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How AI brings accessibility and equity to healthcare



How AI brings accessibility and equity to healthcare

The U.S. Census Bureau reports that during the onset of COVID-19 in 2020, 28 million American citizens didn’t have health insurance at any point during the year. And although many Americans did have health insurance, it often does not cover everything individuals need like mental health services and follow-up breast cancer screenings, which aren’t always covered.

This is where artificial intelligence (AI) can step in to provide quality healthcare options at a lower cost. Companies like Vara and Paradromics are already working to increase access, affordability and ultimately healthcare outcomes — and investors are paying close attention.

“AI could really solve this accessibility issue, especially now that an aging population is a big trend across developing and developed countries,” said Lu Zhang, founder of FusionFund, a venture capital firm focused on backing early-stage startups like Paradromics. “The main point is to be able to better understand the root of the disease and to achieve a highly personalized diagnostic and treatment plan.”

Those without access or with minimal health insurance coverage are often Black, Indigenous, and people of color (BIPOC) individuals and are disproportionately impoverished. The Kaiser Family Foundation (KFF) found that “In 2019, non-elderly AIAN [American Indian, Alaska Native], Hispanic, NHOPI [Native Hawaiian and other Pacific Islander] and Black people remained more likely to lack health insurance than their White counterparts.” And although programs and services like Medicaid and the Children’s Health Insurance Program help, “…they do not fully offset the difference, leaving them more likely to be uninsured.” 

Insurance access was made even worse because of the 2020 pandemic, which disproportionately impacted individuals in the communities listed above with job losses and decreases in income, and therefore likely contributed to further disruptions in healthcare and medical coverage, according to KFF.

AI-powered healthcare on the horizon

AI could improve health outcomes by up to 40% and reduce treatment costs up to 50% by improving diagnosis, increasing access to care and enabling precision medicine,” according to Harvard’s School of Public Health,  If implemented correctly at scale, it could save the medical industry upwards of $150 billion in costs by 2025.

“I think we start with, for example, AI for medical imaging, AI for diagnostic or AI for medical sequencing. There’s also more discussion about how we could better improve workflow efficiency,” Zhang said. “When we talk about AI, we only think about AI algorithms, but there’s also other artificial intelligence products like AI robotics.”

Improving access and results in breast cancer screenings

Every year in the U.S., the CDC reports, on average 255,000 cases of breast cancer are diagnosed in women and 2,300 in men — and 42,000 women and 500 men die per year from the same.

As part of proactive healthcare planning and treatment, individuals, particularly women, are encouraged to have a mammogram performed annually or every few years, depending on age. Though, an important distinction particularly related to insurance coverage is regarding the type of screening they should get.  

An annual mammogram is the screening most commonly covered by insurance plans as it is preventative care, according to United Healthcare, a multinational managed healthcare and insurance company. 

However, if an individual goes in for an annual mammogram, for instance, and any abnormalities are found, they are then referred for a diagnostic mammogram, which is a screening that is less commonly covered by insurance, but that is used to diagnose breast cancer.  And since the latter is used to make a diagnosis, more costs are typically associated with it, even if insurance covers part of it, United Healthcare notes.

The high costs for diagnosis is one reason Jonas Muff, founder and CEO of Vara, an AI-powered mammography screening platform, started his company. The company offers a software screening service that can be installed on existing machines and doesn’t require hospitals or healthcare companies to invest in substantial new equipment. Once a center adopts Vara’s technology, the main change (other than improved efficiency) is a branding partnership, which Muff noted is often simple and along the lines of, “Clinic XY powered by Vara.”

Image showing Vara's AI SaaS platform and how it works with breast cancer screening technology.
Images showing Vara’s AI SaaS platform and how it works with breast cancer screening technology.

Provided by Vara.

Vara’s software platform works across the workflow of a radiologist. Muff says Vara uses AI on multiple fronts. The software platform works to seamlessly filter out normal cancer-free mammograms, so the radiologist can spend more time focusing on and analyzing screenings that may have suspicious aspects. Additionally,  Vara’s technology also alerts the radiologist in case they missed a potential case of cancer that might be otherwise overlooked. Muff said the team refers to this feature as Vara’s “safety net,” which, via its AI and machine learning, may more quickly spot potential cancer.

“The vision is really that every woman can afford it. The more clinics Vara is in, the more women can afford these screenings, which is then obviously very good for the patients, but ultimately, it’s also great for businesses and everyone in the cancer treatment industry,” Muff said.

In clinical trials in Germany, where the company was founded, Muff claims that Vara found roughly 40% of all cancers that were missed by the radiologists. To get an idea of the cost savings AI can provide in this way, Vara’s screening services in Mexico are offered for about $15, which Muff noted is typically self-pay. He said women pay for the service with their credit cards, given that they’re not insured for receiving the screenings. If they choose to have a screening performed somewhere else in private clinics without Vara, Muff claims they can expect to pay between $50 to $150 in Mexico per screening.

Personalizing diagnosis and treatments in mental health

Like breast cancer screenings, mental health care and treatment are also often left out of insurance coverage in the U.S. In fact, the National Institute of Mental Health (NIMH) reports that one in five U.S. adults live with a mental illness. However, many barriers exist among insurance plans that can often delay access to treatment for these conditions, cause individuals to travel far distances for in-network providers, or may not cover mental health treatment at all, leaving individuals to pay high out-of-pocket costs.

The National Alliance on Mental Illness (NAMI) cited the above in a 2020 blog post and stated that although measures have been taken to make care for mental health more accessible, it isn’t enough.

“The 2008 Mental Health Parity and Addiction Equity Act, Affordable Care Act and state mental health parity laws require certain healthcare plans to provide mental and physical health benefits equally. And yet, insurers are still not covering mental health care the way they should,” the post reads.

“A behavioral health office visit is over five times more likely to be out-of-network than a primary care appointment,” NAMI reports that, And additionally, in general, the organization has found individuals in need of this type of treatment report increased difficulty with “finding in-network providers and facilities for mental health care compared to general or specialty medical care. Often, going out of network was the only option for treatment. And individuals reported difficulty finding correct information about the in-network providers for their health plans.”

This can leave individuals who are in need of treatment with few options or options that are unaffordable. This is where Paradromics, an AI-powered company, hopes to bridge the gap. 

Paradromics aims to develop a data interface that directly interacts with neural signals from the brain using AI and machine learning. One technology the company developing, called  “Connexus Direct Data Interface,” collects a massive amount of individual neural signals with a fully implantable device designed for long-term daily service. Paradromics reports that its first clinical application is an assistive-communication device for patients who’ve lost the ability to speak or type, but the technology will likely expand to mental health diagnoses in the future. 

“We can imagine a future where certain mental health diagnoses become better understood through a neurological — rather than psychiatric — framework. This type of understanding could contribute to destigmatizing these disorders,” said Matt Angle, CEO of Paradromics. “It is well-known that pharmaceutical treatments, which are broad-acting and have nonspecific action, are not universally effective and pose challenges for individualizing mental health care. Within the large category of mental illness and mood disorders, over 5 million patients in the U.S. suffer from severe, drug-resistant mental illness and could immediately benefit from new treatment modalities.

Though the technology isn’t yet commercially available, Paradromics’ goals include applications that focus on detecting and treating intractable mental illnesses. Paradromics’ devices would be surgically implanted to function and would likely be used therapeutically once a condition has been diagnosed.

“Researchers have shown that depression and mood disorders, for example, are brain-network level phenomena. Promisingly, mood states can be both decoded and modulated using implanted electrodes,” Angle said. “Already we can see clinical trials for depression using older generation brain implants (deep brain stimulators) and the capabilities to decode and modulate mood and other neuropsychiatric states will only get better when DDIs [Direct Data Interfaces] become clinically available.”

Maintaining privacy and quashing bias

While AI can help improve equity and access when insurance coverage falls short, privacy can still be a concern.

“We really need better technology solutions to show that we can protect data privacy. We should not just say whoever uses the technology should have confidentiality, but rather enhance the technology itself,” Zhang said. “For example, you can search within an encryption. That technology solution could enable us to show the public that the data has protection already. This will help them ease their concern regarding the privacy issue.”

Similarly, bias can pose an issue throughout healthcare, so training the algorithms properly, while maintaining privacy, is equally important.

“It is important that we find the right model where we take the human into full account with the training data loop and that we find the right workflow for medical experts,” Muff said, “If you train your algorithm only on data from a certain subpopulation … then it’s not guaranteed that the algorithm will work on every other population, for example. It’s important that you evaluate your algorithms on clinically relevant subtypes. If you don’t, it could do more harm than good.”

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Why trusted execution environments will be integral to proof-of-stake blockchains



Why trusted execution environments will be integral to proof-of-stake blockchains

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Ever since the invention of Bitcoin, we have seen a tremendous outpouring of computer science creativity in the open community. Despite its obvious success, Bitcoin has several shortcomings. It is too slow, too expensive, the price is too volatile and the transactions are too public.

Various cryptocurrency projects in the public space have tried to solve these challenges. There is particular interest in the community to solve the scalability challenge. Bitcoin’s proof-of-work consensus algorithm supports only seven transactions per second throughput. Other blockchains such as Ethereum 1.0, which also relies on the proof-of-work consensus algorithm, also demonstrate mediocre performance. This has an adverse impact on transaction fees. Transaction fees vary with the amount of traffic on the network. Sometimes the fees may be lower than $1 and at other times higher than $50.

Proof-of-work blockchains are also very energy-intensive. As of this writing, the process of creating Bitcoin consumes around 91 terawatt-hours of electricity annually. This is more energy than used by Finland, a nation of about 5.5 million.

While there is a section of commentators that think of this as a necessary cost of protecting the entire financial system securely, rather than just the cost of running a digital payment system, there is another section that thinks that this cost could be done away with by developing proof-of-stake consensus protocols. Proof-of-stake consensus protocols also deliver much higher throughputs. Some blockchain projects are aiming at delivering upwards of 100,000 transactions per second. At this performance level, blockchains could rival centralized payment processors like Visa.  

Figure 1: Validators

The shift toward proof-of-stake consensus is quite significant. Tendermint is a popular proof-of-stake consensus framework. Several projects such as Binance DEX, Oasis Network, Secret Network, Provenance Blockchain, and many more use the Tendermint framework. Ethereum is transitioning toward becoming a proof-of-stake-based network. Ethereum 2.0 is likely to launch in 2022 but already the network has over 300,000 validators. After Ethereum makes the transition, it is likely that several Ethereum Virtual Machine (EVM) based blockchains will follow suit. In addition, there are several non-EVM blockchains such as Cardano, Solana, Algorand, Tezos and Celo which use proof-of-stake consensus.  

Proof-of-stake blockchains introduce new requirements

As proof-of-stake blockchains take hold, it is important to dig deeper into the changes that are unfolding.  

First, there is no more “mining.” Instead, there is “staking.” Staking is a process of putting at stake the native blockchain currency to obtain the right to validate transactions. The staked cryptocurrency is made unusable for transactions, i.e., it cannot be used for making payments or interacting with smart contracts. Validators that stake cryptocurrency and process transactions earn a fraction of the fees that are paid by entities that submit transactions to the blockchain. Staking yields are often in the range of 5% to 15%.  

Second, unlike proof-of-work, proof-of-stake is a voting-based consensus protocol. Once a validator stakes cryptocurrency, it is committing to staying online and voting on transactions. If for some reason, a substantial number of validators go offline, transaction processing would stop entirely. This is because a supermajority of votes are required to add new blocks to the blockchain. This is quite a departure from proof-of-work blockchains where miners could come and go as they pleased, and their long-term rewards would depend on the amount of work they did while participating in the consensus protocol. In proof-of-stake blockchains, validator nodes are penalized, and a part of their stake is taken away if they do not stay online and vote on transactions.  

Figure 2: Honest voting vs. dishonest voting.

Third, in proof-of-work blockchains, if a miner misbehaves, for example, by trying to fork the blockchain, it ends up hurting itself. Mining on top of an incorrect block is a waste of effort. This is not true in proof-of-stake blockchains. If there is a fork in the blockchain, a validator node is in fact incentivized to support both the main chain and the fork. This is because there is always some small chance that the forked chain turns out to be the main chain in the long term. 

Punishing blockchain misbehavior

Early proof-of-stake blockchains ignored this problem and relied on validator nodes participating in consensus without misbehaving. But this is not a good assumption to make in the long term and so newer designs introduce a concept called “slashing.” In case a validator node observes that another node has misbehaved, for example by voting for two separate blocks at the same height, then the observer can slash the malicious node. The slashed node loses part of its staked cryptocurrency. The magnitude of a slashed cryptocurrency depends on the specific blockchain. Each blockchain has its own rules.  

Figure 3: Misbehaving validators are slashed by other validators for reasons such as “Attestation rule offense” and “Proposer rule offense”

Fourth, in proof-of-stake blockchains, misconfigurations can lead to slashing. A typical misconfiguration is one where multiple validators, which may be owned or operated by the same entity, end up using the same key for validating transactions. It is easy to see how this can lead to slashing.  

Finally, early proof-of-stake blockchains had a hard limit on how many validators could participate in consensus. This is because each validator signs a block two times, once during the prepare phase of the protocol and once during the commit phase. These signatures add up and could take up quite a bit of space in the block. This meant that proof-of-stake blockchains were more centralized than proof-of-work blockchains. This is a grave issue for proponents of decentralization and consequently, newer proof-of-stake blockchains are shifting towards newer crypto systems that support signature aggregation. For example, the Boneh-Lynn-Shacham (BLS) cryptosystem supports signature aggregation. Using the BLS cryptosystem, thousands of signatures can be aggregated in such a way that the aggregated signature occupies the space of only a single signature.  

How trusted execution environments can be integral to proof-of-stake blockchains  

While the core philosophy of blockchains revolves around the concept of trustlessness, trusted execution environments can be integral to proof-of-stake blockchains.  

Secure management of long-lived validator keys  

For proof-of-stake blockchains, validator keys need to be managed securely. Ideally, such keys should never be available in clear text. They should be generated and used inside trusted execution environments. Also, trusted execution environments need to ensure disaster recovery, and high availability. They need to be always online to cater to the demands of validator nodes.  

Secure execution of critical code

Trusted execution environments today are capable of more than secure key management. They can also be used to deploy critical code that operates with high integrity. In the case of proof-of-stake validators, it is important that conflicting messages are not signed. Signing conflicting messages can lead to economic penalties according to several proof-of-stake blockchain protocols. The code that tracks blockchain state and ensures that validators do not sign conflicting messages needs to be executed with high integrity.  


The blockchain ecosystem is changing in very fundamental ways. There is a large shift toward using proof-of-stake consensus because it offers higher performance and a lower energy footprint as compared to a proof-of-work consensus algorithm. This is not an insignificant change. 

Validator nodes must remain online and are penalized for going offline. Managing keys securely and always online is a challenge. 

To make the protocol work at scale, several blockchains have introduced punishments for misbehavior. Validator nodes continue to suffer these punishments because of misconfigurations or malicious attacks on them. To retain the large-scale distributed nature of blockchains, new cryptosystems are being adopted. Trusted execution environments that offer disaster recovery, high availability, support new cryptosystems such as BLS and allow for the execution of custom code with high integrity are likely to be an integral part of this shift from proof-of-work to proof-of-stake blockchains.

Pralhad Deshpande, Ph.D., is senior solutions architect at Fortanix.


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How NFTs in the metaverse can improve the value of physical assets in the real world



How NFTs in the metaverse can improve the value of physical assets in the real world

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The metaverse has become inseparable from Web3 culture. Companies are racing to put out their own metaverses, from small startups to Mark Cuban and, of course, Meta. Before companies race to put out a metaverse, it’s important to understand what the metaverse actually is.

Or what it should be.

The prefix “meta” generally means both ”self-referential” or “about.” In other words, a meta-level is something about a lower level. From dictionary.com: 

“-a prefix added to the name of a subject and designating another subject that analyzes the original one but at a more abstract, higher level:

metaphilosophy; metalinguistics.

a prefix added to the name of something that consciously references or comments upon its own subject or features:

a meta-painting of an artist painting a canvas.

The key aspect of both definitions is self-reference. Logically, the term “metaverse” then should be “a universe that analyzes the original one, but at an abstracted level.” In other words, the metaverse will be an abstraction layer that describes our current physical world. 

The metaverse should be an extended reality, not a whole new one. 

And that’s why the trend has been heading toward a metaverse that’s built on crypto. Crypto, just like the world, has a kind of physical nature to it. You can’t copy a Bitcoin or an NFT. Just like the coffee cup on your desk can’t occupy the same physical space as the cup next to it. The space itself is singular and immutable and can’t be copied. Even if you make a 3D-printed replica, it’s not the same cup. So crypto is very well suited to building an immutable layer that describes the real world. In crypto, we can build models of the real world that carry over many of its properties.

The natural opportunity will be in digital twins. Digital twins create a universe of information about buildings or other physical assets and are tied to the physical world. In other words, they are that meta-layer. By integrating blockchain technology, in the form of NFTs, all data and information surrounding the physical twin can be verified and saved, forever, all tracked with the asset itself. When you think about it, digital twins are the metaverse versions of the physical twins, and the technology enhances features of the real world. 

Validation is the key to metaverse truth

When evaluating crypto/blockchain’s relationship to the metaverse, it’s important to remember that crypto is about verification and validation. So when considering blockchain’s relationship to the metaverse, it makes sense to think about it as a digital space that can be validated. 

So in the metaverse, it’s time to expand on what an NFT is and what it can hold. NFTs cannot be copied because they are tied to the validation and verification process in time, which is what makes them nonfungible. As the capabilities of NFTs grow, they are becoming a new information dimension that is tied to the real world.

NFT domains are going to be core to this idea. They become a nonfungible data space, uniquely tied to us and our activity on Web3. In the metaverse, these domain NFTs can represent a house; recording and validating every visitor, repair, event, etc. And that record and that infrastructure can be sold not just with the house but as a core component of the house, increasing the value.

By clearly defining what a true metaverse is, both for developers and investors, we can start to move toward a meaningful version of it. 

Leonard Kish is cofounder of Cortex App, based on YouBase’s distributed date protocol.


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Protecting the modern workforce requires a new approach to third-party security



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Ask any HR leader: they’ll tell you that attracting and retaining employees continues to be a top challenge. While this has never been easy, there’s little doubt that the COVID-19 pandemic (and distributed workforces) have made things even more complex. As you read this article, many workers are actively considering leaving their current roles, which don’t support their long-term goals or desired work-life balance. While organizations attempt to navigate this “Great Resignation,” more than 4 million workers are still resigning every month.

As 2022 marches on, hiring teams face another massive obstacle: global talent shortages. These trends have companies rushing to find creative stop-gap solutions to ensure business continuity in difficult times. It shouldn’t come as a surprise that more companies are relying on third-party vendors, suppliers and partners to meet short-term needs, reduce costs and keep innovation humming. In addition, the rise of the gig economy has more employees entering into nontraditional or temporary working relationships. This trend is particularly prevalent in the healthcare industry, but as many as 36% of American employees have a gig work arrangement in some form, either alongside or instead of a full-time job. 

What’s more, the corporate supplier ecosystem has become exponentially more complex. Amidst the supply chain vulnerabilities revealed by the pandemic, organizations are expanding and diversifying the number of supplier relationships they’re engaging in. Meanwhile, regulators have stepped up efforts to manage these business ecosystems.

In many cases, outsourcing to temporary workers or external partners makes good business sense. Sometimes, given the constraints of the talent pool, there’s simply no other option for a company. Either way, organizations should be aware of the security risks that third parties bring — and the steps they can take to minimize the chances of a breach occurring. 

Third-party security challenges remain prevalent

Bringing a third-party workforce onboard in a rushed way – and without proper governance or security controls in place – leaves organizations open to significant cyber risk. These risks can stem from the third-party users or suppliers themselves or those third parties’ access becoming compromised and used as a conduit for lateral movement, enabling attackers to access the company’s most sensitive data. Sadly, a lack of centralized control over suppliers and partners is all too common, no matter the industry. In many organizations, unlike full-time employees, third-party users are managed on an ad hoc basis by individual departments using manual processes or custom-built solutions. This is a recipe for increased cyber risk.

Take the now-infamous Target breach, which remains among the largest-scale third-party security breaches in history. In this incident, attackers made their way onto the retail giant’s network after compromising login credentials belonging to an employee of an HVAC contractor, eventually stealing 110 million customers’ payment information. 

In today’s world, where outsourcing and remote work are now the norm, third parties require corporate network access to get their jobs done. If companies don’t reconsider third-party security controls – and take action by addressing the root of the problem – they’ll remain open to cyber vulnerabilities that can devastate their business and its reputation.

A pervasive lack of visibility and control

Although reliance on third-party workers and technology is widespread in nearly every industry (and in some, it’s common for an organization to have more third-party users than employees), most organizations still don’t know exactly how many third-party relationships they have. Even worse, most don’t even grasp precisely how many employees each vendor, supplier or partner brings into the relationship or their level of risk. According to one survey conducted by the Ponemon Institute, 66% of respondents have no idea how many third-party relationships their organization has, even though 61% of those surveyed had experienced a breach attributable to a third party. 

Grasping the full extent of third-party access can be particularly challenging when there’s collaboration with outsiders through cloud-based applications like Slack, Microsoft Teams, Google Drive or Dropbox. Of course, the adoption of these platforms skyrocketed with the large-scale shift to remote and hybrid work that has come about over the last two years.

Another challenge is that although an organization may try to maintain a supplier database, it can be near-impossible to ensure that it’s both current and accurate with current technical capabilities. Because of processes like self-registration and guest invites, external identities remain disconnected from the security controls applied to employees. 

Growing regulatory interest and contractual obligations

As incidents and breaches attributable to third parties continue to rise, regulators are taking notice. For instance, Sarbanes-Oxley (SOX) now includes several controls targeted explicitly at managing third-party risk. Even the Cybersecurity Maturity Model Certification (CMMC) explicitly targets improving the cybersecurity maturity of third parties that serve the federal government. The ultimate goal of such regulations is to bring all third-party access under the same compliance controls required for employees so that there’s consistency across the entire workforce and violations can be mitigated quickly.

Today, we expect companies to push their suppliers, vendors and partners to implement more stringent security controls. In the long run, however, such approaches are unsustainable, since it’s difficult, if not impossible, to enforce standards across a third-party organization. Hence, the focus will need to shift to ensuring that identity-based perimeters are robust enough to identify and manage threats that third parties may pose.

Currently, decentralized identity solutions are moving into the mainstream. As these technologies become more widely accepted, they’ll continue to mature. This will help many organizations streamline third-party management in the future. It will also assist companies on their journey toward zero trust-compatible identity postures. Incorporating ongoing security monitoring and implementing continuous identity verification systems will also become increasingly important. 

Five steps to mitigate third-party risk today

Today’s challenges are complex but not unsolvable. Here are five steps organizations can take to improve third-party access governance over the short term.

1) Consolidate third-party management. This process can begin with finance and procurement. Anyone with any contract to provide services to any department in the company should be identified and cataloged in an authoritative system of record that includes information on the access privileges assigned to external users. 

Security teams should test for stale accounts and deprovision any that are no longer needed or in use. In addition, they should assign sponsorship and joint accountability to third-party administrators.

2) Institute vetting and risk-aware onboarding processes. Both the organization and its supplier/vendor need to determine workflows for vetting and onboarding third-party users to ensure they are who they say they are — and that their onboarding process follows the principle of least privilege. Implementing a self-service portal where third-party users can request access and provide required documentation can smooth the path to productivity. Access decisions should be based on risk.  

3) Define and refine policies and controls. The organization — and its vendors and suppliers — should continuously optimize policies and controls to identify potential violations and reduce false positives. Policies and controls must be tested periodically, and security teams should also review employees’ access. Over time, auto-remediation can minimize administrative overhead further.

4) Institute compliance controls for your entire workforce. Look for a third-party access governance solution that will enable consistency across employees and third-party users, especially since regulators increasingly require this. Having access to out-of-the-box compliance reports for SOX, GDPR, HIPAA and other relevant regulations makes it easier to enforce the appropriate controls and provide necessary audit documentation.

5) Implement privileged access management (PAM). Another critical step that organizations can take to boost their cybersecurity maturity is implementing a PAM solution. This will enable the organization to enforce least privileged access and zero-standing privilege automatically across all relevant accounts. 

The world of work will never again look like it did in 2019. The flexibility, agility and access to first-rate talent that businesses gain from embracing modern ways of working make the changes more than worthwhile. And enterprises can realize enormous value within today’s complex and dynamic business relationship and supplier ecosystems. They need to ensure their cybersecurity strategies can keep up by strengthening identity and third-party access governance.

Paul Mezzera is VP of Strategy at Saviynt.


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