The Catalyst IR8140 Heavy Duty Series Router will be Cisco’s first router to support new Capabilities for FAN 1.1. to meet increasing digitization needs. 

In 2019, the Wi-SUN Alliance introduced the f… Read more on Cisco Blogs

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The Catalyst IR8140 Heavy Duty Series Router will be Cisco’s first router to support new Capabilities for FAN 1.1. to meet increasing digitization needs. 

In 2019, the Wi-SUN Alliance introduced the first certified products implementing Field Area Network 1.0, which is a secure, self-forming , self-healing IPv6 wireless mesh network designed to support smart utility, smart city and other use cases operating over large geographic areas.  Based on IETF IoT standards and sub-GHz IEEE 802.15.4 radio, there are today more than 90 certified products supporting electric utility metering, distribution automation, and municipal street lighting applications.

2024 will see the availability of the first certified devices implementing the new FAN 1.1 features, which will include important additional capabilities:

Low power device operation.  The world’s top metering companies have developed FAN’s new low power capabilities.  Low power nodes will be able to function for up to 20 years on battery, targeting use cases such as water metering, gas metering and various wide area, low power monitoring applications.
Higher performance.  FAN 1.1 adds an Orthogonal Frequency Division Multiplexing PHY to the existing 2FSK support, meaning FAN 1.1 data rates will cover the range of 50 Kbps up to 2.4 Mbps.  The higher data rates will be welcome for low latency utility distribution automation applications such as Fault Location Isolation and Restoration (FLISR).
Mesh neighbors will be able to negotiate modulation and data rate.  This “gear shifting” capability can be used, for example, to transition a section of lower throughput metering mesh to a higher throughput mode for fault isolation operations.
Expanded geographic support.  North America, Brazil, Japan, and European Union operation is supported.  Extension to additional 800 and 900 MHz regions is now practical.

A single FAN 1.1 mesh can support thousands of Router nodes, each able to parent low power nodes. A classic utility use case for this topology is a deployment of electric meters (Routers), each parenting one or more water or gas meters.  Adding additional meshes scales a deployment to millions of nodes.

Figure 1 depicts an example FAN 1.1 mesh.  A self-forming, self-healing mesh is formed amongst the Border Router and Routers.  Routers are further able to “parent” low power nodes.  The sub-GHz mesh RF links can stretch to a kilometer or more (depending upon local conditions).  The mesh is configured with a base data rate/modulation, with mesh nodes able to negotiate with neighbors to “gear shift” to a different data rate as required by application specifics.

Figure 1: An Example FAN 1.1 Mesh

The Catalyst IR8100 Heavy Duty Series Industrial Router will be the first member of the Cisco Resilient Mesh solution to be FAN 1.1 certified.   Given its rugged design for harsh outdoor environments, flexible backhaul configuration, and security capabilities, the IR8140 is an ideal FAN 1.1 Border Router.  An individual IR8140 can root a mesh of thousands of FAN 1.1 devices, with millions of scale device networks achieved with the deployment of additional IR8140s.   Following the IR8140, the IR510 Industrial Router, IR530 Range Extender, and Cisco Resilient Mesh Endpoint SDK will also be scheduled for FAN 1.1 certification, rounding out a complete Cisco FAN 1.1 portfolio of Border Routers, Routers, and endpoint design SDK.

Figure 2: Cisco IR8140, IR510, and IR530

“As utility endpoints become smarter by adopting an IP-based network, it becomes imperative to manage the workflows of the field area network with security and scale” said Lakshmi Narayana Jammi, Product Manager at Cisco Industrial IoT. “Wi-SUN addresses this challenge in the field area network by enabling different vendors to interoperate and communicate securely from the customer edge to the utility control center by adopting open-source protocols validated at scale to meet the growing needs of the IoT FAN industry.  Adopting a Wi-SUN standard must be seen as a critical milestone to allow vendor interoperability and various services to be onboarded to the existing Field Area Network.

Cisco’s Wi-SUN solution provides solutions that are Wi-SUN 1.0 and also covers the upcoming Wi-SUN 1.1 use cases, such as gear shifting and support for low-energy devices. Cisco provides a secure, scalable, and simplistic onboarding process and help customers pick backhaul options to transport the data securely from the customer edge to the utility control center and manage the lifecycle of all the communication assets in a scalable manner.”

Large FAN 1.1 networks require a network management system able to provide lifecycle management for million node networks.  Cisco IoT Field Network Director is purpose built and field proven to manage these large-scale networks.

“The Wi-SUN Alliance is thrilled to see the new capabilities of FAN 1.1 coming to fruition” said Phil Beecher, President and CEO of the Wi-SUN Alliance.  “The addition of low power operation and high performance RF to Wi-SUN FAN 1.1 enables use cases from very low power water and gas metering applications all the way up to high performance distribution automation capabilities required by critical utility and smart city operations.  All the while providing enterprise class security within a multi-vendor, interoperable ecosystem”.

For more information about the Wi-SUN Alliance and Field Area Network 1.1, head over to the Wi-SUN FAN information site.

Also see this additional information about Cisco Resilient Mesh products and Cisco Field Network Director.

Finally, if you are attending DISTRIBUTECH next week, join us at Booth 1135 to see the Catalyst IR8140 and our IoT Field Network Director in person, as well key solutions to help utilities with their grid modernization projects in grid security, substation automation, distribution automation, renewable energy, and more.

"}]]  The Catalyst IR8140 Heavy Duty Series Router will be Cisco’s first router to support new Capabilities for FAN 1.1. to meet increasing digitization needs.  Read More Cisco Blogs 

ZTNA hasn’t delivered on the full promise of zero trust

Zero Trust has been all the rage for several years; it states, “never trust, always verify” and assumes every attempt to access the network or a… Read more on Cisco Blogs

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ZTNA hasn’t delivered on the full promise of zero trust

Zero Trust has been all the rage for several years; it states, “never trust, always verify” and assumes every attempt to access the network or an application could be a threat. For the last several years, zero trust network access (ZTNA) has become the common term to describe this type of approach for securing remote users as they access private applications. While I applaud the progress that has been made, major challenges remain in the way vendors have addressed the problem and organizations have implemented solutions. To start with, the name itself is fundamentally flawed. Zero trust network access is based on the logical security philosophy of least privilege. Thus, the objective is to verify a set of identity, posture, and context related elements and then provide the appropriate access to the specific application or resource required…not network level access.

Most classic ZTNA solutions on the market today can’t gracefully provide this level of granular control across the full spectrum of private applications. As a result, organizations have to maintain multiple remote access solutions and, in most scenarios, they still grant access at a much broader network or network segment level.  I believe it’s time to drop the “network” from ZTNA and focus on the original goal of least-privilege, zero trust access (ZTA).

Classic ZTNA drawbacks

With much in life, things are easier said than done and that concept applies to ZTNA and secure remote access. When I talk to IT executives about their current ZTNA deployments or planned initiatives there are a set of concerns and limitations that come up on a regular basis. As a group, they are looking for a cloud or hybrid solution that provides a better user experience, is easier for the IT team to deploy and maintain, and provides a flexible and granular level of security…but many are falling short.

With that in mind, I pulled together a list of considerations to help people assess where they are and where they want to be in this technology space. If you have deployed some form of ZTNA or are evaluating solutions in this area, ask yourself these questions to see if you can, or will be able to, meet the true promise of a true zero trust remote access environment.

Is there a method to keep multiple, individual user to app sessions from piggybacking onto one tunnel and thus increasing the potential of a significant security breach?
Does the reverse proxy utilize next-generation protocols with the ability to support per-connection, per-application, and per-device tunnels to ensure no direct resource access?
How do you completely obfuscate your internal resources so only those allowed to see them can do so?
When do posture and authentication checks take place? Only at initial connection or continuously on a per session basis with credentials specific to a particular user without risk of sharing?
Can you obtain awareness into user activity by fully auditing sessions from the user device to the applications without being hindered by proprietary infrastructure methods?
If you use Certificate Authorities that issue certs and hardware-bound private keys with multi-year validity, what can be done to shrink this timescale and minimize risk exposure?

While the security and architecture elements mentioned above are important, they don’t represent the complete picture when developing a holistic strategy for remote, private application access. There are many examples of strong security processes that failed because they were too cumbersome for users or a nightmare for the IT team to deploy and maintain. Any viable ZTA solution must streamline the user experience and simplify the configuration and enforcement process for the IT team. Security is ‘Job #1’, but overworked employees with a high volume of complex security tools are more likely to make provisioning and configuration mistakes, get overwhelmed with disconnected alerts, and miss legitimate threats. Remote employees frustrated with slow multi-step access processes will look for short cuts and create additional risk for the organization.

To ensure success, it’s important to assess whether your planned or existing private access process meets the usability, manageability and flexibility requirements listed below.

The solution has a unified console enabling configuration, visibility and management from one central dashboard.
Remote and hybrid workers can securely access every type of application, regardless of port or protocol, including those that are session-initiated, peer-to-peer or multichannel in design.
A single agent enables all private and internet access functions including digital experience monitoring functions.
The solution eliminates the need for on-premises VPN infrastructure and management while delivering secure access to all private applications.
The login process is user friendly with a frictionless, transparent method across multiple application types.
The ability to handle both traditional HTTP2 traffic and newer, faster, and more secure HTTP3 methods with MASQUE and QUIC

Cisco Secure Access: A modern approach to zero trust access

Secure Access is Cisco’s full-function Security Service Edge (SSE) solution and it goes far beyond traditional methods in multiple ways. With respect to resource access, our cloud-delivered platform overcomes the limitations of legacy ZTNA. Secure Access supports every factor listed in the above checklists and much more, to provide a unique level of Zero Trust Access (ZTA). Secure Access makes online activity better for users, easier for IT, and safer for everyone.

Here are just a few examples:

To protect your hybrid workforce, our ZTA architectural design has what we call ‘proxy connections’ that connect one user to one application: no more. If the user has access to several apps as once, each app connection has its own ‘private tunnel’. The result is true network isolation as they are completely independent. This eliminates resource discovery and potential lateral movement by rogue users.
We implement per session user ID verification, authentication and rich device compliance posture checks with contextual insights considered.
Cisco Secure Access delivers a broad set of converged, cloud-based security services. Unlike alternatives, our approach overcomes IT complexity through a unified console with every function, including ZTA, managed from one interface. A single agent simplifies deployment with reduced device overhead. One policy engine further eases implementation as once a policy is written, it can be efficiently used across all appropriate security modules.
Hybrid workers get a frictionless process: once authenticated, they go straight to any desired application-with just one click. This capability will transparently and automatically connect them with least privileged concepts, preconfigured security policies and adaptable enforcement measures that the administrator controls.
Connections are quicker and provide high throughput. Highly repetitive authentication steps are significantly reduced.

With this type of comprehensive approach IT and security practitioners can truly modernize their remote access. Security is greatly enhanced, IT operations work is dramatically simplified, and hybrid worker satisfaction and productivity maximized.

To obtain deeper insights into the technical requirements for true zero trust private access and to see how Cisco Secure Access with ZTA overcomes the limitations of ZTNA, view the Deep dive into a modern Zero Trust Access (ZTA) architecture webinar. Also, visit the Cisco SSE Institute site for more information on ZTA and SSE.

We’d love to hear what you think. Ask a Question, Comment Below, and Stay Connected with Cisco Security on social!

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"}]]  Move beyond ZTNA with Zero Trust Access to modernize remote user security  Read More Cisco Blogs 

Turn cloud native chaos into business context

Considering that more than 90% of organizations leveraging public clouds are moving to a multi cloud strategy Cisco Observability Platform [1] promises… Read more on Cisco Blogs

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Turn cloud native chaos into business context

Considering that more than 90% of organizations leveraging public clouds are moving to a multi cloud strategy Cisco Observability Platform [1] promises to “turn cloud native chaos into business context” [2]. Such cloud observability tools for cloud native applications will possibly see wider adoption if the process of setting them up can be simplified. Automations for setting up observability across various cloud vendors – with a single set of APIs [3] – will allow enterprises to focus on their mission critical business applications and user experience rather than dealing with the proprietary methodologies of individual clouds.

Programmability for observability tool integrations

The first step to observability is setting up the conduits that serve up the telemetry data from different cloud vendors to observability tools, such as Cisco Cloud Observability or CCO. Each of the cloud vendors have a proprietary method to set up and manage these data conduits. CCO APIs abstract and automate setting up the connections to the public cloud vendors and let you observe all the cloud infrastructure telemetry data with a single pane of glass.

Once cloud connections are in place, CCO normalizes telemetry data collected from multiple cloud deployments allowing developers to then provision the health rules, anomaly detection, and automated actions which is crucial to proactive troubleshooting of any degradations in business applications.

This blog will be followed by a series of blogs each exploring the CCO APIs listed below.

Cloud Connections API

Documentation
Blog: Leverage Abstraction To Hide Complexity with the AppDynamics Cloud Connection API
Code Exchange repo
DevNet Learning Lab
dCloud Sandbox

Health Rules API

Documentation
Blog: Identify weak links in your application stack with Full-Stack Observability Health Rules
Code Exchange repo
DevNet Learning Lab
dCloud Sandbox

Anomaly Detection API

Documentation
Blog: Identify weak links in your application stack with Full-StackObservability Anomaly Detection
Code Exchange repo
DevNet Learning Lab
dCloud Sandbox

Actions API – Upcoming >Learn more

Ingestion Service API – Upcoming >Learn more

Query Service API – Upcoming >Learn more

Have questions or comments?

Go to our Community page.

References

[1] Cisco Cloud Observability
[2] AppDynamics turns cloud native chaos into business context
[3] Developer Resources

"}]]  Automations for setting up observability across various cloud vendors – with a single set of APIs - will allow enterprises to focus on their mission critical business applications and user experience rather than dealing with the proprietary methodologies of individual clouds.  Read More Cisco Blogs 

Health Rules and Cisco Cloud Observability APIs

Applications are the face of an organization, and we are entering the new age of application observability.[1] Keeping applications running like a… Read more on Cisco Blogs

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Health Rules and Cisco Cloud Observability APIs

Applications are the face of an organization, and we are entering the new age of application observability.[1] Keeping applications running like a well-oiled machine is imperative if the business is to succeed. Considering the complexity of the application stack that is spread across a multi cloud ecosystem, organizations have no choice but to adopt full stack observability that gives them visibility and insights into every entity in their application stack.[2]

Organizations know the ins and outs of their own applications and how best to operate them in production. However, they will not have real-time observability across their entire technology stack unless they tightly integrate with their cloud providers. Data collected because of this integration can then be used to correlate and contextualize across the stack to achieve full stack observability. This is where Cisco Cloud Observability (CCO) comes in. [3]

Cloud Connections with Cisco Cloud Observability

Cloud connections to your account in AWS/Azure/GCP will allow this FSO solution to pull data for the cloud resources and cloud services that you leverage in your application stacks. We address cloud connection API’s in the blogs referenced in [4] [5].

Fig 1. High-level overview of how Cisco Cloud Observability works.

Monitoring Entity Health with Cisco Cloud Observability

Once cloud connections are provisioned to your cloud accounts, be it in AWS or Azure or GCP, data is collected from your cloud resources and services subscribed. To gain insights from this data, the next step is to provision health rules to monitor entity health and automated response actions for the proactive management of entities in your application stack.

For manual provisioning of health rules and actions with ClickOps, you would use the Cisco Cloud Observability portal.[6]

For programmatic provisioning of health rules and actions using API’s [7], you can explore this with:

sample python code [8],
sandbox [9] and
learning lab [10].

As an example, the code and sandbox use the lowest entity in your application stack, namely compute. The same methodology can be used on any entity in the application stack for which data collection is enabled.

Further reading

[1] The Age of Application Observability
[2] Innovation in the Age of Application Observability
[3] About Cisco Cloud Observability
[4] Leverage Abstraction To Hide Complexity with Cisco Cloud Observability Cloud Connection API
[5] Automating Observability with Cisco Cloud Observability Cloud API’s
[6] Health Rules Configuration with ClickOps
[7] API Documentation
[8] DevNet Code Exchange
[9] Sandbox
[10] Learning Lab

"}]]  See how Cisco Cloud Observability helps you tightly integrate with your cloud providers to collect data that can then be used to correlate and contextualize to achieve real-time observability across their entire technology stack.  Read More Cisco Blogs 

Five months after the launch of Webex Connect in August 2023, the enterprise-grade Communications Platform as a Service (CPaaS) has continued to enhance how businesses engage with their customers.… Read more on Cisco Blogs

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Five months after the launch of Webex Connect in August 2023, the enterprise-grade Communications Platform as a Service (CPaaS) has continued to enhance how businesses engage with their customers. With its ability to handle customer communications over multiple digital channels, its variety of integration options, and quick agent escalation, Webex Connect has become an efficient solution that is relied upon by the Cisco Store.

Session Breakdown and Agent Handover

455 total chatbot sessions occurred at the Cisco Store in the first quarter of FY24, but that number jumped to 599 in the second quarter, an almost 32% increase. The number of sessions handled by the bot also increased from 193 in the first quarter to 288 in the second quarter, while the number of total agent handovers increased from 262 to 311. This means that not only were more people interacting with the chatbot, but the bot was able to handle 49% more sessions while still giving customers the opportunity to speak to live agents as they saw fit, all while retaining the conversation context. Webex Connect’s easy interface makes it convenient for a small staff to continuously improve the bot’s responses and speak directly with customers whenever needed.

Channel Breakdown

Customers can select their preferred channels to interact with the chatbot. Over Q2, 97% of the bot’s sessions occurred on the web. The online vs. in-person patterns of shoppers stayed consistent from Q1, as was seen by the almost 59% increase in online interactions. There was a marked decrease in in-person interactions, presumably due to the holiday season that dominated Q2.

Online Interactions [Q1 FY24]

Online Interactions [Q2 FY24]

Conversation Topics

In-person store visitors throughout Q2 generally asked the chatbot questions regarding customer tours, engagement with a live agent, order tracking, women’s apparel, and men’s apparel. Online store visitors asked questions around order tracking, gift vouchers, and customer support. Placing orders and receiving assistance has never been easier using Webex Connect, and customers can get their order questions easily answered through a couple of quick interactions rather than having to drive to an in-store location.

Check back next quarter to see how Webex Connect performed in Q3!

"}]]  Checking in on Webex Connect’s second quarter at the Cisco Store.  Read More Cisco Blogs 

Anomaly Detection and Cisco Cloud Observability APIs

In the Part 1 blog [1], we talked about the importance of application observability and how the application stack is more complex than ever with… Read more on Cisco Blogs

​[[{"value":"

Anomaly Detection and Cisco Cloud Observability APIs

In the Part 1 blog [1], we talked about the importance of application observability and how the application stack is more complex than ever with multi cloud deployments. We saw how the FSO solution, Cisco Cloud Observability [2], can be used to identify and react to cloud native application entity health leveraging Health Rules APIs and Actions API.

One aspect of any APM solution is to ensure that your business applications are healthy. Another key aspect is to ensure that they are performing per the metrics that you lay out. Applications should be performing at or above their expected behavior. How does one specify this expected behavior? Can we leverage machine learning capabilities of the Full-Stack Observability solution to learn what’s normal, and flag when abnormal behavior of an application is detected? This is where anomaly detection [3] comes in. This blog gets you started with how to go about configuring anomaly detection and associate actions when violations are detected.

As in health rules, cloud connections to your cloud accounts starts the data collection from your cloud resources and services. This data forms the basis for the machine learning algorithm to identify abnormal behavior.

Cloud Connections with Cisco Cloud Observability

Review cloud connection API’s in the blogs referenced in [4] [5].

Fig 1. High-level overview of how Cloud Native Application Observability work

Monitoring Entity Health with Cloud Native Application Observability

For manual provisioning of anomaly detection and actions with ClickOps, you would use the Cisco Cloud Observability portal.[6]

For programmatic provisioning of health rules and actions using API’s [7], you can explore this with:

sample python code [8],
sandbox [9] and
learning lab [10].

As an example, the code and sandbox use the lowest entity in you application stack, namely compute. The same methodology can be used on any supported entity in the application stack for which data collection is enabled. You can review the entities enabled for AD in [3].

Further reading

[1] Identify weak links in your application stack with FSO Health Rules
[2] About Cisco Cloud Observability
[3] Anomaly Detection in Cisco Cloud Observability
[4] Leverage Abstraction To Hide Complexity with Cisco Cloud Observability Cloud Connection API
[5] Automating Observability with Cisco Cloud Observability Cloud API’s
[6] Anomaly Detection Configuration with ClickOps
[7] API Documentation
[8] DevNet Code Exchange
[9] Sandbox
[10] Learning Lab

"}]]  How can you learn what’s normal, and flag when abnormal behavior of an application is detected? This blog gets you started with how to configure anomaly detection and associate actions when violations are detected.  Read More Cisco Blogs 

Tech companies and governments will join forces to develop advanced AI detection systems, ensuring a safer online environment.

Human ingenuity boosted by AI capabilities offers new pathways to… Read more on Cisco Blogs

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Tech companies and governments will join forces to develop advanced AI detection systems, ensuring a safer online environment.

Human ingenuity boosted by AI capabilities offers new pathways to address complex societal problems—such as more efficient agricultural production, medical research, and sustainable energy production. AI may even harness the power of networks at scale to finally tip the balance in favor of defenders over cyber threat actors.

However, to realize this enticing vision, more work must be done to counter the rising threat that AI-enabled disinformation poses to people, companies, and society. Advances in AI technology make it faster, easier and cheaper than ever to manipulate and abuse digital content with the aim to mislead and deceive on a massive scale. This is an area where those developing, using, and regulating the technology all have an important role to play if we hope to achieve the potential AI benefits while effectively managing for the new risks it inevitably introduces.

Despite efforts among the public and private sectors to detect and prevent the effects of this shadowy disinformation war, its ramifications are no longer theoretical. The material and reputational impacts of AI-powered manipulation are clear as AI plays an increasing role in scams, fraud, and opinion campaigns.

AI-powered attempts to influence hearts, minds and election processes have been well-publicized, however public awareness has done little to address this growing concern. Neither has it prevented lesser-known individuals or organizations from being targeted. While motives vary, the weaponization of AI to discredit private and public figures, harm organizations, steal money, and distort perceptions of reality demands a coordinated, global content-provenance response.

As more and more data are generated through the normal operations of modern business and our digital-driven lives, the attack surface along with sources for AI disinformation widens. Whether used to generate clicks or profit, large volumes of data increase AI accuracy.

For example, this puts a target on recognizable individuals who have been the subject of hours of high-quality video footage, as well as holders of large amounts of data such as social media platforms, corporations, and governments.

Part of the answer is to ensure companies developing AI-powered technologies do so responsibly. At Cisco, we have extensive experience in secure software development, including the development of AI-powered technologies. And we are an industry leader in developing responsible AI principles and practices that ensure transparency, fairness, accountability, reliability, security and privacy.

We have also seen examples of governments engaging with the industry to better understand both the promise and the risk that comes from widely available AI-powered content generation tools, including the Biden administration’s Safe AI Executive Order and the UK government’s AI Safety Summit. But more work needs to be done by technology developers, implementers, users, and governments working together and in parallel.

Picking up the pace

Cisco’s recent Cybersecurity Readiness Index revealed that only 15% of organizations were in a mature state of readiness to remain resilient when faced with a cybersecurity threat. Just 22% are in a mature state of readiness to protect data. While it’s clear that the pressure is on to leverage AI capabilities, the 2023 Cisco AI Readiness Index showed that 86% of organizations around the world are not fully prepared to integrate AI into their businesses.

In 2024, we will see organizations take considerable strides to address these dual challenges. In particular, they will focus their attention on developing systems to reliably detect AI and mitigate the associated risks.

In her 2024 tech predictions, Cisco Chief Strategy Officer and GM of Applications Liz Centoni summed it up: “Inclusive new AI solutions will guard against cloned voices, deepfakes, social media bots, and influence campaigns. AI models will be trained on large datasets for better accuracy and effectiveness. New mechanisms for authentication and provenance will promote transparency and accountability.”

To date, detecting AI-generated written content has proven stubbornly difficult. AI detection tools have managed only low levels of accuracy, often interpreting AI content as human-generated and returning false positive results for human-written text. This has obvious implications for those in areas that may disallow AI. One such example is education, where students may be penalized if content they have personally written ‘fails’ an AI detector’s algorithm.

To strengthen their guard against AI-based subversion, we can expect tech companies to invest further in this area—improving detection of all forms of AI output. This may take the form of developing mechanisms for content authentication and provenance, allowing users to verify the authenticity and source of AI-generated content.

Leveraging a collective response

In 2024, we anticipate a significant increase in public-private interactions aimed at combating the misuse of AI-generated content. According to Centoni, “In keeping with the G7 Guiding Principles on AI regarding threats to democratic values, the Biden administration’s Safe AI Executive Order, and the EU AI Act, we’ll also see more collaboration between the private sector and governments to raise threat awareness and implement verification and security measures.”

That’s likely to include sanctions against those responsible for digital disinformation campaigns. To address regulatory concerns, businesses will need to double down on protecting their data and detecting threats before the effects of any damaging impact can be felt. This will mean constant vigilance, regular vulnerability assessments, diligent security system updates and thorough network infrastructure auditing.

Moreover, AI’s dual role both in exacerbating and mitigating AI-powered disinformation requires transparency, and a broad approach to protect democratic values and individual rights. Addressing both sides of the equation involves rethinking IT infrastructure. In fact, business leaders are now realizing that their technical infrastructure is their business infrastructure.

Early detection through monitoring and observability, for example, over the complex tapestry of infrastructure, network components, application code and its dependencies, and the user experience can be part of the solution. Identifying and linking potential outcomes to an effective, efficient response is crucial.

AI-powered technologies may finally unlock the answers to problems that have outpaced human innovation throughout history, but it will also unleash new problems outside the range of our own experience and expertise. Carefully developed, strategically deployed technology and regulations can help but only if we all recognize the responsibility we share.

Tech companies have an integral role to play in assisting governments to ensure compliance with new regulations. This is both in terms of developing the capabilities that makes compliance possible and fostering a culture of responsible AI use. Private-public collaboration as well as the implementation of robust verification mechanisms and cybersecurity measures are emerging as the backdrop for mitigating the risks and threats posed by AI-generated content in the year ahead.

With AI as both catalyst and canvas for innovation, this is one of a series of blogs exploring Cisco EVP, Chief Strategy Officer, and GM of Applications Liz Centoni’s tech predictions for 2024. Her complete tech trend predictions can be found in The Year of AI Readiness, Adoption and Tech Integration ebook.

Catch the other blogs in the 2024 Tech Trends series

"}]]  Tech companies and governments will join forces to develop advanced AI detection systems, ensuring a safer online environment.  Read More Cisco Blogs