A review of on-device machine learning for IoT: An energy perspective
Recently, there has been a substantial interest in on-device Machine Learning (ML) models
to provide intelligence for the Internet of Things (IoT) applications such as image …
to provide intelligence for the Internet of Things (IoT) applications such as image …
Energy consumption of on-device machine learning models for IoT intrusion detection
Abstract Recently, Smart Home Systems (SHSs) have gained enormous popularity with the
rapid development of the Internet of Things (IoT) technologies. Besides offering many …
rapid development of the Internet of Things (IoT) technologies. Besides offering many …
Beyond smart homes: An in-depth analysis of smart aging care system security
The upward trend in the percentage of the population older than 65 has made smart aging
more relevant than ever before. Growing old in a traditional assisted living facility can take a …
more relevant than ever before. Growing old in a traditional assisted living facility can take a …
Detecting unknown encrypted malicious traffic in real time via flow interaction graph analysis
In this paper, we propose HyperVision, a realtime unsupervised machine learning (ML)
based malicious traffic detection system. Particularly, HyperVision is able to detect unknown …
based malicious traffic detection system. Particularly, HyperVision is able to detect unknown …
[PDF][PDF] Evasion attacks and defenses on smart home physical event verification
In smart homes, when an actuator's state changes, it sends an event notification to the IoT
hub to report this change (eg, the door is unlocked). Prior works have shown that event …
hub to report this change (eg, the door is unlocked). Prior works have shown that event …
{LocIn}: Inferring Semantic Location from Spatial Maps in Mixed Reality
Mixed reality (MR) devices capture 3D spatial maps of users' surroundings to integrate
virtual content into their physical environment. Existing permission models implemented in …
virtual content into their physical environment. Existing permission models implemented in …
Amir: Active multimodal interaction recognition from video and network traffic in connected environments
Activity recognition using video data is widely adopted for elder care, monitoring for safety
and security, and home automation. Unfortunately, using video data as the basis for activity …
and security, and home automation. Unfortunately, using video data as the basis for activity …
When a RF beats a CNN and GRU, together—A comparison of deep learning and classical machine learning approaches for encrypted malware traffic classification
Internet traffic classification plays a crucial role in Quality of Experience (QoE), Quality of
Services (QoS), intrusion detection, and traffic-trend analyses. While there is no theoretical …
Services (QoS), intrusion detection, and traffic-trend analyses. While there is no theoretical …
Ignorance is bliss? the effect of explanations on perceptions of voice assistants
Voice assistants offer a convenient and hands-free way of accessing computing in the home,
but a key problem with speech as an interaction modality is how to scaffold accurate mental …
but a key problem with speech as an interaction modality is how to scaffold accurate mental …
Spying through your voice assistants: realistic voice command fingerprinting
Voice assistants are becoming increasingly pervasive due to the convenience and
automation they provide through the voice interface. However, such convenience often …
automation they provide through the voice interface. However, such convenience often …