Artificial Intelligence
Insights on the Human and Machine Trust/Threat Detection and Damage Mitigation Global Market to 2026 – Featuring 3D Robotics, Airbus and Alert Logic Among Others
Dublin, Aug. 05, 2021 (GLOBE NEWSWIRE) — The “Human and Machine Trust/Threat Detection and Damage Mitigation Market by Technology, Solution, Deployment Model, Use Case, Application, Sector(Consumer, Enterprise, Industrial, Government), Industry Vertical, and Region 2021 – 2026” report has been added to ResearchAndMarkets.com’s offering.
This research evaluates the machine trust market. This includes human-machine threat detection and damage mitigation systems in both human-machine and machine-machine security frameworks. The report assesses the market from both technology and solution perspective and associated services. The report also evaluates unique approaches across industry verticals as well as the government sector with forecasts from 2021 to 2026.
Select Report Findings:
- The market for host-based intrusion detection and response systems will reach $3.1 globally by 2026
- The combined global market for TDDM in government office and public infrastructure will reach $9.3B by 2026
- Government initiatives across the world are increasing including TDDM practices as an extremely high-security priority
- Offering end-to-end solutions is the best strategy to achieve optimal success in the threat detection and mitigation solution market
- More advanced TDDM solutions look beyond human-led threat detection and mitigation to autonomous Machine-to-Machine solutions
- Advanced persistent threats have emerged in recent years as a systemic concern for many industry verticals as well as service providers and government sector
- Machine-led automation systems alone are NOT enough to specifically understand the motives behind attacks as there is also a need for cognitive computing enabled human intervention
Threat detection and damage mitigation (TDDM) refers to those processes, procedures, tools that provide the ability of an organization to accurately identify potential threats to networks, systems, applications and/or other assets with emphasis upon the ability to pre-emptively and proactively respond to security events and/or mitigate damage.
More advanced TDDM solutions look beyond human-led threat detection and mitigation to autonomous M2M solutions. Regardless of whether threats originate from human beings or autonomous computer programs, the new vision of TDDM is to create a human-machine threat detection framework in which network operators and systems administrators may choose their level of interaction and control.
Human-machine threat detection systems leverage various techniques such as video surveillance, cloud-controlled cyber-bots, and physical robots, artificial intelligence, biometric security systems, and IoT solutions. Various combinations of automation techniques and technologies are leveraged in orchestration with human-controlled threat detection solutions. Solutions will have varying levels of autonomy, including fully autonomous, remote-controlled (such as via handheld devices), and hybrid variants.
Recent concerns and threats stemming from the COVID-19 pandemic have added a new dimension of safety and security to protect human lives. The new expectation will have a longer-term impact on routine behavior and processes. It has now become very important across the world to control the spread of the COVID-19 virus and protect human lives.
In addition to physical threats associated with pandemics, bad actors also seize the opportunity to engage in various threats against cyber infrastructure. For example, we see aviation, transportation, and public safety industries relying upon human-machine TDDM solutions on an increasingly larger scale to restore human confidence over security systems as part of both industry and government initiatives.
Based on our analysis, we see certain vendors as key to the ecosystem including Check Point, Cisco, Fidelis, FireEye, Fortinet, McAfee, Palo Alto Networks, Symantec, Trend Micro, etc. offer integrated architecture for threat detection and mitigation solutions on all of the options. Companies like IBM QRadar, Splunk, Chronicle Security Backstory, Microsoft Azure Sentinel, etc. provide security analytics solutions.
Key Topics Covered:
1.0 Executive Summary
2.0 Introduction
2.1 Human-Machine Threat Detection and Mitigation
2.1.1 Human to Machine Interaction Framework
2.1.2 Machine to Machine Interaction Framework
2.2 Threat Detection in Zero Trust Environment
2.2.1 Types of Threat and Trust Environment Goals
2.2.1.1 Cyber Environments
2.2.1.2 Physical Environments
2.2.2 Threat Motives and Traceability
2.3 Threat Hunting and Response
2.3.1 Consolidation of Threat Identification and Mitigation Tools
2.4 Humans as Security Sensors
2.4.1 Integrated Human as a Security Sensor (IHaaSS)
2.5 Insider Threat Detection
2.6 Autonomous System as Actor
2.7 Real Time Sensing and Trust
2.8 Designing Threat Detection Programs
2.9 Human Machine Decision Support Systems
2.10 Regulatory Analysis
2.10.1 General Data Protection Regulation
2.10.2 Payment Card Industry Data Security Standard
2.10.3 Health Insurance Portability and Accountability Act
2.10.4 Federal Information Security Management Act
2.10.5 Sarbanes-Oxley Act
2.10.6 Gramm-Leach-Bliley Act
2.10.7 International Organization for Standardization
2.11 COVID 19 Impact and Business Issues
2.12 Market Drivers and Challenges
2.13 Value Chain Analysis
2.13.1 Stakeholder Role and Benefit Analysis
2.13.1.1 Hardware and Equipment Providers
2.13.1.2 Software Solution Providers
2.13.1.3 Integrated Platform Solution Providers
2.13.2 Manufacturing Process Analysis
2.13.3 Manufacturing Cost Structure Analysis
2.13.4 Business Model Analysis
2.13.5 Downstream Customer Group Analysis
3.0 Technology and Application Analysis
3.1 Human to Machine Interaction Technology and products
3.1.1 Device Based Intrusion Detection System
3.1.1.1 Memory Scanning System
3.1.1.2 Network Intrusion Detection System
3.1.1.3 Host-based Intrusion Detection System
3.1.1.4 Perimeter Intrusion Detection System
3.1.2 Screening and Management Platform
3.1.2.1 People and Component Screening
3.1.2.2 Baggage Screening
3.1.3 Security and Surveillance Robots
3.1.4 Disinfection and Disease Protection System
3.1.4.1 Ultraviolet Light-Based Disinfection System
3.1.4.2 Disinfection Chamber/Sanitizing Tunnels
3.1.4.3 Tray Disinfection System
3.1.4.4 Airborne Disease Protection System
3.1.5 Handheld and Photosensitive Detection Device
3.2 Human to Machine Interaction Application Analysis
3.2.1 Explosive Detection
3.2.2 Radiological and Nuclear Detection
3.2.3 Chemical and Biological Detection
3.2.4 Narcotics Detection
3.2.5 Network Intrusion Detection
3.2.6 Disease Control and Management
3.2.7 People and Component Detection
3.2.8 Fire detection
3.3 Machine to Machine Interaction Technology and Products
3.3.1 Cloud Access and Security Brokers (CASB)
3.3.2 Endpoint Detection and Response Systems
3.3.3 Intrusion Detection Systems
3.3.4 Network Firewalls
3.3.5 Malware Sandboxing
3.3.6 Honeypots
3.3.7 Security Information and Event Management System
3.3.8 Threat Intelligence Platforms
3.3.9 Use and Entity Behaviour Analytics
3.4 Machine to Machine Interaction Application Analysis
3.4.1 Unauthorized Identity and Access Detection
3.4.2 Suspicious Behaviour Detection
3.4.3 Malicious Activity Detection
3.4.4 Enterprise Threat Detection
3.4.5 Connected Threat and Attacks Detection
3.4.6 Known Threat Intelligence Feeds
3.4.7 Malware Code Detection
3.4.8 RansomWare Detection
3.5 Human-Machine Threat Detection Use Case Analysis
3.5.1 Public Infrastructure Deployment
3.5.2 Commercial Space Deployment
3.5.3 Institutional Deployment
3.5.4 Industrial Deployment
3.6 Human-Machine Threat Detection across Industry Vertical
3.6.1 Consumer Sector
3.6.2 Enterprise Sector
3.6.3 Industrial Sector
3.6.4 Government Sector
3.7 Infrastructure and People Monitoring
3.8 Advanced Threat Monitoring and Response
3.9 Cloud vs. On-Premise Deployment
3.10 AI and Machine Learning Role
3.11 Ethical AI
3.12 Threat Visualization and Analytics
3.13 Threats to IoT, Edge Computing, and 5G
4.0 Company Analysis
4.1 3D Robotics
4.2 Airbus
4.3 Alert Logic
4.4 Analogic Corporation
4.5 Armor Defense
4.6 AT&T Cybersecurity
4.7 Axis Communication AB
4.8 Barracuda Networks
4.9 Blighter Surveillance Systems
4.10 Broadcom (Blue Coat Systems)
4.11 Boeing
4.12 Chemimage Corporation
4.13 Chemring Group
4.14 Cisco Systems
4.15 Darktrace
4.16 Dell
4.17 Drone Shield
4.18 Elbit Systems
4.19 Exabeam
4.20 FireEye
4.21 Flir Systems
4.22 Forcepoint
4.23 Fortinet
4.24 Group IB
4.25 General Electric
4.26 Google
4.27 Huawei Technologies
4.28 IBM
4.29 Intel
4.30 Lockheed Martin Corporation
4.31 McAfee
4.32 Mirion Technologies
4.33 Medtronic
4.34 Microsoft Corporation
4.35 Northrop Grumman
4.36 Palo Alto Networks
4.37 RAE Systems (Honeywell)
4.38 Rapid7
4.39 Rapiscan Systems
4.40 Raytheon Technologies
4.41 Safran
4.42 Smiths Detection Group
4.43 Thales Group
4.44 Trend Micro
4.45 Collins Aerospace
4.46 WatchGuard
5.0 Market Analysis and Forecast 2021 – 2026
5.1 Global Human Machine Threat Detection Market 2021 – 2026
5.2 Global Human Machine Threat Detection Market by Segment 2021 – 2026
5.3 Human to Machine Interaction Market 2021 – 2026
5.3.1 Global Human to Machine Interaction Market for Threat Detection by Technology
5.3.2 Global Human to Machine Interaction Market for Threat Detection by Solution
5.3.2.1 Global Intrusion Detection Device Market by Product and System
5.3.2.2 Global Screening and Management Machine Market by Product and System
5.3.2.3 Global Security and Surveillance Robots Market by Product and System
5.3.2.4 Global Disinfection and Disease Protection System Market by Product and System
5.3.2.5 Global Handheld and Photosensitive Detection Device Market by Product and System
5.3.2.6 Global Human to Machine Interaction Market for Threat Detection by Service
5.3.3 Global Human to Machine Interaction Market for Threat Detection by Deployment Model
5.3.4 Global Human to Machine Interaction Market for Threat Detection by Use Case
5.3.5 Global Human to Machine Interaction Market for Threat Detection by Application
5.3.6 Global Human to Machine Interaction Market for Threat Detection by Sector
5.3.7 Global Human to Machine Interaction Market for Threat Detection by Industry Vertical
5.3.8 Global Human to Machine Interaction Market for Threat Detection by Region
5.3.8.1 North America Human to Machine Interaction Market for Threat Detection by Country
5.3.8.2 Europe Human to Machine Interaction Market for Threat Detection by Country
5.3.8.3 APAC Human to Machine Interaction Market for Threat Detection by Country
5.3.8.3.1 SEA Human to Machine Interaction Market for Threat Detection by Country
5.3.8.4 Latin America Human to Machine Interaction Market for Threat Detection by Country
5.3.8.5 MEA Human to Machine Interaction Market for Threat Detection by Country
5.4 Machine to Machine Interaction Market 2021 – 2026
5.4.1 Global Machine to Machine Interaction Market for Threat Detection by Technology
5.4.2 Global Machine to Machine Interaction Market for Threat Detection by Solution
5.4.2.1 Global Machine to Machine Interaction Market for Threat Detection by Product and System
5.4.2.2 Global Machine to Machine Interaction Market for Threat Detection by Service
5.4.3 Global Machine to Machine Interaction Market for Threat Detection by Deployment Model
5.4.4 Global Machine to Machine Interaction Market for Threat Detection by Use Case
5.4.5 Global Machine to Machine Interaction Market for Threat Detection by Application
5.4.6 Global Machine to Machine Interaction Market for Threat Detection by Sector
5.4.7 Global Machine to Machine Interaction Market for Threat Detection by Industry Vertical
5.4.8 Global Machine to Machine Interaction Market for Threat Detection by Region
5.4.8.1 North America Machine to Machine Interaction Market for Threat Detection by Country
5.4.8.2 Europe Machine to Machine Interaction Market for Threat Detection by Country
5.4.8.3 APAC Machine to Machine Interaction Market for Threat Detection by Country
5.4.8.3.1 SEA Machine to Machine Interaction Market for Threat Detection by Country
5.4.8.4 Latin America Machine to Machine Interaction Market for Threat Detection by Country
5.4.8.5 MEA Machine to Machine Interaction Market for Threat Detection by Country
6.0 Conclusions and Recommendations
For more information about this report visit https://www.researchandmarkets.com/r/s7aooe
Artificial Intelligence
LG STRENGTHENS EUROPEAN PRESENCE WITH ITS KITCHEN SOLUTIONS SHOWCASE AT MDW 2024
Featuring Advanced AI Technologies and Sleek Design, Company’s Expanded Lineup of Built-in Appliances Brings Outstanding Convenience and Style to the Kitchen
SEOUL, South Korea, April 18, 2024 /PRNewswire/ — LG Electronics (LG) is unveiling its latest built-in kitchen appliances at Milan Design Week (MDW) 2024, taking place in Milan, Italy, from April 16-21. At the center of LG’s Milan showcase are the brand-new Signature Kitchen Suite built-in oven, free zone induction hob, and downdraft hood. Boasting innovative, premium design and highly-convenient features, the company’s refined built-in solutions bring exceptional ease-of-use and effortless elegance to the kitchen.
Signature Kitchen Suite Built-in Oven with Advanced Cooking Technologies
Debuting at MDW 2024 and designed with European consumers in mind, the Signature Kitchen Suite 60-centimeter (24-inch) built-in oven offers a variety of cutting-edge features and AI technologies to elevate the culinary experience. Equipped with Gourmet AI™️, the oven can identify what the user is cooking and automatically select the appropriate cooking mode from 130 recipes. Gourmet AI also enables ‘browning’ control for foods such as pizza and steak, actively keeping tabs on the cooking process and notifying users via the ThinQ™️ app as soon as their food is done. Thanks to video-recognition, LG’s intelligent oven can suggest the optimal settings for the dish being prepared, while real-time video monitoring and time-lapse recording make it easy to check on the progress of one’s meal using the ThinQ app.
Employing enhanced ProBake powered by inverter technology, the new oven delivers uniform heat and fast, efficient cooking with an A++ energy rating. LG’s innovative technology rotates the convection fan back and forth to ensure shorter preheating times, even heating, and crispier results when using the oven’s Air Fry mode. The company’s unique InstaView™️ technology further enhances user convenience, making it possible to see inside simply by knocking twice on the oven door.
Free Zone Induction Hob for Convenient and Flexible Cooking
The Signature Kitchen Suite’s 90-centimeter (36-inch) free zone induction hob presents next-level flexibility and ease-of-use, allowing users to place any size and type of cookware – such as Paella pans and moka pots – anywhere on its cooking surface.* The new appliance can detect and track the position of cookware, eliminating the need to manually cancel and reapply settings when moving a saucepan or skillet from one part of the cooking surface to another. What’s more, the AI technology embedded in the hob can detect the temperature of cookware and automatically lower the heat when necessary, helping to minimize spills and splatter when boiling water or preparing soups and sauces.
Expanded Built-in Lineups for Diverse Kitchen Lifestyles
LG is further bolstering its built-in product lineup with the introduction of the new Signature Kitchen Suite downdraft hood. Made to integrate seamlessly into islands and countertops, the 90-centimeter (36-inch) hood offers a sleek, sophisticated look with its chic black glass and modern frame design. It also provides powerful ventilation, effectively extracting steam and odors for a more pleasant cooking experience.
Additionally, LG has expanded its portfolio of built-in appliances for the European market. Along with new products, such as an 80-centimeter (30-inch) induction hob and built-in combi refrigerators and microwave ovens, the company now provides a wider range of options within its oven lineups – from more product variation to a greater choice of colors and sizes. Among the new models are the Signature Kitchen Suite 122 centimeter (48 inch)-wide French-door refrigerator and stunning appliances from the Transitional lineup, featuring slim handles and satin stainless steel exteriors with a velvety matte finish. To help customers create a curated kitchen aesthetic, the company offers an array of new finishes for its premium built-in products, with black stainless steel and stainless steel joining the previously-introduced black glass finish.
“We are thrilled to showcase our latest built-in innovations at this year’s Milan Design Week, demonstrating our commitment to leading new design trends and meeting the diverse needs of European customers,” said Lyu Jae-cheol, president of LG Electronics Home Appliance & Air Solution Company. “LG will continue to strengthen its presence in Europe through an expanded range of built-in appliances delivering style, performance and convenience in the kitchen.”
Visitors to MDW 2024 in Milan from April 16-21 can experience LG’s latest built-in lineups at the LG booth at Milan Fairgrounds.
* Cookware recognition may vary depending on the size or number of items placed on the surface.
About LG Electronics Home Appliance & Air Solution Company
The LG Home Appliance & Air Solution Company is a global leader in home appliances, air solutions as well as smart home solutions featuring LG ThinQ. The company is creating various solutions with its industry leading core technologies and is committed to making life better and sustainable for consumers and the planet by developing thoughtfully designed kitchen appliances, living appliances, HVAC and air purification solutions. Together, these products deliver enhanced convenience, superb performance, efficient operation and sustainable lifestyle solutions. For more news on LG, visit www.LGnewsroom.com.
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SINGAPORE, April 18, 2024 /PRNewswire/ — DataTracks, a provider of cloud-based software to automate/generate compliance reports for filing with financial/security regulators to more than 28,000 business enterprises in 26 countries, celebrates the completion of 19 years of service and innovation. Founded with a vision to make regulatory compliance “accurate, reliable, timely, and easy”, DataTracks has grown into a leading name in the industry, worldwide with cutting edge software that incorporates “artificial intelligence” aided features to reduce “time to prepare” and improve “accuracy”.
Decades of Dedication and Expertise
Over nearly two decades, DataTracks has achieved significant growth, with its software delivering more than 400,000 reports, showcasing its pivotal role in regulatory reporting. The software and service address regulations across diverse jurisdictions, including SEC in the USA, HMRC and FCA in the UK, Revenue in Ireland, CIPC in South Africa, ACRA in Singapore, MCA in India, SSM in Malaysia and ESMA, EBA, and EIOPA in Europe.
DataTracks distinguishes itself in the industry
(a) with its global footprint (preferred by business enterprises whose regulatory obligations are spread across multiple jurisdictions)
(b) with its state-of-the art software that incorporates “AI/ML” features and
(c) with its credentials for information security (including ISO 9001:2015 and ISO 27001:2013 certifications)
Addressing the employees and spouses in a town hall meeting to celebrate the event, Vinod P John, President of DataTracks said: “We are happy to start our 20th year in the industry. I have to thank the 28,000 clients who trust us and the several hundred employees who developed our software and who helped customers (and our internal team) prepare compliance reports for reaching this milestone. We’ve always believed in leveraging technology to make regulatory compliance as easy, quick, timely, and accurate as possible for our clients. Our continuous investment in AI and machine learning is a testament to this belief, and it’s what keeps us at the forefront of the industry.”
Looking ahead, DataTracks is ready to address upcoming mandates such as the DATA Act and FTA in the US as well as the MBRS/XBRL mandate by SSM in Malaysia.
About DataTracks
DataTracks is a Singapore-based globally renowned leader in providing cloud-based regulatory compliance software for self-use and “black box services” using the same software, catering to 28,000 clients across 26 countries. In 19 years DataTracks has helped its client enterprises prepare more than 400,000 compliance reports for filing with financial/security regulators in several jurisdictions. Financial analysts have rated the quality of reports generated using DataTracks as top of industry for quality; significantly above that of several of its competitors. For further information, visit www.datatracks.com.
For Business Enquiries: Email: [email protected]; Phone: Singapore: +6531582850, US: +1(646)9048324, UK: +44(0)2036088035
Media Contact: [email protected]
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Tailored, lightweight AI models facilitate rapid deployment with low overhead
LAS VEGAS, April 17, 2024 /PRNewswire/ — SAS INNOVATE — Today at SAS Innovate, SAS – a pioneer in data and AI solutions – unveiled a game-changing approach for organizations to tackle business challenges head-on. Introducing lightweight, industry-specific AI models for individual license, SAS is equipping organizations with readily deployable AI technology to productionize real-world use cases with unparalleled efficiency.
AI software provider SAS is uniquely positioned to flex its decades of expertise in applying scalable and trustworthy AI models for prominent global financial, health care, and manufacturing brands, as well as government institutions.
“SAS is evolving its portfolio to meet wider user needs and capture market share with innovative new offerings,” said Chandana Gopal, Research Director, Future of Intelligence, IDC. “An area that is ripe for SAS is productizing models built on SAS’ core assets, talent and IP from its wealth of experience working with customers to solve industry problems.”
In today’s market, the consumption of models is primarily focused on large language models (LLMs) for generative AI. In reality, LLMs are a very small part of the modeling needs of real-world production deployments of AI and decision making for businesses. With the new offering, SAS is moving beyond LLMs and delivering industry-proven deterministic AI models for industries that span use cases such as fraud detection, supply chain optimization, entity management, document conversation and health care payment integrity and more.
Unlike traditional AI implementations that can be cumbersome and time-consuming, SAS’ industry-specific models are engineered for quick integration, enabling organizations to operationalize trustworthy AI technology and accelerate the realization of tangible benefits and trusted results.
Expanding market footprintOrganizations are facing pressure to compete effectively and are looking to AI to gain an edge. At the same time, staffing data science teams has never been more challenging due to AI skills shortages. Consequently, businesses are demanding agility in using AI to solve problems and require flexible AI solutions to quickly drive business outcomes. SAS’ easy-to-use, yet powerful models tuned for the enterprise enable organizations to benefit from a half-century of SAS’ leadership across industries.
Delivering industry models as packaged offerings is one outcome of SAS’ commitment of $1 billion to AI-powered industry solutions. As outlined in the May 2023 announcement, the investment in AI builds on SAS’ decades long focus on providing packaged solutions to address industry challenges in banking, government, health care and more.
“Models are the perfect complement to our existing solutions and SAS Viya platform offerings and cater to diverse business needs across various audiences, ensuring that innovation reaches every corner of our ecosystem,” said Udo Sglavo, Vice President for AI and Analytics, SAS. “By tailoring our approach to understanding specific industry needs, our frameworks empower businesses to flourish in their distinctive environments.”
Bringing AI to the massesSAS is democratizing AI by offering out-of-the-box, lightweight AI models – making AI accessible regardless of skill set – starting with an AI assistant for warehouse space optimization. Leveraging technology like large language models, these assistants cater to nontechnical users, translating interactions into optimized workflows seamlessly and aiding in faster planning decisions.
“SAS Models provide organizations with flexible, timely and accessible AI that aligns with industry challenges,” said Sglavo. “Whether you’re embarking on your AI journey or seeking to accelerate the expansion of AI across your enterprise, SAS offers unparalleled depth and breadth in addressing your business’s unique needs.”
The first SAS Models are expected to be generally available later this year. Learn more about SAS Applied AI and Modeling here: https://blogs.sas.com/content/tag/applied-ai-modeling/.
Today’s announcement was made at SAS Innovate, the data and AI experience for business leaders, technical users and SAS Partners. Keep up with the latest news from SAS by following @SASsoftwareNews on X/Twitter.
About SASSAS is a global leader in data and AI. With SAS software and industry-specific solutions, organizations transform data into trusted decisions. SAS gives you THE POWER TO KNOW®.
SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration. Other brand and product names are trademarks of their respective companies. Copyright © 2024 SAS Institute Inc. All rights reserved.
Editorial Contact:Jennifer [email protected] 202-210-4180 sas.com/news
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