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Latest revision as of 13:00, 8 May 2026

CROSSCON

Cross-platform Open Security Stack for Connected Devices

Full project details (EU Research results portal): https://cordis.europa.eu/project/id/101070537

Project description:

IoT developers face a very fragmented landscape made of very different devices, from bare metal devices with few KB of RAM and limited or no security protection to devices equipped with powerful support for AI and with built-in hardware (HW) to implement Root of Trust (RoT) and Trusted Execution Environments (TEE). Such different devices coexist, and it is an open challenge to guarantee an acceptable level of security across the whole system to avoid “easy” entry points for attackers. The complexity is further exacerbated by the existence of many HW platforms, general purpose but also domain specific, each implementing proprietary instances of RoT and TEE that prevent or make it very difficult for applications and security services to interoperate. CROSSCON aims at addressing all these issues by designing a new open, flexible, highly portable and vendor independent IoT security stack that can run across a variety of different edge devices and multiple HW platforms to offer a consistent security baseline across an entire IoT system. A high-level assurance is guaranteed by the formal verification of the stack specifications. CROSSCON stack offers a unified set of trusted APIs to the layers above. It is modular and among all the security features it offers is possible to configure only the ones needed depending on the underlined HW and firmware. It leverages the security features already implemented in the layers below. In case such security features are missing, like in bare metal devices, the stack offers an entire TEE implementation suitable for such devices. As devices are getting more powerful and use cases more complex, there is the need to add new trusted services as building blocks to implement security at the higher levels, such as protection of the models given in input to ML engines embedded in HW or support for biometrics and template protections. CROSSCON provides the open specifications of the stack along with an open-source reference implementation.

EuroVoc IDs: /natural sciences/computer and information sciences/internet/internet of things

EU Programme: Horizon 2020

EU Project

Project publications:

EU ProjectHas TitleHas CategoryHas TypeHas YearHas DOI
CROSSCONBUSted!!! Microarchitectural Side-Channel Attacks on the MCU Bus InterconnectCybersecurity, Privacy, and TrustConference proceedings2024https://doi.org/10.1109/SP54263.2024.00062
CROSSCONEfficient and Safe I/O Operations for Intermittent SystemsCybersecurity, Privacy, and TrustConference proceedings2023https://doi.org/10.1145/3552326.3587435
CROSSCONHFL: Hardware Fuzzing Loop with Reinforcement LearningCybersecurity, Privacy, and TrustConference proceedings2025https://doi.org/10.23919/DATE64628.2025.10993080
CROSSCONRLFuzz: Accelerating Hardware Fuzzing with Deep Reinforcement LearningCybersecurity, Privacy, and TrustConference proceedings2025https://doi.org/10.1109/HOST64725.2025.11050051
CROSSCONValkyrie: A Response Framework to Augment Runtime Detection of Time-Progressive AttacksCybersecurity, Privacy, and TrustConference proceedings2025https://doi.org/10.1109/DSN64029.2025.00053
CROSSCONShedding Light on Static Partitioning Hypervisors for Arm-based Mixed-Criticality SystemsCybersecurity, Privacy, and TrustConference proceedings2023https://doi.org/10.1109/rtas58335.2023.00011
CROSSCONBridging the Interoperability Gaps Among Trusted Architectures in MCUsCybersecurity, Privacy, and TrustConference proceedings2025https://doi.org/10.1007/978-981-95-3543-9 15
CROSSCONCertified Secure Updates for IoT DevicesCybersecurity, Privacy, and TrustConference proceedings2025https://doi.org/10.1007/978-3-031-92882-6 11
CROSSCONThe Nonce-nce of Web Security: an Investigation of CSP Nonces ReuseCybersecurity, Privacy, and TrustConference proceedings2023https://doi.org/10.1007/978-3-031-54129-2 27
CROSSCONCyber-physical metropolitan area digital substations test bench for evaluating intrusion detection systemsCybersecurity, Privacy, and TrustConference proceedings2024https://doi.org/10.36227/techrxiv.171778519.94792591/v1
CROSSCON?IPS: Software-Based Intrusion Prevention for Bare-Metal Embedded SystemsCybersecurity, Privacy, and TrustConference proceedings2023https://doi.org/10.1007/978-3-031-51482-1 16
CROSSCONOne for All and All for One: GNN-based Control-Flow Attestation for Embedded DevicesCybersecurity, Privacy, and TrustConference proceedings2024https://doi.org/10.1109/SP54263.2024.00182
CROSSCONAppBox: A Black-Box Application Sandboxing Technique for Mobile App Management SolutionsCybersecurity, Privacy, and TrustConference proceedings2023https://doi.org/10.1109/ISCC58397.2023.10217861
CROSSCONFreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated LearningCybersecurity, Privacy, and TrustConference proceedings2024https://doi.org/10.48550/arxiv.2312.04432
CROSSCONDevice Behavioral Profiling for Autonomous Protection Using Deep Neural NetworksCybersecurity, Privacy, and TrustConference proceedings2023https://doi.org/10.1109/ISCC58397.2023.10218275
CROSSCONMind the CORSCybersecurity, Privacy, and TrustConference proceedings2023https://doi.org/10.1109/TPS-ISA58951.2023.00035
CROSSCONCryptojackingTrap: An Evasion Resilient Nature-Inspired Algorithm to Detect Cryptojacking MalwareCybersecurity, Privacy, and TrustPeer reviewed articles2024https://doi.org/10.21227/kwh4-0g27
CROSSCONBiRtIO: VirtIO for Real-Time Network Interface Sharing on the Bao HypervisorCybersecurity, Privacy, and TrustPeer reviewed articles2024https://doi.org/10.1109/ACCESS.2024.3512777
CROSSCONFuzzerfly Effect: Hardware Fuzzing for Memory SafetyCybersecurity, Privacy, and TrustPeer reviewed articles2024https://doi.org/10.1109/MSEC.2024.3365070
CROSSCONHSP-V: Hypervisor-less Static Partitioning for RISC-V COTS PlatformsCybersecurity, Privacy, and TrustPeer reviewed articles2024https://doi.org/10.1109/ACCESS.2024.3399601
CROSSCONBeyond Random Inputs: A Novel ML-Based Hardware FuzzingCybersecurity, Privacy, and TrustPeer reviewed articles2024https://doi.org/10.23919/DATE58400.2024.10546625
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