Top Ten Cybersecurity Companies - Deep Instinct
Deep Instinct is a cybersecurity company that applies deep learning to cybersecurity. The company implements advanced Artificial Intelligence to the task of preventing and detecting malware. Deep Instinct was founded in 2014 by Guy Caspi, Dr. Eli David, and Nadav Maman. The headquarters of the company is located in New York City.
Using deep learning, Deep Instinct offers a predictive threat prevention platform. The multi-layer protection is provisioned across pre, on, and post-execution stages. It is based on a prevention first approach, followed by detection & response, automatic analysis and remediation.
Unlike detection and response based cybersecurity solutions, which wait for the execution of the attack to react, our advanced preventative approach proactively keeps our customers protected by preventing the attack from entering and causing any damage.
By using deep learning, the company is able to predict and prevent any kind of threat – known and unknown – anywhere in zero-time. Every endpoint, server, mobile device, network and operating system is protected against any type of attack, be it fileless or file-based. This advanced approach to threat prevention ensures that attacks are identified and blocked before any damage can be caused.
What is deep learning?
Deep learning is the most advanced subset of artificial intelligence. Also known as “deep neural networks,” it takes inspiration from how the human brain works.
Namely, the more data that is fed into the machine the better it is at intuitively understanding the meaning of new data. It, therefore, does not require a (human) expert to help it understand the significance of new features.
Deep Instinct is changing the way we look at cybersecurity by harnessing the power of Deep Learning Neural Networks to prevent threats in zero time. The platform’s unique deep learning multi-layer security architecture is designed for any security need, against any known or unknown threat. It can be applied anywhere in the enterprise, be it network perimeter, endpoints, mobile, servers and VDIs. Effectively protecting the entire enterprise from any type of threat, no matter how advanced they may be.
A deep learning neural network is located at the Deep Instinct™ lab. It is the core component of the deep learning cyber security architecture developed by Deep Instinct™. It continuously learns, reflecting the ever-evolving cyber threat arena. The output of its continuous deep learning process is a lightweight prediction model (D-Brain). The D-Brain is then distributed to all managed D-Clients.
Report: Financial institutions face cloud-based threats
Over one year into the pandemic, different financial institutions report costly consequences to falling short of protecting their data storage from cloud-based attacks and network disruptions. The report is based on more than 800 responses from IT professionals working in the financial services industry in North America, Latin America, Europe, and the Asia-Pacific region.
- Data breaches are an increasingly significant cost burden for the industry: Worldwide, financial firms that experienced a data breach reported estimated average losses of roughly $4.2 million per attack, with U.S. organisations hit hardest at $4.7 million in estimated losses.
- Network outages also result in costly burdens: Institutions lose an estimated $3.2 million on average with Asia-Pacific followed by European institutions carrying the heaviest losses at $4.3 million and $3.1 million respectively.
- The industry remains a popular target for cloud-based attacks: Over half of all organisations (54%) surveyed suffered a data breach in the last 12 months with 49% plagued by a cloud malware attack as well.
- Cloud and network-based attacks will continue to be a major threat vector: More than 50% of respondents expect to face a combination of IoT attacks, cloud vulnerabilities including misconfigurations, and data manipulation attempts over the next 12 months.
- Threat resolution teams are embracing network visibility for security hygiene: Globally, network monitoring (76%), threat intelligence (64%), and threat hunting (57%) are considered the most effective mitigation tactics against these threats.
Even before the pandemic, tech companies were increasingly seeking moves to the cloud. The COVID-19 crisis has accelerated the adoption of cloud computing by the financial sector as part of its process of digitalisation. As companies transition and move data, there can be a lack of protection due to a number of factors such as undertrained staff and insufficient firewalls.
“The financial services sector has long been a target for bad actors who are following the cyber money trail into the cloud,” said Anthony James, VP of Product Marketing at Infoblox. “As the pandemic pushed IT infrastructures to rely on remote work, cloud-based technologies that enabled digital transformation also created soft spots for cyber criminals to exploit.”
“This report shows us that cloud compromise has become the biggest cybersecurity issue for financial institutions and the investments they are making to protect themselves,” James continued.