Deep Instinct has been recognized by CIOReview Magazine as the recipient of “Top 20 Artificial Intelligence Solution Companies - 2017,” based on our proprietary methodology, reflecting its position in the industry. This profile has been developed by the CIOReview research and editorial team based on insights from an interview with Guy Caspi, CEO.

Deep Instinct
Powering Cybersecurity through Deep Learning

Guy Caspi, CEO

‘Once a brain learns to identify an object, its identification becomes second nature.’ This aptly describes the context of deep learning. Today, deep learning is more commonplace and can be seen in Google’s speech recognition system, Amazon’s text understanding systems, natural language processing, image recognition systems, to name a few. This turnkey technology has transformed every landscape where it has been applied; however the same cannot be said about cybersecurity. Albeit the successful adoption of deep learning in computer vision, speech recognition, and text understanding, its application to cybersecurity is, by orders of magnitude, more challenging. The varying file sizes and formats in the cybersecurity domain pose difficulties in successful deep learning implementation. Deep Instinct, an organization based out of San Francisco, is first ever to implement deep learning in solving cybersecurity challenges.

“We have successfully implemented an end-to-end deep learning system for malware detection, which proves that deep learning can potentially revolutionize any field, even if its application is not straightforward,” remarks Guy Caspi, CEO of Deep Instinct. Since its inception, Deep Instinct has architected solutions that preclude zero-day threats and advanced persistent threat (APT) attacks for endpoint devices and mobile. By leveraging deep learning from the ground up, Deep Instinct has significantly improved the accuracy of threat detection over the past few years. This is the result of continuous training of deep neural networks at the company headquarters. By feeding these networks with huge datasets of malicious and legitimate files, Deep Instincts brings a comprehensive and unique cyber-intelligence solution to the table. Through deep learning, the firm obtains a better and higher detection rate (of malicious files) and a much lower false positive rate (of legitimate files) in its solutions compared to its competitors.

Deep Instinct’s purview of cybersecurity is proactive and the firm’s approach is deeply intertwined with the maxim ‘expecting the next unexpected attack to prevent it.’ Deep Instinct provides real-time protection to endpoint devices using a lightweight agent without impacting the user experience.

The firm secures endpoint devices working on any operating system and ensures continuous monitoring of foreseeable attacks even when the device is disconnected from the company network.

Through deep learning, the firm obtains a better and higher detection rate and a much lower false positive rate

Essentially, three components comprise Deep Instinct’s solution portfolio. D-Brain is the core component of the deep learning cybersecurity solution. This is hosted in the Deep Instinct headquarters and is a deep neural network that is constantly fed with malware datasets to develop real-time cyber-threat intelligence capabilities. Utilizing all the updates from D-Brain, D-Appliance provides an intuitive, powerful, visualization, and management tool that configures organization’s security policy and enables thorough threat monitoring. D-Client combines the work done by aforementioned components and that transcends into a lightweight, connectionless, real-time cyber-threat prevention solution. D-client proactively scans devices as per the policies outlined by D-Appliance and ensures the safe upkeep of all endpoints across the organization. It is because of such defined segmentation that Deep Instinct’s solutions were able to heighten its accuracy and bolster system performance.

Being the flag bearer of deep learning based cybersecurity solutions, Deep Instinct’s innovative approach towards cybersecurity has attracted a wide and variegated clientele. As per Caspi, the firm’s solutions, had typically monitored and averted umpteen threats that evaded detection by other cybersecurity solutions. This has strengthened the firm’s stance in the landscape and resulted in a higher customer satisfaction rate.

Caspi affirms that deep learning certainly is going to re-model the cybersecurity landscape in the impending years and that would attribute to its widespread use. “Our company’s vision is to accord due thrust on developing additional deep learning based solutions within cybersecurity,” Caspi concludes.

Deep Instinct

Deep Instinct Appoints Ed Carter as Chief Revenue Officer to Scale Growth of Prevention-first Cybersecurity

Friday, April 14, 2023

NEW YORK: Deep Instinct, the prevention-first cybersecurity company that stops unknown malware pre-execution with a purpose-built, AI-based deep learning (DL) framework, announced that Ed Carter has joined the company as Chief Revenue Officer. In this role, Carter will drive Deep Instinct's growth and expansion with enterprise customers, technology and channel partners, and MSSPs, by delivering on the prevention-first mission.

"As we accelerate our growth, Ed Carter brings the level of leadership experience to build a scalable and repeatable go-to-market team. His success as a sales leader and champion of channel partnerships matches the proven model that will lead Deep Instinct to the public markets,” said Lane Bess, chief executive officer of Deep Instinct.

"I am extremely excited about Deep Instinct's strong value proposition. The deep learning framework is foundational for the next generation of AI-based cybersecurity solutions,” Carter said. “I believe that the ‘prevention-first’ approach will be disruptive and is a quantum leap forward to address the continued board-level concerns about ransomware and other debilitating attacks."

Carter is no stranger to bringing disruptive technologies to market at scale, highlighted by his impact on bringing converged infrastructure to market while at VCE (now Dell EMC) and Zerto (HPE). Most recently, as the CRO at Zimperium, Carter architected and executed a global enterprise growth strategy.

Deep Instinct Introduces DIANNA, the First Generative AI-Powered Cybersecurity Assistant to Provide Expert-Level Malware Analysis for Unknown Threats

Thursday, June 13, 2024

Cyber companion, DIANNA, builds upon Deep Instinct’s prevention-first capabilities, redefining the boundaries of AI and cybersecurity

NEW YORK --Deep Instinct, the prevention-first cybersecurity company that stops unknown malware pre-execution with a purpose-built, AI-based deep learning (DL) framework, today announced the launch of Deep Instinct’s Artificial Neural Network Assistant (DIANNA), the industry’s first AI-based cybersecurity companion that provides explainability into unknown threats. DIANNA enhances Deep Instinct's prevention-first approach to cybersecurity through its expert-grade static malware analysis, something no other solution on the market can replicate.

Powered by a large language model (LLM), DIANNA serves as a virtual AI team of malware analysts and incident response specialists. It provides deep analysis into all attacks, including never-before-seen threats, revealing the techniques employed and behaviors of files to provide a comprehensive narrative that facilitates understanding and mitigation of threats before breach.

While traditional AI tools leverage LLMs to provide human-like summarization data from existing sources like logs and reputation engines, none provide insights into how unknown attacks are malicious in nature. While valuable, their approach only offers retrospective analysis with limited context. Deep Instinct harnesses generative AI to equip DIANNA with the collective knowledge of countless cybersecurity experts, effectively embedded within the LLM, to provide in-depth malware analysis of unknown files and identify malicious intent with unparalleled accuracy.

“With the rise in AI-generated attacks, organizations can no longer be complacent or reactive in how they approach cybersecurity. It’s time to fight AI with better AI, and raise greater awareness about the unknown threats impacting businesses,” said Lane Bess, CEO of Deep Instinct. “DIANNA provides vital threat explainability, enhances our prevention-first approach, and marks a strategic shift towards a more informed, efficient, and effective cybersecurity environment.”

DIANNA seamlessly integrates with Deep Instinct's DL-powered prevention-first capabilities to provide in-depth insights into both known and unknown attack behavior through static analysis. Unlike traditional machine learning-based tools, DIANNA doesn't just provide the classification results; it provides in-depth analysis and reporting in a clear, digestible way. This transparency enables security teams to make informed decisions and prioritize threats effectively, optimizing security operation center (SOC) performance. It also reduces mean-time-to-repair (MTTR) while significantly improving job satisfaction by reducing the amount of time spent chasing false positives.

By harnessing the power of generative AI, DIANNA empowers security teams with the following capabilities:

• Unparalleled Expertise for Unknown Threats: DIANNA’s static analysis goes beyond traditional methods, offering an unprecedented level of insight into unknown scripts, documents, and raw binaries, providing valuable insights for organizations facing zero-day attacks.

• Translating Code Intent and Activity to Natural Language: DIANNA translates binary code and scripts from various languages into a natural language report. DIANNA doesn't just analyze the code; it understands the intent and the potential actions and explains what the code is designed to do, what makes it malicious, and how it might impact systems.

• Enhanced Visibility: DIANNA offers insights into the decision-making process of Deep Instinct's prevention models, allowing organizations to fine-tune their security posture for maximum effectiveness.

• Expert-Level Analysis of Threat Delivery File Types: DIANNA analyzes various file formats including binaries, scripts, documents, shortcut files, and other threat delivery file types.

• Streamlined Workflows: DIANNA automates some of the most tedious tasks of SOC analysis, freeing up security teams to focus on more strategic initiatives.

“DIANNA is the ultimate cyber companion for security teams,” said Yariv Fishman, Chief Product Officer of Deep Instinct. “There are two factors that set DIANNA apart from other AI-powered chatbots. First, its unprecedented malware analysis compresses hours of work, requiring deep cyber threat expertise, into seconds. Second, DIANNA’s ability to analyze unknown threats, including scripts, documents, and raw binary files, is unmatched. Both of these capabilities build upon our prevention-first approach and allow security teams to focus on what truly matters.”

Top 20 Artificial Intelligence Solution Companies - 2017

Company
Deep Instinct

Management
Guy Caspi, CEO

Description
The first company to incorporate deep learning in cybersecurity solutions

Deep Instinct Powering Cybersecurity through Deep Learning