WISEC

In this paper, a machine learning (ML) approach is proposed to detect and classify jamming attacks on unmanned aerial vehicles (UAVs). Four attack types are implemented using software-defined radio (SDR); namely, barrage, single-tone, successive-pulse, ...

With the great advances in location-based services (LBS), Wi-Fi localization has attracted great interest due to its ubiquitous availability in indoor environments. Deep neural network (DNN) is a powerful method to achieve high localization performance ...

Smart grids are vulnerable to cyber-attacks. This paper proposes a game-theoretic approach to evaluate the variations caused by an attacker on the power measurements. Adversaries can gain financial benefits through the manipulation of the meters of ...

Spectrum access in the next generation wireless networks will be congested, competitive, and vulnerable to malicious intents of strong adversaries. This compels us to rethink wireless security for a cross-layer solution addressing it as a joint problem ...

Machine learning and cloud computing have been integrated in diverse applications to provide intelligent services. With powerful computational ability, the cloud server can execute machine learning algorithm efficiently. However, since accurate machine ...

Backdoor attacks represent a serious threat to neural network models. A backdoored model will misclassify the trigger-embedded inputs into an attacker-chosen target label while performing normally on other benign inputs. There are already numerous works ...

The BackDoor system provides a method for inaudibly transmitting messages that are recorded by unmodified receiver microphones as if they were transmitted audibly. Adversarial Audio attacks allow for an audio sample to sound like one message but be ...

Towards sixth-generation networks (6G), satellite communication systems, especially based on Low Earth Orbit (LEO) networks, become promising due to their unique and comprehensive capabilities. These advantages are accompanied by a variety of challenges ...

With the availability of different wireless networks in wireless virtualization, dynamic network selection in a given heterogeneous environment is challenging task when there is cyber security and data privacy requirements for wireless users. Selection ...

Cooperative spectrum sensing aims to improve the reliability of spectrum sensing by individual sensors for better utilization of the scarce spectrum bands, which gives the feasibility for secondary spectrum users to transmit their signals when primary ...

The key generation rate (KGR) performance of wireless physical layer (PHY) key generation can be limited by the quasi-static slow fading environment. In this work, we aim to exploit the radio environment reconfiguration ability enabled by reconfigurable ...

Deep learning based RF Fingerprinting has shown great promise for IoT device security. This work explores various multi-agent reinforcement learning approaches to enable RF Fingerprint enhancement for an ensemble of transmitters. A RiftNetTM ...

Mobile Crowdsensing is prone to adversarial attacks particularly the data injection attacks to mislead the servers in the decision-making process. This paper aims to tackle the problem of threat anticipation from the standpoint of data poisoning attacks,...

We propose a framework, RiftNeXtTM, to perform radio frequency (RF) scene context change detection and classification with Expert driven neural explainability. Our approach uses a deep learning based classifier to perform spectrum monitoring of Wi-Fi ...

Behavioral biometric-based smartphone user authentication schemes based on touch/swipe have shown to provide the desired usability. However, their accuracy is not yet considered up to the mark. This is primarily due to the lack of a sufficient number of ...

We study the role of information complexity in privacy leakage about an attribute of an adversary's interest, which is not known a priori to the system designer. Considering the supervised representation learning setup and using neural networks to ...