Federico Turrin

Luca Attanasio, Mauro Conti, Denis Donadel et al.

The impact of global warming and the imperative to limit climate change have stimulated the need to develop new solutions based on renewable energy sources. One of the emerging trends in this endeavor are the Electric Vehicles (EVs), which use electricity instead of traditional fossil fuels as a power source, relying on the Vehicle-to-Grid (V2G) paradigm. The novelty of such a paradigm requires careful analysis to avoid malicious attempts. An attacker can exploit several surfaces, such as the remote connection between the Distribution Grid and Charging Supply or the authentication system between the charging Supply Equipment and the Electric Vehicles. However, V2G architecture's high cost and complexity in implementation can restrain this field's research capability. In this paper, we approach this limitation by proposing MiniV2G, an open-source emulator to simulate Electric Vehicle Charging (EVC) built on top of Mininet and RiseV2G. MiniV2G is particularly suitable for security researchers to study and test real V2G charging scenarios. MiniV2G can reproduce with high fidelity a V2G architecture to easily simulate an EV charging process. Finally, we present a MiniV2G application and show how MiniV2G can be used to study V2G communication and develop attacks and countermeasures that can be applied to real systems. Since we believe our tool can be of great help for research in this field, we also made it freely available.

Alessandro Brighente, Mauro Conti, Denis Donadel et al.

EVs (Electric Vehicles) represent a green alternative to traditional fuel-powered vehicles. To enforce their widespread use, both the technical development and the security of users shall be guaranteed. Privacy of users represents one of the possible threats impairing EVs adoption. In particular, recent works showed the feasibility of identifying EVs based on the current exchanged during the charging phase. In fact, while the resource negotiation phase runs over secure communication protocols, the signal exchanged during the actual charging contains features peculiar to each EV. A suitable feature extractor can hence associate such features to each EV, in what is commonly known as profiling. In this paper, we propose EVScout2.0, an extended and improved version of our previously proposed framework to profile EVs based on their charging behavior. By exploiting the current and pilot signals exchanged during the charging phase, our scheme is able to extract features peculiar for each EV, allowing hence for their profiling. We implemented and tested EVScout2.0 over a set of real-world measurements considering over 7500 charging sessions from a total of 137 EVs. In particular, numerical results show the superiority of EVScout2.0 with respect to the previous version. EVScout2.0 can profile EVs, attaining a maximum of 0.88 recall and 0.88 precision. To the best of the authors' knowledge, these results set a new benchmark for upcoming privacy research for large datasets of EVs.

Mauro Conti, Denis Donadel, Federico Turrin

The increasing digitization and interconnection of legacy Industrial Control Systems (ICSs) open new vulnerability surfaces, exposing such systems to malicious attackers. Furthermore, since ICSs are often employed in critical infrastructures (e.g., nuclear plants) and manufacturing companies (e.g., chemical industries), attacks can lead to devastating physical damages. In dealing with this security requirement, the research community focuses on developing new security mechanisms such as Intrusion Detection Systems (IDSs), facilitated by leveraging modern machine learning techniques. However, these algorithms require a testing platform and a considerable amount of data to be trained and tested accurately. To satisfy this prerequisite, Academia, Industry, and Government are increasingly proposing testbed (i.e., scaled-down versions of ICSs or simulations) to test the performances of the IDSs. Furthermore, to enable researchers to cross-validate security systems (e.g., security-by-design concepts or anomaly detectors), several datasets have been collected from testbeds and shared with the community. In this paper, we provide a deep and comprehensive overview of ICSs, presenting the architecture design, the employed devices, and the security protocols implemented. We then collect, compare, and describe testbeds and datasets in the literature, highlighting key challenges and design guidelines to keep in mind in the design phases. Furthermore, we enrich our work by reporting the best performing IDS algorithms tested on every dataset to create a baseline in state of the art for this field. Finally, driven by knowledge accumulated during this survey's development, we report advice and good practices on the development, the choice, and the utilization of testbeds, datasets, and IDSs.

Giovanni Barbieri, Mauro Conti, Nils Ole Tippenhauer et al.

Modern Industrial Control Systems (ICSs) allow remote communication through the Internet using industrial protocols that were not designed to work with external networks. To understand security issues related to this practice, prior work usually relies on active scans by researchers or services such as Shodan. While such scans can identify publicly open ports, they cannot identify legitimate use of insecure industrial traffic. In particular, source-based filtering in Network Address Translation or Firewalls prevent detection by active scanning, but do not ensure that insecure communication is not manipulated in transit. In this work, we compare Shodan-only analysis with large-scale traffic analysis at a local Internet Exchange Point (IXP), based on sFlow sampling. This setup allows us to identify ICS endpoints actually exchanging industrial traffic over the Internet. Besides, we are able to detect scanning activities and what other type of traffic is exchanged by the systems (i.e., IT traffic). We find that Shodan only listed less than 2% of hosts that we identified as exchanging industrial traffic, and only 7% of hosts identified by Shodan actually exchange industrial traffic. Therefore, Shodan do not allow to understand the actual use of insecure industrial protocols on the Internet and the current security practices in ICS communications. We show that 75.6% of ICS hosts still rely on unencrypted communications without integrity protection, leaving those critical systems vulnerable to malicious attacks.