Security Challenges in the Tactile Internet - Ultra-low-latency networks and real-time haptic communication vulnerabilities

SHILPI MONDAL| DATE: NOVEMBER 12 ,2025

Picture controlling a surgery knife from miles away, sensing every bit of pushback through a smart glove. Or think about guiding a massive machine across the country like you’re right there, hands-on, feeling the grind of steel on steel. This is what the Tactile Internet could bring - sending touch, pressure, and movement back and forth almost instantly, fast enough for humans to react naturally, often said to be within just one millisecond. When actions happen this quickly over open networks, risks shift from theory to reality - not just data leaks but actual injury, broken equipment, lost money. Here’s a close-up view of how these lightning-fast touch systems might get hacked, how attackers could twist split-second delays or fake feedback signals, and what fixes - both tech upgrades and workflow changes - are needed now before things go wrong.

Why the Tactile Internet is different (and riskier) than video or audio

Web apps usually handle delays of dozens or even hundreds of milliseconds - no problem. But touch-based feedback can’t cope. Studies and guidelines show: tasks like remote surgery, delicate machine handling, or precision robots need response times under 10 ms, sometimes near 1 ms, just to feel natural and stay stable. This tight window totally shifts how we think about safety.

Old-school crypto setups take too long 'cause they keep resending data and checking stuff over again; this lag messes up real-time controls plus annoys users when things feel sluggish. Hitting 1 millisecond response time became a big deal in touch-based web experiments.

Safety’s about real-world harm: breaches might not just grab info - tampering with touch signals could lead to bodily harm or wreck machines for good.

Edge computing (MEC) along with time-sensitive networking (TSN) often get pushed as fixes for speed delays - yet shifting operations closer to devices expands where trust is needed while bringing fresh issues around code and systems.

The attack surface: ways hackers might take advantage of touch-based tech

Here’s a breakdown of real threat types sorted by their main focus - timing issues, info accuracy, privacy risks, command pathways, or how people see things.

Delay plus timing shifts - attacks that mess with when data arrives

If control relies on precise timing, someone messing with delays - by slowing things down, adding shaky gaps, or randomly cutting data - can throw off touch-based systems. That might make vibrations wobble unpredictably, push users to react too much or too little, or trigger dizziness when sound, sight, and feel don’t line up. Worst scenarios? Risky machine movements. What sets time-focused hacks apart is they turn timing itself into a tool, not just the data.

One person sneaks between two others while altering commands sent back and forth

Haptic signals usually come as quick, repeated bursts carrying data on speed, location, or pressure. Instead of altering commands directly, an attacker might tweak responses, nudging the device off course - say, by shifting resistance slightly - which risks faulty or risky actions. Because each packet is tiny and sent nonstop, squeezing in solid encryption gets tough without slowing things down.

Replay plus sync-related threats

Playing back old haptic data might trick the senses or make motors move again unexpectedly. Since these systems need precise timing, using delayed packet times could mess things up badly.

Denial-of-service attacks happen when systems get overwhelmed or misused

URLLC or Tactile Internet apps need fixed network capacity. Overloading a system on purpose - say, by swamping a local server or jamming high-priority queues - can block vital touch-based communications, possibly leading to real-world harm. Using slices of the network along with traffic controls offers some protection; still, these setups might draw hackers trying to breach separation layers.

Side-channel or inference attacks on touch-based information

Haptic signals - like force patterns or movement trails - might accidentally expose private details about activities, items, or someone’s physical state. Take a doctor's touch during treatment; that sensation profile could hint at secret industrial methods or personal medical info. If hackers get hold of sensor records or motion data streams, they could piece together confidential scenarios.

Firmware breach plus supply chain weak spots at the device or edge layer

Haptic gadgets like gloves or robotic arms, along with local servers, often use custom code and built-in software. If hackers break into that level, they skip firewalls completely - a tainted software upgrade might twist how pressure gets sent or felt. Devices running on nearby computing hubs (like MEC) mean more spots where attacks can happen.

Adversarial AI and perception manipulation

Some touch-based setups use AI to boost user commands - like guessing moves or measuring push strength. Instead of just working together, sneaky inputs might trick the learning parts into giving risky feedback. This can alter how hard something feels, or mess up timing fixes so the person gets confused.

Leaked data along with secret filming

Constant touch data collection - saved for records, rules checks, or coaching - opens doors to spying. Leaked files might expose private health details or business info; worse yet, they could sync up with sound or visuals to build deeper profiles.

Actual outcomes from real situations

Tele-surgery: 

Hackers add tiny delays into touch-response signals, making doctors react too strongly mid-procedure - putting patients in real danger. That’s not just speculation - research on ultra-fast networks keeps pointing out how risky this application really is.

Remote upkeep in factories: 

When force data’s played back, it makes a robot mimic moves - sometimes wrecking equipment or hurting someone close by.

Stolen ideas: 

Copied touch-based data from a hidden production method shows rivals distinct clues about how it’s made.

Big chaos: 

If hackers hit several key network hubs at once - those running a city's virtual reality and touch-feedback systems - it might shut down essential urban functions overnight.

Why regular safety fixes don’t work as well

Cryptography versus speed: 

TLS setups, checking certificates, or tagging each packet with a MAC keep data safe - yet they slow things down. Lightweight encryption still demands smart design so it doesn’t mess up real-time responses. Some new approaches test tweaked versions of QUIC or TLS, shaped around touch-sensitive applications.

Retransmitting data’s risky:

ARQ or retry methods meant to ensure delivery can introduce random lag, messing up real-time touch feedback. Instead, systems should rely on error-correcting codes or multiple signal routes; however, those eat up more network space and make sync harder.

Edge expands where we place trust:

Using local servers or device-based computing cuts delays, yet multiplies the systems needing protection. Rules are in place to assist, although real-world use still falls short.

Sensible fixes - built in levels, down-to-earth, easy to track

It’s not about one quick fix. When it comes to touch-based tech, protection needs to grow alongside speed, consistency, or risk control - depending on the situation. Here's a mix of hands-on fixes and team setups, each with real compromises you’d have to weigh.

Keep key loops close to the user - that’s how layout shields function

Edge computing (MEC): shift haptic feedback systems closer to endpoints - this slashes lag. Use verified software updates alongside trusted startup routines for tighter device protection. Weigh easier access against stricter machine shielding, fixes, and tracking. Standards from ETSI MEC back these setups.

Deterministic networking but also separation

Wired parts use Time-Sensitive Networking (IEEE-TSN), while wireless relies on 5G URLLC along with segmented networks - both keep delays under control and separate traffic flows. When set up right, TSN plus slicing cuts down jitter so odd timing patterns stand out faster. Yet these systems aren’t simple; they need full-path setup to actually work.

Easy-to-use encryption that’s quick plus checks identity without slowing things down

Go for encryption that checks identity, fits tiny data chunks, works fast on chips built for it - like AEAD modes with AES-GCM or ChaCha20-Poly1305 when you’ve got special circuitry to handle the math quick.

Shift away from bulky handshakes - use session resuming instead, try out 0-RTT tools if you’ve got solid replay safeguards, or set up shared keys ahead of time for vital connections to cut down on back-and-forth. Some newer studies are testing how QUIC can work better for touch-based interactions.

Extra backups or separate routes keep things running - even if one part fails

Shoot copies - or error-tough versions - of touch feedback through separate fast lanes when possible. When a route gets hit or jammed, the rest keep steering alive. Using extra data hurts efficiency, yet it’s usually better than resending later.

Safety covers or backup options nearby

Build backup controls right into devices at the spot: when connection gets too shaky, gadgets switch automatically - hold still, turn on vibration alerts, or start self-driving actions. That way, they don’t need constant signal strength to stay safe.

Live verification plus spotting oddities right away

Set up tools to watch how long actions take, how much pressure is used, and whether commands look off - like odd spikes in force or weird repeats. Use quick checks that lean on caution so real issues are caught without flagging normal use by mistake.

Secure device lifecycle and supply chain controls

Safe startup, verified software, keys built into hardware, or solid check-in during updates must always guard touch devices and local hubs. Checking where parts come from can stop hidden traps planted early.

Keeping data private while tracking info but also recording logs

Use tricks such as noise addition, tight permission rules, also local data merging - so touch records meant for analysis won’t get easily traced back or stolen.

Checking proofs along with proof packages

When it comes to high-stakes uses - like remote surgery - apply strict verification techniques on timing-critical systems while building clear proof files that show how system stability holds up if networks fail or slow down.

Governance plus rules - yet also response guides

People running systems need clear actions for emergencies - like shutting things down fast or alerting teams far away. Working alongside groups such as 3GPP, IEEE, ETSI, and ITU makes it easier to match up on basic safety rules.

Research paths or unresolved questions

Fast-secure coding tools: fresh encryption setup built for tiny, repeated data chunks - works smoothly with dedicated chips.

Safe, lightweight login for short-lived access:

Methods delivering solid confidence minus lengthy back-and-forth steps.

Spotting sneaky changes by checking if touch, sight, or sound don’t match up - using one to test another when something feels off.

Figuring out ways to protect touch-based machine learning from sneaky fake signals that mess up predictions - using tricks to spot weak spots plus training systems to resist tampering.

Rules for safe touch-data records:

Setting which info gets saved, how much time you store it, also ways to guard that data.

Latest school studies along with tech talks show one thing’s certain - when setting up safe touch-based setups, each safety rule needs checking for how it affects speed; because of this demand, digging into solutions isn’t just pressing - it pulls from loads of different fields.

A worker's to-do list - simple moves to start right away

• Pinpoint key touch-based signals then check how much delay or variation they can handle from start to finish.

• Harden endpoints by using secure boot - include signed firmware, while keeping the attack surface small.

• Run control loops on edge devices, while securing MEC machines using local intrusion detection plus regular updates.

• Use AEAD for tiny touch-based messages while leaning on quick reconnects or zero-delay starts when it’s secure enough.

• Use TSN - or something like it - for fixed-line parts, while setting up 5G ultra-reliable links where wireless is needed.

• Set up safety zones plus actions that kick in when network quality drops without warning.

• Keep logs minimal using tight access limits along with data masking when checking stats.

• Try tough tests - like timing tricks or repeating actions - with machine learning edge cases during quality checks.

• Team up with local staff, legal advisors, or safety reps to build shared response plans for digital and physical threats.

  
  

One last idea - put people’s safety at the front

The Tactile Internet gives wild new powers - like remote surgery, distant factories running live, deep interactive training - but now people and stuff are stuck inside automated digital commands. So safety isn’t about firewalls or codes; it’s whether the system keeps folks from getting hurt, even when bits of it fail. If something goes wrong, can someone halt movement right away, no hesitation? When a local device gets hijacked, is there a way to yank it offline without putting anyone in danger?

Solving these issues means network pros, cyber defenders, control techs, hardware builders, also field experts - like surgeons or factory engineers - have to work together. Just copying old internet safety tricks won’t cut it for touch-based systems; instead, we need fresh thinking around protection, shaped by the tight demands of near-instant response times, while making sure reliability and human safety drive how these devices are built from the start.

Citations:

1. Fettweis, G., Boche, H., Wiegand, T., Zielinski, E., Schotten, H., Alcatel-Lucent Stiftung für Kommunikationsforschung, Merz, P., Hirche, S., Festag, A., Häffner, W., Meyer, M., Steinbach, E., Kraemer, R., Steinmetz, R., Hofmann, F., Eisert, P., Scholl, R., Ellinger, F., Weiß, E., & Riedel, I. (2014). The tactile internet. In ITU-T Technology Watch Report. https://www.itu.int/dms_pub/itut/oth/23/01/t23010000230001pdfe.pdf

2. Kalsha, S., & Kalsha, S. (2025, October 1). Tactile Internet: Ultra-Low Latency Networks for Haptic Feedback | QodeQuAY. Qodequay Technologies. https://www.qodequay.com/tactile-internet-haptic-feedback

3. Li, Y., Raison, N., Ourselin, S., Mahmoodi, T., Dasgupta, P., & Granados, A. (2024). AI solutions for overcoming delays in telesurgery and telementoring to enhance surgical practice and education. Journal of Robotic Surgery, 18(1), 403. https://doi.org/10.1007/s11701-024-02153-9

4. The Security and Privacy of Mobile Edge Computing: An Artificial Intelligence Perspective. (n.d.). https://arxiv.org/html/2401.01589v1

5. Sheikh, A. M., Islam, M. R., Habaebi, M. H., Zabidi, S. A., Najeeb, A. R. B., & Kabbani, A. (2025). A survey on Edge Computing (EC) Security Challenges: Classification, threats, and mitigation strategies. Future Internet, 17(4), 175. https://doi.org/10.3390/fi17040175

6. A comprehensive survey of the tactile internet: state-of-the-art and research directions. (2021). In IEEE Communications Surveys & Tutorials [Journal-article]. https://arxiv.org/pdf/2009.12164

7. Satka, Z., Ashjaei, M., Fotouhi, H., Daneshtalab, M., Sjödin, M., & Mubeen, S. (2023). A comprehensive systematic review of integration of time sensitive networking and 5G communication. Journal of Systems Architecture, 138, 102852. https://doi.org/10.1016/j.sysarc.2023.102852

8. Rodriguez-Martin, P., Adamuz-Hinojosa, O., Muñoz, P., Caleya-Sanchez, J., Navarro-Ortiz, J., & Ameigeiras, P. (2025). Empirical analysis of the impact of 5G jitter on time-aware shaper scheduling in a 5G-TSN network. arXiv. https://doi.org/10.48550/arXiv.2503.19555

9. Benetel, & Benetel. (2025, September 10). Time-Sensitive Networking /TSN) and 5G integration. Benetel - OpenRAN Radio Units.  Opening Possibilities.  https://benetel.com/benetel-white-paper-time-sensitive-networking-tsn-and-5g-integration-enabling-deterministic-and-ultra-reliable-communications/

10. Maier, M., Chowdhury, M., Rimal, B. P., & Van, D. P. (2016). The tactile internet: vision, recent progress, and open challenges. IEEE Communications Magazine, 54(5), 138–145. https://doi.org/10.1109/mcom.2016.7470948

11. Mehmet. (2024, January 24). Integration of 5G with Time-Sensitive Networking for Industrial Communications. 5G-ACIA. https://5g-acia.org/whitepapers/integration-of-5g-with-time-sensitive-networking-for-industrial-communications

12. Dahmen-Lhuissier, S. (n.d.). Multi-Access Edge Computing (MEC). ETSI. https://www.etsi.org/technologies/multi-access-edge-computing?

13. Sengupta, J., Dey, D., Ferlin, S., Ghosh, N., & Bajpai, V. (2024). Accelerating Tactile Internet with QUIC: A Security and Privacy Perspective [Journal-article]. arXiv. https://vaibhavbajpai.com/documents/papers/preprints/2024-arxiv-quic.pdf? 

14. Mahbub, M., & Shubair, R. M. (2023). Contemporary advances in multi-access edge computing: A survey of fundamentals, architecture, technologies, deployment cases, security, challenges, and directions. Journal of Network and Computer Applications, 219, 103726. https://doi.org/10.1016/j.jnca.2023.103726

15. Time-Sensitive Networking (TSN) Task Group |. (n.d.). https://1.ieee802.org/tsn/? 

Image Citations:

1. Kalsha, S., & Kalsha, S. (2025, October 1). Tactile Internet: Ultra-Low Latency Networks for Haptic Feedback | QodeQuAY. Qodequay Technologies. https://www.qodequay.com/tactile-internet-haptic-feedback