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Employee safety is for sale

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10 of the biggest cybersecurity disasters and hacks in 2019
ZDNet’s Beth Mauder looks back on 2019 and the worst incidents that happened in cybersecurity. Read more: https://zd.net/2r6yvfT

In Forrester’s “Predictions 2020: Cybersecurity” report, we projected that the anti-surveillance economy would grow by 15%. At the time, we didn’t know a story about location data would publish a few weeks after our prediction, but we knew that the conditions existed for something like this to occur. Surveillance is now an enterprise risk. Specifically, The New York Times shares how its reporters were able to obtain the location data of specific individuals from the data set. For security leaders, those individuals could represent an executive, shareholder, employee, or contractor for your firm. 

Location data is vital to operational security 

Many companies use compartmentalized facilities and technology to isolate teams working on new mission-critical innovation. The projects have code names, special non-disclosure agreements, and strict third-party contracts to ensure that their secrets are kept safe. All those precautions can be rendered useless, however, because of data brokers’ ability to provide competitive insights about your firm based on location data. For example, say a competitor identifies that your executives have meetings with several early-stage startups in a niche category — they could now identify which companies you might be targeting for acquisition based on where your employees are traveling to. Those competitors could determine that you are meeting with a supplier that makes a specific type of technology, which could clue them in that you are developing a new piece of hardware with specific functionality. Back in the film “Wall Street,” this Bud Fox character followed around various individuals; now, he’d just have to buy data. Data can tell you whether “Blue Horseshoe loves Anacott Steel.” The surveillance economy – the dark side of the data economy – should vault into your risk register in 2020. 

IT and security are clueless to employees’ apps 

Anti-surveillance tools are usually first adopted by end-users that are looking to make their jobs easier. For example, many users run pop-up blockers or add-ons that prevent scripts from running on webpages. However, many of these tools are not supported by IT or security despite them being run on corporate devices. The bottom-up approach will not work for enterprises in the surveillance economy. IT and security need to stay on top of this. Mobile devices are also creating issues because they share enriched data about location on top of browser histories, cookies, and IP addresses. 

BYOD is not new, but new problems exist 

The balance between allowing enterprise data on a mobile device, personal use, and personal ownership of that device is still a balancing act. But as more details on the amount of location data available and the degree to which that data can tie to specific individuals emerge, more complications are added to bring-your-own-device. CISOs need to protect non-corporate-owned devices. Physical security is also a concern, especially as location data intersects with geopolitics and especially when executives or employees with critical knowledge of company initiatives travel abroad to countries where kidnapping or other physical security threats could occur. 

Protecting the privacy of your employees helps you secure the enterprise 

In 2020, we will continue our anti-surveillance research into the tools, techniques, and procedures that security leaders must adopt in order to protect the privacy and security of their employees. In much the same way that companies now offer their employees identity protection as a benefit or discounted subscriptions to enterprise productivity software, they will need to offer the same to help protect online anonymity and prevent technology-enabled surveillance on their employees. CISOs who do a good job on awareness, behavior, and culture will recognize that savvy users will not only appreciate this but come to expect it in the future. Those that do neither will open their firms to data gathering by competitors and investors at best or attackers with malicious intent at worst. 

To learn more predictions from Forrester’s cybersecurity team, download Forrester’s Predictions 2020 guide to understanding the major dynamics that will impact firms next year. 

This post was written by VP, Principal Analyst Jeff Pollard and Fatemeh Khatibloo, and Principal Analyst Heidi Shey. It originally appeared here. 



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Key Criteria for Evaluating Security Information and Event Management Solutions (SIEM)

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Security Information and Event Management (SIEM) solutions consolidate multiple security data streams under a single roof. Initially, SIEM supported early detection of cyberattacks and data breaches by collecting and correlating security event logs. Over time, it evolved into sophisticated systems capable of ingesting huge volumes of data from disparate sources, analyzing data in real time, and gathering additional context from threat intelligence feeds and new sources of security-related data. Next-generation SIEM solutions deliver tight integrations with other security products, advanced analytics, and semi-autonomous incident response.

SIEM solutions can be deployed on-premises, in the cloud, or a mix of the two. Deployment models must be weighed with regard to the environments the SIEM solution will protect. With more and more digital infrastructure and services becoming mission critical to every enterprise, SIEMs must handle higher volumes of data. Vendors and customers are increasingly focused on cloud-based solutions, whether SaaS or cloud-hosted models, for their scalability and flexibility.

The latest developments for SIEM solutions include machine learning capabilities for incident detection, advanced analytics features that include user behavior analytics (UBA), and integrations with other security solutions, such as security orchestration automation and response (SOAR) and endpoint detection and response (EDR) systems. Even though additional capabilities within the SIEM environment are a natural progression, customers are finding it even more difficult to deploy, customize, and operate SIEM solutions.

Other improvements include better user experience and lower time-to-value for new deployments. To achieve this, vendors are working on:

  • Streamlining data onboarding
  • Preloading customizable content—use cases, rulesets, and playbooks
  • Standardizing data formats and labels
  • Mapping incident alerts to common frameworks, such as the MITRE ATT&CK framework

Vendors and service providers are also expanding their offerings beyond managed SIEM solutions to à la carte services, such as content development services and threat hunting-as-a-service.

There is no one-size-fits-all SIEM solution. Each organization will have to evaluate its own requirements and resource constraints to find the right solution. Organizations will weigh factors such as deployment models or integrations with existing applications and security solutions. However, the main decision factor for most customers will revolve around usability, affordability, and return on investment. Fortunately, a wide range of solutions available in the market can almost guarantee a good fit for every customer.

How to Read this Report

This GigaOm report is one of a series of documents that helps IT organizations assess competing solutions in the context of well-defined features and criteria. For a fuller understanding consider reviewing the following reports:

Key Criteria report: A detailed market sector analysis that assesses the impact that key product features and criteria have on top-line solution characteristics—such as scalability, performance, and TCO—that drive purchase decisions.

GigaOm Radar report: A forward-looking analysis that plots the relative value and progression of vendor solutions along multiple axes based on strategy and execution. The Radar report includes a breakdown of each vendor’s offering in the sector.

Solution Profile: An in-depth vendor analysis that builds on the framework developed in the Key Criteria and Radar reports to assess a company’s engagement within a technology sector. This analysis includes forward-looking guidance around both strategy and product.

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Key Criteria for Evaluating Secure Service Access

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Since the inception of large-scale computing, enterprises, organizations, and service providers have protected their digital assets by securing the perimeter of their on-premises data centers. With the advent of cloud computing, the perimeter has dissolved, but—in most cases—the legacy approach to security hasn not. Many corporations still manage the expanded enterprise and remote workforce as an extension of the old headquarters office/branch model serviced by LANs and WANs.

Bolting new security products onto their aging networks increased costs and complexity exponentially, while at the same time severely limiting their ability to meet regulatory compliance mandates, scale elastically, or secure the threat surface of the new any place/any user/any device perimeter.

The result? Patchwork security ill-suited to the demands of the post-COVID distributed enterprise.

Converging networking and security, secure service access (SSA) represents a significant shift in the way organizations consume network security, enabling them to replace multiple security vendors with a single, integrated platform offering full interoperability and end-to-end redundancy. Encompassing secure access service edge (SASE), zero-trust network access (ZTNA), and extended detection and response (XDR), SSA shifts the focus of security consumption from being either data center or edge-centric to being ubiquitous, with an emphasis on securing services irrespective of user identity or resources accessed.

This GigaOm Key Criteria report outlines critical criteria and evaluation metrics for selecting an SSA solution. The corresponding GigaOm Radar Report provides an overview of notable SSA vendors and their offerings available today. Together, these reports are designed to help educate decision-makers, making them aware of various approaches and vendors that are meeting the challenges of the distributed enterprise in the post-pandemic era.

How to Read this Report

This GigaOm report is one of a series of documents that helps IT organizations assess competing solutions in the context of well-defined features and criteria. For a fuller understanding consider reviewing the following reports:

Key Criteria report: A detailed market sector analysis that assesses the impact that key product features and criteria have on top-line solution characteristics—such as scalability, performance, and TCO—that drive purchase decisions.

GigaOm Radar report: A forward-looking analysis that plots the relative value and progression of vendor solutions along multiple axes based on strategy and execution. The Radar report includes a breakdown of each vendor’s offering in the sector.

Solution Profile: An in-depth vendor analysis that builds on the framework developed in the Key Criteria and Radar reports to assess a company’s engagement within a technology sector. This analysis includes forward-looking guidance around both strategy and product.

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Key Criteria for Evaluating Edge Platforms

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Edge platforms leverage distributed infrastructure to deliver content, computing, and security closer to end devices, offloading networks and improving performance. We define edge platforms as the solutions capable of providing end users with millisecond access to processing power, media files, storage, secure connectivity, and related “cloud-like” services.

The key benefit of edge platforms is bringing websites, applications, media, security, and a multitude of virtual infrastructures and services closer to end devices compared to public or private cloud locations.

The need for content proximity started to become more evident in the early 2000s as the web evolved from a read-only service to a read-write experience, and users worldwide began both consuming and creating content. Today, this is even more important, as live and on-demand video streaming at very high resolutions cannot be sustained from a single central location. Content delivery networks (CDNs) helped host these types of media at the edge, and the associated network optimization methods allowed them to provide these new demanding services.

As we moved into the early 2010s, we experienced the rapid cloudification of traditional infrastructure. Roughly speaking, cloud computing takes a server from a user’s office, puts it in a faraway data center, and allows it to be used across the internet. Cloud providers manage the underlying hardware and provide it as a service, allowing users to provision their own virtual infrastructure. There are many operational benefits, but at least one unavoidable downside: the increase in latency. This is especially true in this dawning age of distributed enterprises for which there is not just a single office to optimize. Instead, “the office” is now anywhere and everywhere employees happen to be.

Even so, this centralized, cloud-based compute methodology works very well for most enterprise applications, as long as there is no critical sensitivity to delay. But what about use cases that cannot tolerate latency? Think industrial monitoring and control, real-time machine learning, autonomous vehicles, augmented reality, and gaming. If a cloud data center is a few hundred or even thousands of miles away, the physical limitations of sending an optical or electrical pulse through a cable mean there are no options to lower the latency. The answer to this is leveraging a distributed infrastructure model, which has traditionally been used by content delivery networks.

As CDNs have brought the internet’s content closer to everyone, CDN providers have positioned themselves in the unique space of owning much of the infrastructure required to bring computing and security closer to users and end devices. With servers close to the topological edge of the network, CDN providers can offer processing power and other “cloud-like” services to end devices with only a few milliseconds latency.

While CDN operators are in the right place at the right time to develop edge platforms, we’ve observed a total of four types of vendors that have been building out relevant—and potentially competing—edge infrastructure. These include traditional CDNs, hyperscale cloud providers, telecommunications companies, and new dedicated edge platform operators, purpose-built for this emerging requirement.

How to Read this Report

This GigaOm report is one of a series of documents that helps IT organizations assess competing solutions in the context of well-defined features and criteria. For a fuller understanding consider reviewing the following reports:

Key Criteria report: A detailed market sector analysis that assesses the impact that key product features and criteria have on top-line solution characteristics—such as scalability, performance, and TCO—that drive purchase decisions.

GigaOm Radar report: A forward-looking analysis that plots the relative value and progression of vendor solutions along multiple axes based on strategy and execution. The Radar report includes a breakdown of each vendor’s offering in the sector.

Vendor Profile: An in-depth vendor analysis that builds on the framework developed in the Key Criteria and Radar reports to assess a company’s engagement within a technology sector. This analysis includes forward-looking guidance around both strategy and product.

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