C2 Server: What Is It? What Can Be Done to Thwart Them?
what is a c2 server Across a diverse set of markets, cybersecurity attacks are on the rise. Behind the more intentional attacks is a desire to...
4 min read
Ian Ferguson | VP Marketing
:
Nov 16, 2023 12:57:33 PM
The concept of “digital transformation” is hardly new. Since the ‘90s, the phrase has become a widely used, some would say overused, term to describe strategic initiatives organizations undertake to leverage technology and drive innovation in their operations. As our company celebrates its 35th year, the executive team has been giving this concept renewed attention, spurred by the rapid rise of generative AI (GenAI).
What is new is the breadth of operations likely to be affected by this technology. For most businesses, GenAI will likely impact every department, every operation, and every employee. Although we use Artificial Intelligence, this is a subset being discussed here as Machine Learning (ML), where a machine makes a decision based on a model that consists of a large number of values and then iterates based on the feedback to the decisions it made previously.
Three main considerations shaping where AI is currently being deployed in aviation, namely:
AI-enabled vision is helping in-flight refueling be accomplished more effectively than a human pilot can perform. In a similar way to certain vehicles where AI can detect lane departure detection or a need to brake more effectively than a driver, we see AI helping pilots with flight plans and changes, alerting the pilot to potential problems with the aircraft, supporting object avoidance maneuvers, and assisting air traffic decision making. It also helps airports with ground operations move aircraft more effectively, reducing fuel use and saving time on turnarounds.
The increased deployment of sensors in aircraft subsystems has created the opportunity to generate vast swathes of data. This is used to provide more accurate predictive maintenance services, saving money and lives.
The area where AI is being deployed quickly is in easing the time, cost, and risk pressures around these projects. For example, GenAI is being explored to accelerate the testing of code bases to ensure relevant software patches have been deployed to make these systems as immune to cyberattacks as possible. For safety-critical products like aircraft, automobiles, and industrial machinery, engineers must ensure that any system updates do not change the device’s fundamental safety capabilities. A key challenge in safety and security engineering is finding a balance between the fun part (innovating and implementing) and the robustness requirements. GenAI presents an opportunity to accelerate the robustness engineering piece and help us focus on the innovation side.
We are also starting to see deployments of AI where it is used as a key element in increasing the resiliency of systems to cyberattacks. The AI element focuses on learning what normal system behavior looks like, with the intention of identifying “abnormal”.
For military systems, there is a significant shift to deployment of many, more cost-effective drones, working in partnership with highly capable fighters like the F-35. Many of these are flown by wire today (for example, General Atomics Gray Eagle Drone), with the pilots safely located hundreds or thousands of miles away. We are seeing this shift to increasingly autonomous platform operation as part of the next phase of the military battlefield. The fighters are becoming “servers with wings”, providing the edge decision-making as opposed to sending all data back to the cloud.
In conclusion, we feel the world of GenAI can learn a lot from the stories of digital transformation. Digital transformation initiatives have earned their bad rap:
These failures share many common attributes, and at their center is a lack of clear business objectives. Before leaping into the world of GenAI, one needs to consider the “why”. At its core, the allure of GenAI is to automate some type of outcome from this computation. One needs to determine:
Neither path is right or wrong, but not having clarity on your value is a misstep. Many organizations find that from a business perspective, GenAI creates an opportunity for evolution in a company’s business model, enabling, for example, a transition to a subscription-based offering from a “one and done” transaction. Transitioning to AI-enabled processes will be uncomfortable for some. Others will embrace this new way of operating. Encourage a culture of innovation, experimentation, and collaboration across the ecosystem, in which employees are empowered to explore AI-driven ideas and prototype new approaches, and you’ll find that your organization has fully adopted new digital ways of working.
We provide foundational software that is focused on keeping applications isolated from each other. With so many companies now harnessing update mechanisms like containers which can be infused with malware, our software ensures that vital system resources are decoupled from the operating systems running those applications; virtual machines are only allowed to access the minimum set of system resources needed to run their applications. Our hypervisor stays out of the dataplane which again reduces the ability for a hacker to infiltrate and modify the system behavior or extract system secrets.
Interested in hearing more on our thoughts around GenAI? Read our CEO, Tim Reed's guest feature in Forbes, "Here We Go Again: GenAI Ushers In A New Age Of Digital Transformation".
what is a c2 server Across a diverse set of markets, cybersecurity attacks are on the rise. Behind the more intentional attacks is a desire to...
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