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Detection of Energy Consumption Cyber Attacks on Smart Devices

Zainab Alwaisi, Simone Soderi, Rocco De Nicola

TL;DR

A lightweight technique for detecting energy consumption attacks on smart home devices by analyzing received packets that considers TCP, UDP, and MQTT protocols, as well as device statuses, and accounts for resource constraints and promptly alerts administrators upon detecting an attack.

Abstract

With the rapid development of Internet of Things (IoT) technology, intelligent systems are increasingly integrating into everyday life and people's homes. However, the proliferation of these technologies raises concerns about the security of smart home devices. These devices often face resource constraints and may connect to unreliable networks, posing risks to the data they handle. Securing IoT technology is crucial due to the sensitive data involved. Preventing energy attacks and ensuring the security of IoT infrastructure are key challenges in modern smart homes. Monitoring energy consumption can be an effective approach to detecting abnormal behavior and IoT cyberattacks. Lightweight algorithms are necessary to accommodate the resource limitations of IoT devices. This paper presents a lightweight technique for detecting energy consumption attacks on smart home devices by analyzing received packets. The proposed algorithm considers TCP, UDP, and MQTT protocols, as well as device statuses (Idle, active, under attack). It accounts for resource constraints and promptly alerts administrators upon detecting an attack. The proposed approach effectively identifies energy consumption attacks by measuring packet reception rates for different protocols.

Detection of Energy Consumption Cyber Attacks on Smart Devices

TL;DR

A lightweight technique for detecting energy consumption attacks on smart home devices by analyzing received packets that considers TCP, UDP, and MQTT protocols, as well as device statuses, and accounts for resource constraints and promptly alerts administrators upon detecting an attack.

Abstract

With the rapid development of Internet of Things (IoT) technology, intelligent systems are increasingly integrating into everyday life and people's homes. However, the proliferation of these technologies raises concerns about the security of smart home devices. These devices often face resource constraints and may connect to unreliable networks, posing risks to the data they handle. Securing IoT technology is crucial due to the sensitive data involved. Preventing energy attacks and ensuring the security of IoT infrastructure are key challenges in modern smart homes. Monitoring energy consumption can be an effective approach to detecting abnormal behavior and IoT cyberattacks. Lightweight algorithms are necessary to accommodate the resource limitations of IoT devices. This paper presents a lightweight technique for detecting energy consumption attacks on smart home devices by analyzing received packets. The proposed algorithm considers TCP, UDP, and MQTT protocols, as well as device statuses (Idle, active, under attack). It accounts for resource constraints and promptly alerts administrators upon detecting an attack. The proposed approach effectively identifies energy consumption attacks by measuring packet reception rates for different protocols.
Paper Structure (12 sections, 2 equations, 9 figures, 1 table, 1 algorithm)

This paper contains 12 sections, 2 equations, 9 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. Motivation and Contribution
  3. Organization of the paper
  4. Related Work and Background
  5. Proposed Algorithm
  6. Packet Measurements
  7. Energy Measurements
  8. Calculation of normal and abnormal behaviors
  9. Experimentation and Discussion
  10. The testbed scenario
  11. Experimental Results
  12. Conclusion and Future work

Figures (9)

  • Figure 1: Packet Reception Rate measurement in the absence and presence of the attack.
  • Figure 2: A Technique to detect Energy Consumption Attack.
  • Figure 3: Energy consumption measurement of normal and abnormal behaviors of the Raspberry Pi device.
  • Figure 4: Testing Environment.
  • Figure 5: Testbed scenario showing the devices used in our experiment and the sensor used to measure the energy consumption.
  • ...and 4 more figures