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Irtaza Shahid

dblp:323/1557 · DBLP profile ↗
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5ranked-venue papers
4as first author
5since 2021 · last 2025
0000-0002-3963-9966ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 3 · 2 first-author · 3 since 2021Security and privacy · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
3 papers
Digital forensics and information hiding · 51% Privacy and data protection · 34% Usable security · 15%
Computer networks
1 paper
Wireless sensing and localization · 100%
Computer graphics and multimedia
1 paper
Audio and music processing · 100%

Topics — the 3 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Digital forensics and information hiding › digital forensics
multimedia forensics
1.322023
Poster: Preventing Fake News through Live Speech Signature · MobiSys 2023
"Is this my president speaking?" Tamper-proofing Speech in Live Recordings · MobiSys 2023
Wireless sensing and localization › indoor localization
ultra-wideband localization
0.912025
Large Network UWB Localization: Algorithms and Implementation · NSDI 2025
Wireless sensing and localization
localization algorithms
0.312025
Large Network UWB Localization: Algorithms and Implementation · NSDI 2025

Methods — techniques the papers use, named apart from their topics

voice anonymization · 1.7adversarial audio examples · 1.7meta-information generation · 1.3QR code-based screen-camera communication · 1.3
YearPublicationVenuePosition
2025 Large Network UWB Localization: Algorithms and Implementation
Nakul Garg, Irtaza Shahid, Ramanujan K. Sheshadri, Karthikeyan Sundaresan, Nirupam Roy
NSDI2
2025 For Human Ears Only: Preventing Automated Monitoring on Voice Data
Irtaza Shahid, Nirupam Roy
USENIX Security Symposium1
2024 Towards Enabling DPOAE Estimation on Single-Speaker Earbuds
abstract
Distortion Product OtoAcoustic Emissions (DPOAEs) represents faint cochlear responses to dual-frequency stimuli, commonly employed in hearing screening. This paper introduces an innovative approach to trigger DPOAEs using single-speaker earbuds. Due to their compact size, the speakers used in the earbuds exhibit nonlinear behavior, leading to Inter-Modulation Distortions (IMDs) that interfere with DPOAE signals. Conventional medical devices employ dual speakers to mitigate this distortion, such a solution is impractical for space-constrained earbuds. To address this challenge, we propose a method that triggers DPOAEs while circumventing IMDs by designing a stimulus signal that alternates between the two frequencies necessary for triggering DPOAEs. The performance of our system was evaluated through a preliminary user study involving 8 participants, and it demonstrated a median correlation of 0.65 when compared to a medical-grade reference device.
Irtaza Shahid, Khaldoon Al-Naimi, Ting Dang, Yang Liu 0101, Fahim Kawsar, Alessandro Montanari
ICASSP1
2023 "Is this my president speaking?" Tamper-proofing Speech in Live Recordings
abstract
Malicious editing of audiovisual content has emerged as a popular tool for targeted defamation, spreading disinformation, and triggering political unrest. Public speeches and statements of political leaders, public figures, or celebrities are particularly at target due to their effectiveness in influencing the masses. Ubiquitous audiovisual recording of live speeches with smart devices and unrestricted content sharing and redistributing on social media make it difficult to address this threat using existing authentication techniques. Given public recordings of live events lack source control over the media, standard solutions falter. This paper presents TalkLock, a speech integrity verification system that can enable live speakers to protect their speeches from malicious alterations even when the speech is recorded by any member of the audience. The core idea is to generate meta-information from the speech signal in real-time and disseminate it through a secure QR code-based screen-camera communication. The QR code when recorded along with the speech embeds the meta-information in the content and it can be used later for independent verification in stand-alone applications or online platforms. A user study with live speech and real-world experiments with different types of voices, languages, environments, and distances show that TalkLock can verify fake content with 94.4% accuracy.
Irtaza Shahid, Nirupam Roy
MobiSys1
2023 Poster: Preventing Fake News through Live Speech Signature
abstract
Malicious editing to alter audiovisual content has become increasingly prevalent in recent years, as it allows for targeted defamation, the dissemination of disinformation, and the incitement of political unrest. Public speeches and statements made by political leaders, public figures, and celebrities are particularly vulnerable to such attacks, as they have the power to sway public opinion. The widespread use of smart devices to record live speeches, combined with unrestricted content sharing and redistribution on social media platforms, makes it difficult to prevent the spread of manipulated media. Existing solutions, which rely on source control over the media, are not effective for live events. This paper presents TalkLock, a speech integrity verification system that can enable live speakers to protect their speeches from malicious alterations even when the speech is recorded by any member of the audience. The core idea is to generate meta-information from the speech signal in real-time and disseminate it through a secure QR code-based screen-camera communication. The QR code when recorded along with the speech embeds the meta-information in the content and it can be used later for independent verification in stand-alone applications or online platforms. A user study with live speech and real-world experiments with different types of voices, languages, environments, and distances show that TalkLock can verify fake content with 94.4% accuracy.
Irtaza Shahid, Nirupam Roy
MobiSys1