1. WP2: Security aware low power IoT Processor
The 4th International Workshop on Cyber Security – Securing IoT
Lightning talks
Takatsugu Ono
Kyushu University

2. Background and Motivation
The key features of IoT system
Many distributed devices
Connected to the internet
Low performance
The devices can’t execute a rich attacking program
One device is not a threat
But, MANY devices can be a threat
I think the key features of IoT are many distributed embedded devices, and the devices are connected.
The performance of the device is low because a designer focus on reducing power and cost.
So, the IoT devices can't execute a rich attacking program.
It means one device is no threat, but attacker use many devices, it could be a threat.

3. Example: Smart Building
IoT systems
Air conditioner
Internet
Refrigerator
Other systems TV
etc.
Let's think about smart building application
There are some IoT systems in a house, and they are connected to the internet.

4. Example: Smart Building
IoT systems
Air conditioner
Malware
Internet
Refrigerator
Other systems TV
Target
etc.
Here, the attacker tries to attack such as DDoS to the target.
[C] Then, the attacker injects a malware into the IoT system, and highjack them.
[C] The attacker performs the DDoS attack by using the highjacked devices.
To make matters worse, there are many homes.
So the attacker realizes strong DDoS attack exploiting the IoT systems.
Attacker

5. Approach Threat detector Runtime energy-efficient monitoring
Machine-learning based run-time program authentication
Power attack detection, etc
Runtime energy-efficient monitoring
Low-cost, flexible monitoring
Efficient power/energy management
Virtual machine (VM) for IoT devices
Low performance overhead, energy-efficient VM
CPU/Memory architecture
Architectural support for the VM and monitoring system
To solv this problem, we will develop a threat detector, which can detect not authorized program such as malware.

6. Approach Threat detector Runtime energy-efficient monitoring
Machine-learning based run-time program authentication
Power attack detection, etc
Runtime energy-efficient monitoring
Low-cost, flexible monitoring
Efficient power/energy management
Virtual machine (VM) for IoT devices
Low performance overhead, energy-efficient VM
CPU/Memory architecture
Architectural support for the VM and monitoring system
The detector has features of authorized programs and is comparing the features during program execution.
In this research, we will exploit machine learning based approach.

7. Approach Threat detector Runtime energy-efficient monitoring
Machine-learning based run-time program authentication
Power attack detection, etc
Runtime energy-efficient monitoring
Low-cost, flexible monitoring
Efficient power/energy management
Virtual machine (VM) for IoT devices
Low performance overhead, energy-efficient VM
CPU/Memory architecture
Architectural support for the VM and monitoring system
We need features of the program, so we monitor the behavior of the program.
This mechanism should be low cost and energy efficient.

8. Approach Threat detector Runtime energy-efficient monitoring
Machine-learning based run-time program authentication
Power attack detection, etc
Runtime energy-efficient monitoring
Low-cost, flexible monitoring
Efficient power/energy management
Virtual machine (VM) for IoT devices
Low performance overhead, energy-efficient VM
CPU/Memory architecture
Architectural support for the VM and monitoring system
We believe that a VM for IoT devices can extract the behavior.
The requirements are low performance overhead, and energy-efficient.

9. Approach Threat detector Runtime energy-efficient monitoring
Machine-learning based run-time program authentication
Power attack detection, etc
Runtime energy-efficient monitoring
Low-cost, flexible monitoring
Efficient power/energy management
Virtual machine (VM) for IoT devices
Low performance overhead, energy-efficient VM
CPU/Memory architecture
Architectural support for the VM and monitoring system
Also, CPU and Memory architecture should support the low overhead monitoring system.
This system allows executing authorized programs.

10. Conclusions There will be many IoT devices
One device is low performance, but attackers exploit the many devices
We develop a threat detector
Allow to execute only authorized program
Collaboration
Run-time energy-efficient monitoring
IITD: Power, thermal monitoring
KU: Program behavior
CPU/Memory architecture
IITD: Architectural support for light-weight VM
KU: Architectural support for security and power/energy efficiency
IoT devices are increasing.
One device is low performance, but attackers exploit the many devices.
So, we develop a threat detector, which allow to execute only authorized program.
IITD and Kyushu University collaborate to develop the threat detector.
At run-time energy-efficient monitoring area, IITD develops power and thermal monitoring system and Kyushu University analyzes the program behavior.
And, at CPU/Memory architecture area, IITD supports light-weight VM and Kyushu University develops architectural supports for security and power/energy efficiency.

11. Thank you