Biblio

Recently, as the use of Internet of Things (IoT) devices has expanded, security issues have emerged. As a solution to the IoT security problem, PUF (Physical Unclonable Function) technology has been proposed, and research on key generation or device authentication using it has been actively conducted. In this paper, we propose a method to apply PUF-based device authentication technology to the Open Connectivity Foundation (OCF) open platform. The proposed method can greatly improve the security level of IoT open platform by utilizing PUF technology.

Recently, it is predicted that interworking between heterogeneous devices will be accelerated due to the openness of the IoT (Internet of Things) platform, but various security threats are also expected to increase. However, most IoT open platforms remain at the level that utilizes existing security technologies. Therefore, a more secure security technology is required to prevent illegal copying and leakage of important data through stealing, theft, and hacking of IoT devices. In addition, a technique capable of ensuring interoperability with existing standard technologies is required. This paper proposes an IoT device authentication method based on PUF (Physical Unclonable Function) that operates on an IoT open platform. By utilizing PUF technology, the proposed method can effectively respond to the threat of exposure of the authentication key of the existing IoT open platform. Above all, the proposed method can contribute to compatibility and interoperability with existing technologies by providing a device authentication method that can be effectively applied to the OCF Iotivity standard specification, which is a representative IoT open platform.

This paper aims to identify Wi-SUN devices using physical layer fingerprint. We first extract physical layer features based on the received Wi-SUN signals, especially focusing on device-specific clock skew and frequency deviation in FSK modulation. Then, these physical layer fingerprints are used to train a machine learning-based classifier and the resulting classifier finally identifies the authorized Wi-SUN devices. Preliminary experiments on Wi-SUN certified chips show that the authenticator with the proposed physical layer fingerprints can distinguish Wi-SUN devices with 100 % accuracy. Since no additional computational complexity for authentication is involved on the device side, our approach can be applied to any Wi-SUN based IoT devices with security requirements.

As the amount of information distributed and processed through IoT(Internet of Things) devices is absolutely increased, various security issues are also emerging. Above all, since IoT technology is directly applied to our real life, there is a growing concern that the dangers of the existing cyberspace can be expanded into the real world. In particular, leaks of keys necessary for authentication and data protection of IoT devices are causing economic and industrial losses through illegal copying and data leakage. Therefore, this paper introduces the research trend of hardware and software based key hiding technology to respond to these security threats, and proposes IoT device authentication techniques using them. The proposed method fundamentally prevents the threat of exposure of the authentication key due to various security vulnerabilities by properly integrating hardware and software based key hiding technologies. That is, this paper provides a more reliable IoT device authentication scheme by using key hiding technology for authentication key management.

Recently, gray-box attacks on white-box cryptographic implementations have succeeded. These attacks are more efficient than white-box attacks because they can be performed without detailed knowledge of the target implementation. The success of the gray-box attack is reportedly due to the unbalanced encodings used to generate the white-box lookup table. In this paper, we propose a method to protect the gray-box attack against white-box implementations. The basic idea is to apply the masking technique before encoding intermediate values during the white-box lookup table generation. Because we do not require any random source in runtime, it is possible to perform efficient encryption and decryption using our method. The security and performance analysis shows that the proposed method can be a reliable and efficient countermeasure.