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How Deep Learning Technologies Can Help Combat Cyberattacks

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Deep learning is performed through Artificial Neural Networks (ANNs), which are designed to mimic the functionality and connections of neurons seen in the human brain. FREMONT, CA: Almost every business is undergoing a revolution due to artificial intelligence (AI). Deep Learning (DL), an AL methodology, is propelling the high-tech industry forward with an almost infinite index of applications ranging from object recognition for autonomous vehicle systems to potentially saving lives by assisting doctors in more accurately detecting and diagnosing cancer. The most prevalent risks and cyberattacks that cybersecurity teams encounter are listed below; now, it's time to discuss how deep learning technologies might help. Traditionally used malware detection methods, such as standard firewalls, rely on a signature-based detection approach. The company maintains a database of known risks, which it often updates to include newly discovered dangers.


Artificial Intelligence (AI) in Cybersecurity Market Worth $46.3 Billion by 2027- Market Size, Share, Forecasts, & Trends Analysis Report with COVID-19 Impact by Meticulous Research

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Artificial intelligence is changing the game for cybersecurity across several industries by providing cutting-edge security technologies that analyze massive quantities of data. AI technology uses its ability to improve network security over time. Today, several organizations are increasingly implementing AI-powered intelligent security solutions & services to understand and reuse threat patterns to identify new coercions. AI technology provides wider security solutions and simplifies complete recognition and acknowledgment procedures related to cyberattacks. Thus, there is a growing demand for AI-based solutions in the end-use industry for cybersecurity.


3 Ways To Improve Cybersecurity In Your AI Infrastructure

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AI models, applications and systems are not impervious to cyber-attacks. So, organizations must make efforts to protect their AI infrastructure from such threats. A secure AI infrastructure bodes well for the future of your organization's association with intelligent technology. Due to its obvious list of benefits, the dependence of all types of businesses on AI has increased greatly in the last decade or so. Unfortunately, the heavy reliance on AI also becomes a weakness for businesses, especially when you consider the possibility of cyber-attacks that can affect their AI infrastructure.


How Artificial Intelligence Is Changing Cybersecurity

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When it comes to technology, artificial intelligence (AI) is a hot topic. As more designers and programmers integrate AI into their online platforms, it's clear that AIs are more than just science fiction. In fact, using artificial intelligence is well on its way to becoming a standard practice. One of the many industries interested in advancing AI to enhance its tech is cybersecurity. For some, AI programs offer exciting capabilities that reinvent what users expect from security services.


This Cybersecurity Startup Simplifies Endpoint Security With ML Threat Detection. Read To Know How

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Today, in the COVID-19 World, working from home has become an accepted corporate culture, giving rise to security challenges across industries. Enterprises are waking up to the importance of cybersecurity, with rising demand for cybersecurity services among businesses. With such a massive need for cybersecurity, many startups are working towards bringing artificial intelligence into the field and securing companies with their endpoint security. Sequretek is one such company that is known among the circles to use unconventional ways to detect security breaches and using AI to spot an attack from miles away and stop it before it can cause any real damage. Started in 2013 by Pankit Desai and Anand Naik, Sequretek is built on the foundation of'simplifying security' -- less complexity and driving down the cost of ownership.


Securing Machine Identities Needs To Be A Top Cybersecurity Goal In 2021

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Taking a Zero Trust approach to managing every machine identity authentication on a network now ... [ ] could save thousands of hours and dollars in the future. Bottom Line: Bad actors quickly capitalize on the wide gaps in machine identity security, creating one of the most breachable threat surfaces today. Forrester's recent webinar on the topic, How To Secure And Govern Non-Human Identities, estimates that machine identities (including bots, robots and IoT) are growing twice as fast as human identities on organizational networks. Forrester defines machine, or non-human, identities as robotic process automation (bots), robots (industrial, enterprise, medical, military) and IoT devices. The webinar points out that one of the fastest-growing automation types is software bots, with 36% used in finance and accounting, 15% used in business line and 15% in IT.


AI vs. AI: The Future of Cybersecurity

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In fact, it's been around since the 1950s. The problem back then was that computers lacked the ability to store commands, so they could be told what to do but couldn't remember what they did. We've certainly come a long way since then! What are some of the benefits of AI and ML? One of the best use cases we've seen is with how AI and ML can handle the large volume of data that is being produced. ML and AI can help humans manage that data and process things like security data.


Cybersecurity can be made agile with zero-shot AI

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Modern security information and event management and intrusion detection systems leverage ML to correlate network features, identify patterns in data and highlight anomalies corresponding to attacks. Security researchers spend many hours understanding these attacks and trying to classify them into known kinds like port sweep, password guess, teardrop, etc. However, due to the constantly changing attack landscape and the emergence of advanced persistent threats (APTs), hackers are continuously finding new ways to attack systems. A static list of classification of attacks will not be able to adapt to new and novel tactics adopted by adversaries. Also, due to the constant flow of alarms generated by multiple sources in the network, it becomes difficult to distinguish and prioritize particular types of attacks--the classic alarm flooding problem.


Artificial Intelligence (AI) in Cybersecurity 2021

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Organizations across industries are turning to artificial intelligence (AI) in cybersecurity to protect their networks and relieve often …


Security experts predict a global AI-related cyber attack before year-end

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As artificial intelligence technologies become more complex and better integrated with new services and products, executives worldwide are concerned about cyber security vulnerabilities. While AI is a strong tool for security, security experts also predict that malicious actors will utilize artificial intelligence to unleash a global cyber incident in the near future. Today, unauthorized users can get easy access to AI-powered systems to create sophisticated cyber threats. For example, AI chatbots have emerged as a novel doorway to cyber attackers, and the Emotet Trojan malware is hyped as an AI-based cyber threat prototype directed at the financial services sector. A recent global study of early adopters found that over 40 percent of executives have "extreme" or "major" concerns about AI threats, with cybersecurity vulnerabilities leading that list.