A5067468039- Advanced Malware Detection Techniques
- User Authentication and Security Systems
- Privacy-Preserving Technologies in Data
- Energy Harvesting in Wireless Networks
- Network Security and Intrusion Detection
- Adversarial Robustness in Machine Learning
- Energy Efficient Wireless Sensor Networks
- Internet Traffic Analysis and Secure E-voting
- Wireless Body Area Networks
- Cryptography and Data Security
- Advanced Authentication Protocols Security
- Bluetooth and Wireless Communication Technologies
- IoT Networks and Protocols
- Security and Verification in Computing
- Wireless Power Transfer Systems
- Mobile Ad Hoc Networks
- Biometric Identification and Security
- COVID-19 Digital Contact Tracing
- Advanced MIMO Systems Optimization
- Privacy, Security, and Data Protection
- Innovative Energy Harvesting Technologies
- Wireless Networks and Protocols
- RFID technology advancements
- Anomaly Detection Techniques and Applications
- Cooperative Communication and Network Coding
Technical University of Darmstadt
2014-2024
KU Leuven
2020-2022
IMEC
2020-2022
University of Newcastle Australia
2015-2018
Ho Chi Minh City University of Technology
2010
IoT devices are increasingly deployed in daily life. Many of these are, however, vulnerable due to insecure design, implementation, and configuration. As a result, many networks already have that easy compromise. This has led new category malware specifically targeting devices. However, existing intrusion detection techniques not effective detecting compromised given the massive scale problem terms number different types manufacturers involved. In this paper, we present DÏoT, an autonomous...
IoT devices are being widely deployed. But the huge variance among them in level of security and requirements for network resources makes it unfeasible to manage networks using a common generic policy. One solution this challenge is define policies classes based on device type. In paper, we present AuDI, system quickly effectively identifying type an by analyzing their communications. AuDI models periodic communication traffic unsupervised learning method perform identification. contrast...
Federated Learning (FL) is an appealing method for applying machine learning to large scale systems due the privacy and efficiency advantages that its training mechanism provides.One important field FL deployment emerging IoT applications.In particular, has been recently used intrusion detection where clients, e.g., a home security gateway, monitors traffic data generated by devices in network, trains local model, send this model central entity, aggregator, who then computes global (using...
Federated learning (FL) is an emerging distributed machine paradigm which addresses critical data privacy issues in by enabling clients, using aggregation server (aggregator), to jointly train a global model without revealing their training data. Thereby, it improves not only but also efficient as uses the computation power and of potentially millions clients for parallel. However, FL vulnerable so-called inference attacks malicious aggregators can infer information about clients' from...
Federated Learning (FL) allows multiple clients to collaboratively train a Neural Network (NN) model on their private data without revealing the data. Recently, several targeted poisoning attacks against FL have been introduced. These inject backdoor into resulting that adversary-controlled inputs be misclassified. Existing countermeasures are inefficient and often merely aim exclude deviating models from aggregation. However, this approach also removes benign of with distributions, causing...
Solutions for pairing devices without prior security associations typically require users to actively take part in the process of devices. Scenarios involving new types like Internet-of-Things (IoT) appliances and wearable make it, however, desirable be able pair users' personal user involvement. In this paper, we present a approach secure zero-interaction suitable IoT
Energy harvesting (EH) is considered the key enabling technology for mass deployment of Internet-of-Things (IoT) devices. Efficient EH techniques eliminate needs frequent energy source replacement, thus offering a near perpetual network operating environment. Advances in have shifted design paradigm routing protocols energy-harvesting wireless sensor based IoT applications from "energy-aware" to "energy-harvesting-aware". This paper aims an energy-harvesting-aware protocol heterogeneous...
Google and Apple have jointly provided an API for exposure notification in order to implement decentralized contract tracing apps using Bluetooth Low Energy, the so-called "Google/Apple Proposal", which we abbreviate by "GAP". We demonstrate that real-world scenarios current GAP design is vulnerable (i) profiling possibly de-anonymizing infected persons, (ii) relay-based wormhole attacks basically can generate fake contacts with potential of affecting accuracy app-based contact system. For...
With the increasing demand of IoT (Internet Things) applications, for energy efficiency (EE) and quality-of-service (QoS) in networks is on rise. In networks, EE QoS requirements are contradictory where maintaining higher difficult when high required. This paper aims to propose an adaptive MAC protocol which maintains IEEE 802.15.4 standard-based network. To this end, we introduce a new algorithm, referred as RF-AASP, that dynamically adjust sleeping period order sensor nodes harvest RF from...
Energy harvesting (EH) is considered to be the key enabling technology for mass deployment of wireless sensor networks (WSNs) Internet Things (IoT) applications. Efficient EH techniques could remove needs frequent energy source replacement, thus offering a near perpetual network operating environment. Advances in have shifted design routing protocols EH-WSN from `energy-aware' `energy-harvesting-aware'. This paper aims energy-harvesting-aware heterogeneous WSN-based IoT applications presence...
The emergence of IoT poses new challenges towards solutions for authenticating numerous very heterogeneous devices to their respective trust domains. Using passwords or pre-defined keys have drawbacks that limit use in scenarios. Recent works propose contextual information about ambient physical properties devices' surroundings as a shared secret mutually authenticate are co-located, e.g., the same room. In this paper, we analyze these context-based authentication with regard security and...
In the recent years, new services and businesses leveraging location-based (LBS) are rapidly emerging. On other hand this has raised incentive of users to cheat about their locations service providers for personal benefits. Context-based proofs-of-presence (PoPs) have been proposed as a means enable verification users' location claims. However, we show in paper, they vulnerable context guessing attacks. To make PoPs resilient malicious provers propose two complementary approaches making...
This paper addresses two of the most critical challenges in today's wireless sensor network (WSN)-based Internet Things (IoT) applications: self-sustainable operability and matching between harvested energy data transmission demands from nodes. To this end, we propose a radio frequency (RF) harvesting algorithm that optimizes period order for nodes to harvest downlink physical channels LTE eNodeB (i.e., PBCH PDCCH). The proposed adapts accordance stochastic characteristics traffic load IoT...
Low-power wide-area networks enable large-scale deployments of low-power wireless devices. LoRaWAN is a long-range technology that has emerged as and low data rate solution to support Internet Things applications. Although provides cost-efficient networking solution, recent literature shows it performs poorly in terms reliability security dense due the uncoordinated (ALOHA-based) nature MAC (medium access control) protocol. Furthermore, not robust against selective jamming attacks. This...
With the increasing deployment of wireless sensor networks (WSNs), demand for energy efficiency (EE) and Quality Service (QoS) guarantee such is on rise. In a distributed WSN, EE could be directly related to operational expenditure (OPEX) due frequent replacement batteries. An helps prolong network lifetime. Energy in WSN can improved by optimising PHY MAC layer algorithms. this paper, we introduce an adaptive algorithm, known as ABSD that changes parameters IEEE 802.15.4 nodes response...
This paper develops power allocation schemes to manage the signal interference in a multiuser multicell network, where full-duplex transceivers are implemented at all base stations (BSs) and user equipment units (UEs). Beside acute intracell intercell interferences, significant residual self-interference receivers is limiting factor for any network performance enhancement. To help control such severe we propose associate each bidirectional link with net utility function, which consists of...
The emergence of IoT poses new challenges towards solutions for authenticating numerous very heterogeneous devices to their respective trust domains. Using passwords or pre-defined keys have drawbacks that limit use in scenarios. Recent works propose contextual information about ambient physical properties devices' surroundings as a shared secret mutually authenticate are co-located, e.g., the same room. In this paper, we analyze these context-based authentication with regard security and...
IoT devices are increasingly deployed in daily life. Many of these are, however, vulnerable due to insecure design, implementation, and configuration. As a result, many networks already have that easy compromise. This has led new category malware specifically targeting devices. However, existing intrusion detection techniques not effective detecting compromised given the massive scale problem terms number different types manufacturers involved. In this paper, we present D\"IoT, an autonomous...
Copresence verification based on context can improve usability and strengthen security of many authentication access control systems. By sensing comparing their surroundings, two or more devices tell whether they are copresent use this information to make decisions. To the best our knowledge, all context-based copresence mechanisms date susceptible context-manipulation attacks. In such attacks, a distributed adversary replicates same at (different) locations victim devices, induces them...