Sorbonne Researchers Use AI to Enhance Wireless Communication Security

HAL is an open-access archive that facilitates the sharing of scientific research documents from various disciplines. It plays a crucial role in promoting transparency and collaboration in scientific research. The article also discusses Hardware Trojan-based Covert Channels (HTCCs), a significant threat to wireless communications security. It explains how an adversary can embed a malicious modification in the hardware, creating a covert channel for unauthorized information leakage. The researchers propose a deep learning-based solution for detecting and defending against HTCCs. The research was conducted by a team from Sorbonne Université and CNRS LIP6 in Paris, France, and is available on the HAL open-access archive.

What is HAL and its Role in Scientific Research?

HAL, as described in the article, is a multidisciplinary open-access archive that serves as a platform for the deposit and dissemination of scientific research documents. These documents can be published or unpublished and may originate from teaching and research institutions in France or abroad, as well as from public or private research centers. The purpose of HAL is to facilitate the sharing of scientific knowledge, making it accessible to a wider audience. This is particularly important in the field of scientific research, where the exchange of ideas and findings can lead to new discoveries and advancements.

The documents deposited in HAL cover a wide range of disciplines, reflecting the diversity of scientific research. They can be research papers, theses, conference papers, and other types of scientific documents. The open-access nature of HAL means that these documents are freely available to anyone with internet access, promoting transparency and collaboration in scientific research.

HAL plays a crucial role in the scientific community by providing a platform for researchers to share their work and contribute to the collective knowledge of their respective fields. By making research findings accessible, HAL helps to foster a culture of openness and collaboration in scientific research, which is essential for the advancement of science and technology.

What are Hardware Trojan-based Covert Channels (HTCCs)?

The article introduces the concept of Hardware Trojan-based Covert Channels (HTCCs), which pose a significant threat to the security of wireless communications. A Hardware Trojan (HT) is defined as a malicious modification of the hardware performed by an adversary. In the context of wireless Integrated Circuits (ICs), a HT can be embedded inside the Radio Frequency (RF) transmitter, creating a covert channel that can leak information.

The threat of HTCCs is particularly concerning due to the horizontal business model of the IC supply chain, which creates security vulnerabilities that can be exploited by a knowledgeable adversary. This means that an adversary with sufficient knowledge and resources can introduce a HT into the IC during its manufacturing or distribution, creating a covert channel for unauthorized information leakage.

The article emphasizes the need for robust evaluation of HTCC attack models and defenses, given the potential damage that such attacks can cause. This includes understanding the various scenarios in which HTCCs can occur, as well as the different types of signal impairments, noise levels, and HT insertions that can facilitate these attacks.

How Can We Detect and Defend Against HTCCs?

The article proposes a solution for detecting and defending against HTCCs using a deep learning-based approach. The researchers have generated and made open-source a dataset for various HTCC scenarios, representing transmissions from a HT-infected RF transceiver hiding a covert channel that leaks information. This dataset encompasses a wide range of signal impairments, noise levels, and HT insertions, providing a comprehensive resource for evaluating HTCC attack models and defenses.

The proposed deep learning-based HTCC detection defense is described as an “one fit all” solution, meaning that it can deal with all known HTCC scenarios. This circumvents the cost of integrating several distinct defenses, making it a more efficient and cost-effective solution.

The researchers’ approach to HTCC detection and defense demonstrates the potential of artificial intelligence (AI) in enhancing the security of wireless communications. By leveraging the power of deep learning, they have developed a solution that can accurately detect and defend against HTCCs, thereby mitigating the threat posed by these attacks.

Who are the Researchers Behind this Study?

The research was conducted by Alán Rodrigo Díaz Rizo, Abdelrahman Emad Abdelazim, Hassan Aboushady, and Haralampos G. Stratigopoulos from Sorbonne Université and CNRS LIP6 in Paris, France. Their work contributes to the ongoing efforts to enhance the security of wireless communications, particularly in the face of threats such as HTCCs.

These researchers bring their expertise in hardware security and artificial intelligence to address a significant challenge in the field of wireless communications. Their work not only advances our understanding of HTCCs but also provides a practical solution for detecting and defending against these attacks.

Their research, which is available on the HAL open-access archive, reflects the importance of sharing scientific knowledge and findings. By making their research accessible to the wider scientific community, they are contributing to the collective effort to enhance the security of wireless communications.