arXiv subjects

Panos Papadimitratos

Publications and source records attributed to Panos Papadimitratos.

At least 55 records · Page 3Linked to original sources

arXiv2023

Detecting GNSS misbehavior leveraging secure heterogeneous time sources

Civilian Global Navigation Satellite Systems (GNSS) vulnerabilities are a threat to a wide gamut of critical systems. GNSS receivers, as part of the encompassing platform, can leverage external information to detect GNSS attacks. Specifically, cross-checking the time produced by the GNSS receiver against multiple trusted time sources can provide robust and assured PNT. In this work, we explore the combination of secure remote, network-based time providers and local precision oscillators. This multi-layered defense mechanism detects GNSS attacks that induce even small time offsets, including attacks mounted in cold start. Our system does not require any modification to the current structure of the GNSS receiver, it is agnostic to the satellite constellation and the attacker type. This makes time-based data validation of GNSS information compatible with existing receivers and readily deployable.

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arXiv2023

Using Mobile Phones for Participatory Detection and Localization of a GNSS Jammer

It is well known that GNSS receivers are vulnerable to jamming and spoofing attacks, and numerous such incidents have been reported in the last decade all over the world. The notion of participatory sensing, or crowdsensing, is that a large ensemble of voluntary contributors provides measurements, rather than relying on a dedicated sensing infrastructure. The participatory sensing network under consideration in this work is based on GNSS receivers embedded in, for example, mobile phones. The provided measurements refer to the receiver-reported carrier-to-noise-density ratio ($C/N_0$) estimates or automatic gain control (AGC) values. In this work, we exploit $C/N_0$ measurements to locate a GNSS jammer, using multiple receivers in a crowdsourcing manner. We extend a previous jammer position estimator by only including data that is received during parts of the sensing period where jamming is detected by the sensor. In addition, we perform hardware testing for verification and evaluation of the proposed and compared state-of-the-art algorithms. Evaluations are performed using a Samsung S20+ mobile phone as participatory sensor and a Spirent GSS9000 GNSS simulator to generate GNSS and jamming signals. The proposed algorithm is shown to work well when using $C/N_0$ measurements and outperform the alternative algorithms in the evaluated scenarios, producing a median error of 50 meters when the pathloss exponent is 2. With higher pathloss exponents the error gets higher. The AGC output from the phone was too noisy and needs further processing to be useful for position estimation.

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arXiv2022

Digital Twin-based Intrusion Detection for Industrial Control Systems

Digital twins have recently gained significant interest in simulation, optimization, and predictive maintenance of Industrial Control Systems (ICS). Recent studies discuss the possibility of using digital twins for intrusion detection in industrial systems. Accordingly, this study contributes to a digital twin-based security framework for industrial control systems, extending its capabilities for simulation of attacks and defense mechanisms. Four types of process-aware attack scenarios are implemented on a standalone open-source digital twin of an industrial filling plant: command injection, network Denial of Service (DoS), calculated measurement modification, and naive measurement modification. A stacked ensemble classifier is proposed as the real-time intrusion detection, based on the offline evaluation of eight supervised machine learning algorithms. The designed stacked model outperforms previous methods in terms of F1-Score and accuracy, by combining the predictions of various algorithms, while it can detect and classify intrusions in near real-time (0.1 seconds). This study also discusses the practicality and benefits of the proposed digital twin-based security framework.

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arXiv2022

Participatory Sensing for Localization of a GNSS Jammer

GNSS receivers are vulnerable to jamming and spoofing attacks, and numerous such incidents have been reported worldwide in the last decade. It is important to detect attacks fast and localize attackers, which can be hard if not impossible without dedicated sensing infrastructure. The notion of participatory sensing, or crowdsensing, is that a large ensemble of voluntary contributors provides the measurements, rather than relying on dedicated sensing infrastructure. This work considers embedded GNSS receivers to provide measurements for participatory jamming detection and localization. Specifically, this work proposes a novel jamming localization algorithm, based on participatory sensing, that exploits AGC and C/N_0 estimates from commercial GNSS receivers. The proposed algorithm does not require knowledge of the jamming power nor of the channels, but automatically estimates all parameters. The algorithm is shown to outperform similar state-of-the-art localization algorithms in relevant scenarios.

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arXiv2021

HERMES: Scalable, Secure, and Privacy-Enhancing Vehicle Access System

We propose HERMES, a scalable, secure, and privacy-enhancing system for users to share and access vehicles. HERMES securely outsources operations of vehicle access token generation to a set of untrusted servers. It builds on an earlier proposal, namely SePCAR [1], and extends the system design for improved efficiency and scalability. To cater to system and user needs for secure and private computations, HERMES utilizes and combines several cryptographic primitives with secure multiparty computation efficiently. It conceals secret keys of vehicles and transaction details from the servers, including vehicle booking details, access token information, and user and vehicle identities. It also provides user accountability in case of disputes. Besides, we provide semantic security analysis and prove that HERMES meets its security and privacy requirements. Last but not least, we demonstrate that HERMES is efficient and, in contrast to SePCAR, scales to a large number of users and vehicles, making it practical for real-world deployments. We build our evaluations with two different multiparty computation protocols: HtMAC-MiMC and CBC-MAC-AES. Our results demonstrate that HERMES with HtMAC-MiMC requires only approx 1,83 ms for generating an access token for a single-vehicle owner and approx 11,9 ms for a large branch of rental companies with over a thousand vehicles. It handles 546 and 84 access token generations per second, respectively. This results in HERMES being 696 (with HtMAC-MiMC) and 42 (with CBC-MAC-AES) times faster compared to in SePCAR for a single-vehicle owner access token generation. Furthermore, we show that HERMES is practical on the vehicle side, too, as access token operations performed on a prototype vehicle on-board unit take only approx 62,087 ms.

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arXiv2020

Cooperative Location Privacy in Vehicular Networks: Why Simple Mix-zones are not Enough

Vehicular communications disclose rich information about the vehicles and their whereabouts. Pseudonymous authentication secures communication while enhancing user privacy. To enhance location privacy, cryptographic mix-zones were proposed to facilitate vehicles covertly transition to new ephemeral credentials. The resilience to (syntactic and semantic) pseudonym linking (attacks) highly depends on the geometry of the mix-zones, mobility patterns, vehicle density, and arrival rates. We introduce a tracking algorithm for linking pseudonyms before and after a cryptographically protected mix-zone. Our experimental results show that an eavesdropper, leveraging standardized vehicular communication messages and road layout, could successfully link 73% of pseudonyms during non-rush hours and 62% of pseudonyms during rush hours after vehicles change their pseudonyms in a mix-zone. To mitigate such inference attacks, we present a novel cooperative mix-zone scheme that enhances user privacy regardless of the vehicle mobility patterns, vehicle density, and arrival rate to the mix-zone. A subset of vehicles, termed relaying vehicles, are selected to be responsible for emulating non-existing vehicles. Such vehicles cooperatively disseminate decoy traffic without affecting safety-critical operations: with 50% of vehicles as relaying vehicles, the probability of linking pseudonyms (for the entire interval) drops from 68% to 18%. On average, this imposes 28 ms extra computation overhead, per second, on the Roadside Units (RSUs) and 4.67 ms extra computation overhead, per second, on the (relaying) vehicle side; it also introduces 1.46 KB/sec extra communication overhead by (relaying) vehicles and 45 KB/sec by RSUs for the dissemination of decoy traffic. Thus, user privacy is enhanced at the cost of low computation and communication overhead.

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arXiv2020

Towards Scalable Security in Interference Channels With Arbitrary Number of Users

In this paper, we present an achievable security scheme for an interference channel with arbitrary number of users. In this model, each receiver should be able to decode its intended message while it cannot decode any meaningful information regarding messages intended for other receivers. Our scheme achieves individual secure rates which scale linearly with log(SNR) and achieves sum secure rates which is within constant gap of sum secure capacity. To design the encoders at the transmitters side, we combine nested lattice coding, random i.i.d. codes, and cooperative jamming techniques. Asymmetric compute-and-forward framework is used to perform the decoding operation at the receivers. The novelty of our scheme is that it is the first asymptotically optimal achievable scheme for this security scenario which scales to arbitrary number of users and works for any finite-valued SNR. Also, our scheme achieves the upper bound sum secure degrees of freedom of $1$ without using external helpers.

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arXiv2020

Scalable & Resilient Vehicle-Centric Certificate Revocation List Distribution in Vehicular Communication Systems

In spite of progress in securing Vehicular Communication (VC) systems, there is no consensus on how to distribute Certificate Revocation Lists (CRLs). The main challenges lie exactly in (i) crafting an efficient and timely distribution of CRLs for numerous anonymous credentials, pseudonyms, (ii) maintaining strong privacy for vehicles prior to revocation events, even with honest-but-curious system entities, (iii) and catering to computation and communication constraints of on-board units with intermittent connectivity to the infrastructure. Relying on peers to distribute the CRLs is a double-edged sword: abusive peers could "pollute" the process, thus degrading the timely CRLs distribution. In this paper, we propose a vehicle-centric solution that addresses all these challenges and thus closes a gap in the literature. Our scheme radically reduces CRL distribution overhead: each vehicle receives CRLs corresponding only to its region of operation and its actual trip duration. Moreover, a "fingerprint" of CRL 'pieces' is attached to a subset of (verifiable) pseudonyms for fast CRL 'piece' validation (while mitigating resource depletion attacks abusing the CRL distribution). Our experimental evaluation shows that our scheme is efficient, scalable, dependable, and practical: with no more than 25 KB/s of traffic load, the latest CRL can be delivered to 95% of the vehicles in a region (15 x 15 KM) within 15s, i.e., more than 40 times faster than the state-of-the-art. Overall, our scheme is a comprehensive solution that complements standards and can catalyze the deployment of secure and privacy-protecting VC systems.

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arXiv2020

Security and Privacy in Vehicular Social Networks

We surveyed and presented the state-of-the-art VC systems, security and privacy architectures and technologies, emphasizing on security and privacy challenges and their solutions for P2P interactions in VSNs towards standardization and deployment. We note that beyond safety applications that have drawn a lot of attention in VC systems, there is significant and rising interest in vehicle-to-vehicle interaction for a range of transportation efficiency and infotainment applications, notably LBS as well as a gamut of services by mobile providers. While this enriches the VC systems and the user experience, security and privacy concerns are also intensified. This is especially so, considering (i) the privacy risk from the exposure of the users to the service providers, and (ii) the security risk from the interaction with malicious or selfish and thus misbehaving users or infrastructure. We showed existing solutions can in fact evolve and address the VSN-specific challenges, and improve or even accelerate the adoption of VSN applications.

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arXiv2020

Resilient Privacy Protection for Location-Based Services through Decentralization

Location-Based Services (LBSs) provide valuable services, with convenient features for mobile users. However, the location and other information disclosed through each query to the LBS erodes user privacy. This is a concern especially because LBS providers can be honest-but-curious, collecting queries and tracking users' whereabouts and infer sensitive user data. This motivated both centralized and decentralized location privacy protection schemes for LBSs: anonymizing and obfuscating LBS queries to not disclose exact information, while still getting useful responses. Decentralized schemes overcome disadvantages of centralized schemes, eliminating anonymizers, and enhancing users' control over sensitive information. However, an insecure decentralized system could create serious risks beyond private information leakage. More so, attacking an improperly designed decentralized LBS privacy protection scheme could be an effective and low-cost step to breach user privacy. We address exactly this problem, by proposing security enhancements for mobile data sharing systems. We protect user privacy while preserving accountability of user activities, leveraging pseudonymous authentication with mainstream cryptography. We show our scheme can be deployed with off-the-shelf devices based on an experimental evaluation of an implementation in a static automotive testbed.

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arXiv2020

Resilient Collaborative Privacy for Location-Based Services

Location-based Services (LBSs) provide valuable services, with convenient features for users. However, the information disclosed through each request harms user privacy. This is a concern particularly with honest-but-curious LBS servers, which could, by collecting requests, track users and infer additional sensitive user data. This is the motivation of both centralized and decentralized location privacy protection schemes for LBSs: anonymizing and obfuscating LBS queries to not disclose exact information, while still getting useful responses. Decentralized schemes overcome the disadvantages of centralized schemes, eliminating anonymizers and enhancing users' control over sensitive information. However, an insecure decentralized system could pose even more serious security threats than privacy leakage. We address exactly this problem, by proposing security enhancements for mobile data sharing systems. We protect user privacy while preserving accountability of user activities, leveraging pseudonymous authentication with mainstream cryptography. Our design leverages architectures proposed for large scale mobile systems, while it incurs minimal changes to LBS servers as it can be deployed in parallel to the LBS servers. This further motivates the adoption of our design, in order to cater to the needs of privacy-sensitive users. We provide an analysis of security and privacy concerns and countermeasures, as well as a performance evaluation of basic protocol operations showing the practicality of our design.

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arXiv2020

Proactive Certificate Validation for VANETs

Security and privacy in Vehicular Ad-hoc Networks (VANETs) mandates use of short-lived credentials (pseudonyms) and cryptographic key pairs. This implies significant computational overhead for vehicles, needing to validate often numerous such pseudonyms within a short period. To alleviate such a bottleneck that could even place vehicle safety at risk, we propose a proactive pseudonym validation approach based on Bloom Filters (BFs). We show that our scheme could liberate computational resources for other (safety- and time-critical) operations with reasonable communication overhead without compromising security and privacy.

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arXiv2020

DoS-resilient Cooperative Beacon Verification for Vehicular Communication Systems

Authenticated safety beacons in Vehicular Communication (VC) systems ensure awareness among neighboring vehicles. However, the verification of beacon signatures introduces significant processing overhead for resource-constrained vehicular On-Board Units (OBUs). Even worse in dense neighborhood or when a clogging Denial of Service (DoS) attack is mounted. The OBU would fail to verify for all received (authentic or fictitious) beacons. This could significantly delay the verifications of authentic beacons or even affect the awareness of neighboring vehicle status. In this paper, we propose an efficient cooperative beacon verification scheme leveraging efficient symmetric key based authentication on top of pseudonymous authentication (based on traditional public key cryptography), providing efficient discovery of authentic beacons among a pool of received authentic and fictitious beacons, and can significantly decrease waiting times of beacons in queue before their validations. We show with simulation results that our scheme can guarantee low waiting times for received beacons even in high neighbor density situations and under DoS attacks, under which a traditional scheme would not be workable.

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arXiv2020

Scaling VANET Security Through Cooperative Message Verification

VANET security introduces significant processing overhead for resource-constrained On-Board Units (OBUs). Here, we propose a novel scheme that allows secure Vehicular Communication (VC) systems to scale well beyond network densities for which existing optimization approaches could be workable, without compromising security (and privacy).

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arXiv2019

Scaling Pseudonymous Authentication for Large Mobile Systems

The central building block of secure and privacy-preserving Vehicular Communication (VC) systems is a Vehicular Public-Key Infrastructure (VPKI), which provides vehicles with multiple anonymized credentials, termed pseudonyms. These pseudonyms are used to ensure message authenticity and integrity while preserving vehicle (thus passenger) privacy. In the light of emerging large-scale multi-domain VC environments, the efficiency of the VPKI and, more broadly, its scalability are paramount. By the same token, preventing misuse of the credentials, in particular, Sybil-based misbehavior, and managing "honest-but-curious" insiders are other facets of a challenging problem. In this paper, we leverage a state-of-the-art VPKI system and enhance its functionality towards a highly-available, dynamically-scalable, and resilient design; this ensures that the system remains operational in the presence of benign failures or resource depletion attacks, and that it dynamically scales out, or possibly scales in, according to request arrival rates. Our full-blown implementation on the Google Cloud Platform shows that deploying large-scale and efficient VPKI can be cost-effective.

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arXiv2018

Efficient, Scalable, and Resilient Vehicle-Centric Certificate Revocation List Distribution in VANETs

In spite of progress in securing Vehicular Communication (VC) systems, there is no consensus on how to distribute Certificate Revocation Lists (CRLs). The main challenges lie exactly in (i) crafting an efficient and timely distribution of CRLs for numerous anonymous credentials, pseudonyms, (ii) maintaining strong privacy for vehicles prior to revocation events, even with honest-but-curious system entities, (iii) and catering to computation and communication constraints of on-board units with intermittent connectivity to the infrastructure. Relying on peers to distribute the CRLs is a double-edged sword: abusive peers could "pollute" the process, thus degrading the timely CRLs distribution. In this paper, we propose a vehicle-centric solution that addresses all these challenges and thus closes a gap in the literature. Our scheme radically reduces CRL distribution overhead: each vehicle receives CRLs corresponding only to its region of operation and its actual trip duration. Moreover, a "fingerprint" of CRL 'pieces' is attached to a subset of (verifiable) pseudonyms for fast CRL 'piece' validation (while mitigating resource depletion attacks abusing the CRL distribution). Our experimental evaluation shows that our scheme is efficient, scalable, dependable, and practical: with no more than 25 KB/s of traffic load, the latest CRL can be delivered to 95% of the vehicles in a region (50x50 KM) within 15s, i.e., more than 40 times faster than the state-of-the-art. Overall, our scheme is a comprehensive solution that complements standards and can catalyze the deployment of secure and privacy-protecting VC systems.

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arXiv2018

VPKIaaS: A Highly-Available and Dynamically-Scalable Vehicular Public-Key Infrastructure

The central building block of secure and privacy-preserving Vehicular Communication (VC) systems is a Vehicular Public-Key Infrastructure (VPKI), which provides vehicles with multiple anonymized credentials, termed pseudonyms. These pseudonyms are used to ensure message authenticity and integrity while preserving vehicle (and thus passenger) privacy. In the light of emerging large-scale multi-domain VC environments, the efficiency of the VPKI and, more broadly, its scalability are paramount. In this extended abstract, we leverage the state-of-the-art VPKI system and enhance its functionality towards a highly-available and dynamically-scalable design, this ensures that the system remains operational in the presence of benign failures or any resource depletion attack, and that it dynamically scales out, or possibly scales in, according to the requests' arrival rate. Our full-blown implementation on the Google Cloud Platform shows that deploying a VPKI for a large-scale scenario can be cost-effective, while efficiently issuing pseudonyms for the requesters.

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arXiv2017

RHyTHM: A Randomized Hybrid Scheme To Hide in the Mobile Crowd

Any on-demand pseudonym acquisition strategy is problematic should the connectivity to the credential management infrastructure be intermittent. If a vehicle runs out of pseudonyms with no connectivity to refill its pseudonym pool, one solution is the on-the-fly generation of pseudonyms, e.g., leveraging anonymous authentication. However, such a vehicle would stand out in the crowd: one can simply distinguish pseudonyms, thus signed messages, based on the pseudonym issuer signature, link them and track the vehicle. To address this challenge, we propose a randomized hybrid scheme, RHyTHM, to enable vehicles to remain operational when disconnected without compromising privacy: vehicles with valid pseudonyms help others to enhance their privacy by randomly joining them in using on-the-fly self-certified pseudonyms along with aligned lifetimes. This way, the privacy of disconnected users is enhanced with a reasonable computational overhead.

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