As with any new and evolving technology, IT and IAM professionals must be aware of the potential digital twin technology benefits, challenges and security risks so that their companies can benefit from the technology without placing systems, products or end users at risk.

Digital Twin Technology Benefits and Challenges in Identity and Access Management

The growing adoption of smart technology in the industrial sector has given rise to the widespread availability and mainstream use of digital twins. About 48 percent of companies already using smart manufacturing plan to embrace digital twin technology in an effort to improve operations and provide better service to customers.

The Digital Twin: Like the Real Thing, but Virtual

Industry 4.0 is bringing sweeping changes to industrial operations. Defined by i-Scoop as “the evolution to cyber-physical systems, representing the fourth industrial revolution on the road to an end-to-end value chain with Industrial IoT and decentralized intelligence,” this widespread digital transformation is bringing a multitude of new technologies to the mainstream, including digital twins. 

The concept of the digital twin originated with NASA as the organization sought effective ways to handle the difficulties associated with the Apollo 13 mission. Using data collected from sensors, a “virtual model of a process, product or service” is created. This digital representation, the twin, can then be used to visualize something physical in detail, glean critical data and apply the information in practical ways. 

With digital twins established as a reality in many manufacturing businesses, the market for the technology is set to hit $15.66 billion by 2023. By 2021, half of large industrial companies will be using digital twins to transform the way they approach manufacturing and customer service. 

Practical Applications for Digital Twins

Because it’s possible to make digital twins of individual components, complete assets, full systems and entire processes, the technology has broad application in a variety of areas.

Testing New Systems Prior to Manufacture 
Companies can use digital twins to create and test systems, equipment ideas and service models before investing in building or implementation. If a model proves effective, its digital twin could theoretically be linked to the physical creation for real-time monitoring. 

Improving Efficiency and Productivity 
In a 2017 prediction regarding the benefits of digital twins, Forbes suggested using the technology could improve the speed of critical processes by 30 percent. According to Gartner, industrial companies could see a 10 percent improvement in effectiveness. The widespread availability of and diverse use cases for digital twins gives businesses in nearly all industries a better understanding of where processes can be streamlined and improved, thus helping to minimize downtime through the practice of predictive maintenance. 

Managing Assets in Real Time 
Using digital twins to monitor daily operations and streamline manufacturing reduces unnecessary wear and tear on machinery and alerts business owners to potential money-saving changes, such as making adjustments in fuel use. Faster maintenance and repair allows companies to maintain a competitive edge by improving overall output. 

Understanding Data to Provide Better Service 
Digital twins also have customer-facing applications, including remote troubleshooting. Using virtual models, technicians can conduct diagnostic testing from anywhere and walk consumers through the proper steps for repair instead of blindly relying on default protocols. Information gathered from these sessions provides valuable insights for future product planning and development. 

Facing New Security Challenges

The faster a new type of technology spreads, the less attention tends to be paid to security at the outset. This forces companies to scramble to put out metaphorical fires when vulnerabilities are exploited, leading to the loss of time and profits.

Because digital twins are based in the cloud and don’t require physical infrastructure, the associated security risks are somewhat lower than with other types of systems. However, the massive amounts of data being collected and utilized is drawn from numerous endpoints, each of which represents a potential area of weakness. It’s estimated 75 percent of digital twins will be integrated with at least five endpoints by 2023, and a time is coming when visualizing complex systems may require the linking of multiple digital twins. 

Every time a new connection is made and more data flows between devices and the cloud, the potential risk for compromise increases. Therefore, businesses considering digital twin technology must be careful not to rush into adoption without assessing and updating current security protocols. Areas of greatest importance include:

• Data encryption 
• Access privileges, including clear definition of user roles 
Principle of least privilege 
• Addressing known device vulnerabilities 
• Routine security audits 

While the insights digital twins provide can help businesses make improvements in processes and gain more control over operations, the introduction of any new system creates new vulnerabilities requiring the attention of IT security professionals. Businesses seeking to implement digital twin technology must consider the potential weaknesses and take appropriate measures to guard against malicious activity so that the full benefits may be realized with a minimal amount of risk.

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As more businesses seek to incorporate internet of things (IoT) technology, hackers are developing new tactics for launching cyberattacks. The very same artificial intelligence (AI) tools companies use to improve internal and customer-facing operations can enable hackers to increase the reach and magnitude of breaches. Hivenets are one of the most potentially devastating developments to arise from the malicious implementation of AI.

What is a Hivenet?

A hivenet is the next step in the evolution of the botnet, groups of automated “bot” programs capable of seeking out vulnerabilities in devices and exploiting them to inject malware. Hivenets can bring together tens or hundreds of thousands of infected devices, creating a “swarmbot.” 

The most alarming difference between a botnet and a hivenet is the hivenet’s ability to think for itself. Dark Reading describes these swarms as “intelligent clusters of compromised devices,” referring to how bots within a hivenet share information, allowing hackers to take a relatively hands-off approach. Hivenets rely on this communication along with predictive technology to make decisions during an attack, resulting in greater “intelligence” and an increased threat for businesses running outdated security systems. 

How are Hivenets Changing Cyberattacks?

Hivenets give hackers the capabilities to supercharge their attacks by increasing distribution, minimizing detection and supporting almost complete automation.

Intelligent Malware 
Attacks using hivenets could be likened to a group of thieves who are in constant communication and have nearly perfected the art of staying invisible. As soon as one thief discovers a weak point, he calls all the others to move in while the target remains completely in the dark about what’s going on. Malware is evolving to fly under the radar the same way, infecting a wider range of devices to create massive hivenets with multiple attack payloads ready to be unleashed on unsuspecting victims. 

Faster Breaches 
Because the bots in hivenets can learn from each other, network vulnerabilities are detected and exploited more quickly. As an attack progresses, the hivenet becomes more “intelligent” and gains the ability to make decisions about which payload provides the best chance of infiltrating a network. 

Distributed Denial of Service (DDoS) Attacks 
DDoS attacks aim to cripple servers with more requests than can be handled at one time or overwhelm databases with excessive queries. The result is the same: Network access is lost, locking businesses out of critical applications and systems. Although these types of attacks are decreasing in frequency, the advent of hivenets has the potential to make DDoS much more devastating. Speed and the sheer force of numbers may allow hackers to overwhelm systems rapidly and carry out a greater number of attacks.

What Can Businesses Do to Combat the Threat?

Hivenets are progressing from emerging threats to frightening realities, thus necessitating proactive responses from companies utilizing and manufacturing IoT technology.

Identifying Points of Vulnerability 
Now is the time for businesses to take inventory of all devices and third parties with access to internal networks, including employee-owned devices, vendor accounts and technologies used to support daily operations. All potential threats posed by these devices must be considered and addressed to minimize the risk of malware infections. 

Exercising Discernment with Implementation 
Not everything designed to be connected to the internet should be, and it’s important for business owners and IT professionals to determine whether a new device is necessary. Jumping on the bandwagon simply for the right to boast of having the “latest and greatest” can introduce serious security problems. Companies should save IoT technology for processes requiring automation and thoroughly research the security protocols of all third-party providers prior to implementation. 

Providing Stronger Security for Consumers 
Companies in the business of manufacturing and distributing IoT devices are responsible for the security of those devices and the data they collect. Because connected technology shares information between users and networks, including the networks of the manufacturer, strong security is required to prevent a single infected device from spreading malware across multiple systems. Makers of these devices must plan to provide and automatically distribute regular firmware updates. 

Improving Internal Security 
There’s a satisfying sort of irony in using AI to beat hackers at their own games. Integrated security platforms with tools to monitor devices and learn to detect attack patterns are designed to uncover malicious activity and should provide an option for isolating infected devices. 

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Conclusion
When faced with a hivenet drawing on AI technology to launch attacks with the ability to evolve during execution, businesses unprepared for modern threats are likely to be overwhelmed. Hackers are only beginning to discover all IoT and AI can do, and they’re taking advantage of every opportunity to make these technologies work for them. Any company relying on or distributing IoT must be ready to guard against, detect and respond to hivenet attacks using smart security systems and intelligent threat mitigation.