedies some of the biggest challenges facing cybersecurity teams today. Allowing security operation center (SOC) teams to create a custom automated framework that pulls together all of their organization's tools unifies operations, eliminating alert fatigue and reducing context switching. This allows enterprises to not only adapt, but also optimize their security process.
XDR

Extended detection and response (XDR) is a natural extension of the endpoint detection and response (EDR) concept, in which behaviors that occur after threat prevention controls act are further inspected for potentially malicious, suspicious, or risky activity that warrant mitigation. The difference is simply the location (endpoint or beyond) where the behaviors occur.

XDR solutions are increasingly popular as organizations recognize the inefficiencies, and in many cases ineffectiveness, of security infrastructures comprised of many individual “best-of-breed” security products deployed from different vendors over time. Common challenges arising from this point-product approach include:

  • Gaps in security: with each product operating in its own silo, opportunities often arise for cyberattacks to enter in between
  • Too much security information: with each product generating individual alerts and other information, security teams can easily miss indicators of cyberattacks
  • Uncoordinated response: with each product operating independently, it falls on the human operator to share information and coordinate response actions 

Based on these experiences, many organizations are looking to consolidate security vendors and products in favor of integrated solution sets.

Advanced Threat Protection

Deception

According to Verizon’s 2020 Data Breach Investigation Report Verizon’s 2020 Data Breach Investigation Report, two-thirds of breaches found were from external actors while the remaining one-third involved internal actors.

FortiDeceptor is based on deception technology that complements an organization’s existing breach protection strategy, designed to deceive, expose and eliminate attacks originating from either external or internal sources before any real damage occurs.

Sandboxing

Unlike previous generation of viruses that were non-sophisticated and low in volume, antivirus tools were sufficient to provide reasonable protection with their database of signatures.

However, today’s modern malware entails new techniques such as use of exploits. Exploiting a vulnerability in a legitimate application can cause anomalous behavior and it’s this behavior that attackers take advantage of to compromise computer systems. The process of an attack by exploiting an unknown software vulnerability is what is known as a zero-day attack aka 0-day attack, and before sandboxing there was no effective means to stop it.

A malware sandbox, within the computer security context, is a system that confines the actions of an application, such as opening a Word document, to an isolated environment. Within this safe environment the sandbox analyzes the dynamic behavior of an object and its various application interactions in a pseudo-user environment and uncovers any malicious intent. So if something unexpected or wanton happens, it affects only the sandbox and not the other computers and devices on the network. In parallel, any malicious intent is captured, leading to an alert and relevant threat intelligence generated to stop this zero-day attack.

Typical characteristics found in a malware sandbox:

  1. Detection engine consisting of static and dynamic analysis to capture both malware attributes and techniques
  2. Emulation of various device OS including Windows, macOS, Linux, and SCADA/ICS, and associated applications and protocols
  3. Accepts a multitude of sources including network packets, file shares, on-demand submission and automated submissions by NGFW, SEG, EPP/EDR, and WAF, other integrated security controls
  4. Reporting and automated sharing of threat intelligence
  5. Flexible deployment modes such as appliance, VM, SaaS and Public Cloud to fit various on-prem and cloud environments
Isolation

FortiIsolator, Fortinet’s browser isolation platform, adds an additional advanced threat protection capability to the Fortinet Security Fabric and protects critical business data from sophisticated threats out on the web. Content and files from the web are accessed in a remote container and then risk-free content is rendered to users. 

Sophisticated threats on the web multiply by the day. It’s nearly impossible to stay current about what threats reside on which pages, and what objects are good or malicious. It can be intimidating to keep up with the proliferation of advanced attacks.

FortiIsolator allows organizations to keep their most critical, high-value targets secure from the onslaught of threats. It allows users to browse the web in an isolated environment, which renders safe content in a remote container. FortiIsolator is a completely remote environment that does not require an install on a user’s computer or device. 

Virtual Security Analyst ™

Among its many benefits to cybersecurity, Artificial Intelligence (AI) can identify patterns in massive amounts of data, enabling it to detect trends in malware features and make threat classifications much more rapidly than humans can. An AI-based virtual security operations (SecOps) analyst can rapidly detect and respond to security incidents, assisting human analysts and enabling them to operate at a higher level. AI-powered cybersecurity technologies such as this can be a boon to short-staffed security teams affected by the global cybersecurity skills gap.

While Machine Learning (ML) is the most common type of AI used in cybersecurity designed to solve linear problems e.g. perform a task more efficiently and effectively for a specific situation, Deep Learning (DL) is designed to solve larger complex, non-linear problems by modelling the operation of neurons in the human brain.

AI-based learning algorithms fall into three categories: supervised, reinforced and unsupervised. A supervised ML algorithm must be trained on a large dataset of samples labeled as either benign or malicious. In contrast, Deep Neural Networks (DNN), a Deep Learning model uses reinforced learning i.e. an award-based system of learning, during its pre-training and later transitions to unsupervised learning i.e. self-learning, that does not require a labeled dataset for training and maturity. More importantly, lies in its ability to correlate various category of datasets to make decisions.

UEBA

30 percent of data breaches involve organization insiders acting negligently or maliciously. Insiders pose a unique threat to organizations because they have access to proprietary systems and often are able to bypass security measures, creating a security blind spot to the risk and security teams.

Fortinet’s User and Entity Behavior Analytics (UEBA) technology protects organizations from insider threats by continuously monitoring users and endpoints with automated detection and response capabilities. Leveraging machine learning and advanced analytics, FortiInsight automatically identifies non-compliant, suspicious, or anomalous behavior and rapidly alerts any compromised user accounts. This proactive approach to threat detection delivers an additional layer of protection and visibility, whether users are on or off the corporate network.

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Get in Touch

Stefan van de Giessen
Business Unit Manager
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