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New Delhi: The development of remote examinations has come a long way since the beginning of the pandemic, when there was no formal structure for examination practices. The year 2025 will find the continued development of remote examination; the digital examination ecosystem will have matured. Artificial intelligence (AI) proctored exam systems with secure computers, identity verification processes, or workflows and forensics audit trails will have created an environment that appears to be bolstered through layers of protection. However, it is important to recognise that the foundation of any examination process will always be upon a foundation of trust in honesty. The next level of concern surrounding the remote proctoring of examinations will be based on the examination candidates' own devices.
In addition, the examination system of 2025 is, regardless of the overall effectiveness of remote examinations, going to be comprised of many separate, non-integrated examination systems based upon a hodgepodge of technological solutions. Many of today's systems do have layered "security", but they only provide surface protection for the overall success of remote examinations. Three Examples of Technology Solutions Currently Available and used today to assist educators in the remote proctoring of examinations: AI Proctoring (AI) - Artificial Intelligence-Based Proctoring and Secure Browsers, Identity Verification, and Environmental Monitoring Technology.
In an exclusive conversation with TV9English, Manish Mohta, Founder, Learning Spiral, said these measures have drastically reduced visible misconduct, but they struggle with new, stealthy endpoint threats that exploit deeper layers of the device. As AI tools, covert hardware, and OS-level tweaks become accessible to students, traditional proctoring is losing the technological arms race.
Advanced tools for cheating today do not depend on any suspicious activity on the part of users; rather, they conceal themselves from proctoring systems that are currently being used.
Examples include:
• Kernel-level rootkits are typically used to disable or fake the monitoring feature.
• Webcams altered at the firmware level are used to record or manipulate, and deliver pre-recorded videos.
• Background LLM assistants/solvers that can interpret questions/interrogate students for answers.
• Covert HDMI mirroring/display splitters that are used to transmit displays from a computer to another screen or device/display.
• Invisible overlays that cannot be distinguished from legitimate UI elements.
Such attacks can avoid detection by behaviour-based AI and/or lockdown browsers altogether. The problem with cheating is not the student's behaviour but rather the compromised integrity of their devices.
It's not about whether examining devices is more efficient; rather, it’s about whether or not the device is safeguarding the examination procedure. The importance of device-level zero-knowledge monitoring starts there. Unlike traditional monitoring, Device Level Zero Knowledge Monitoring does not inspect or observe the device user. Instead of observing the user, Device Level Zero Knowledge monitoring confirms the device's security posture through various verification methods without accessing private user data.
It verifies that, without storing any data or exposing any identifiable data, no undisclosed automation software or artificial intelligence assistant is in use, no operating system (OS) parts have been changed, no secret hardware has been created that will copy or transfer information, no unrecognised overlays or injected codes are present, and that the environment of the device is the same as its permitted integrity level. This process is much like modern-day banking applications; they can tell if a phone has been rooted or compromised without looking through any of an individual’s personal files.
As technology continues to advance and evolve, many new technologies are emerging that allow for secure enclaves, cryptographic integrity proofs, local audits which will never export data, and privacy-preserving runtime checks as well as tamper-evident logs connected to the device identity, thus shifting to verification of a user’s trust baseline (or what is acceptable) rather than just observing a behaviour on a device (i.e., monitoring a person’s/their behaviour).
The growing use of remote testing in both educational and professional certification settings will continue to be utilised for years to come; however, the continued growth of remote testing creates challenges in that we need to ensure that we protect the integrity of remote testing processes, which cannot happen just through generic or 'one size fits all' approaches in response to remote testing in 2025. Rather, exam integrity going forward will be based on knowing that not only will there be no more eye-in-the-sky monitoring (although more direct surveillance may still exist), but on having confidence that students' testing devices cannot be compromised by any means available to humanity.
