Bridging the Spoof Gap: A Unified Parallel Aggregation Network for Voice Presentation Attacks

Automatic Speaker Verification (ASV) systems are increasingly used in voice bio-metrics for user authentication but are susceptible to logical and physical spoofing attacks, posing security risks. Existing research mainly tackles logical or physical attacks separately, leading to a gap in unified spoofing detection. Moreover, when existing systems attempt to handle both types of attacks, they often exhibit significant disparities in the Equal Error Rate (EER). To bridge this gap, we present a Parallel Stacked Aggregation Network that processes raw audio. Our approach employs a split-transform-aggregation technique, dividing utterances into convolved representations, applying transformations, and aggregating the results to identify logical (LA) and physical (PA) spoofing attacks. Evaluation of the ASVspoof-2019 and VSDC datasets shows the effectiveness of the proposed system. It outperforms state-of-the-art solutions, displaying reduced EER disparities and superior performance in detecting spoofing attacks. This highlights the proposed method's generalizability and superiority. In a world increasingly reliant on voice-based security, our unified spoofing detection system provides a robust defense against a spectrum of voice spoofing attacks, safeguarding ASVs and user data effectively

Securing Voice Biometrics: One-Shot Learning Approach for Audio Deepfake Detection

The Automatic Speaker Verification (ASV) system is vulnerable to fraudulent activities using audio deepfakes, also known as logical-access voice spoofing attacks. These deepfakes pose a concerning threat to voice biometrics due to recent advancements in generative AI and speech synthesis technologies. While several deep learning models for speech synthesis detection have been developed, most of them show poor generalizability, especially when the attacks have different statistical distributions from the ones seen. Therefore, this paper presents Quick-SpoofNet, an approach for detecting both seen and unseen synthetic attacks in the ASV system using one-shot learning and metric learning techniques. By using the effective spectral feature set, the proposed method extracts compact and representative temporal embeddings from the voice samples and utilizes metric learning and triplet loss to assess the similarity index and distinguish different embeddings. The system effectively clusters similar speech embeddings, classifying bona fide speeches as the target class and identifying other clusters as spoofing attacks. The proposed system is evaluated using the ASVspoof 2019 logical access (LA) dataset and tested against unseen deepfake attacks from the ASVspoof 2021 dataset. Additionally, its generalization ability towards unseen bona fide speech is assessed using speech data from the VSDC dataset

Organizational Determinants as a Barrier of Balanced Scorecard Adoption for Performance Measurement in Pakistan

The prime objective of this study was to identify the status of Balanced Scorecard (BSC) adoption in Pakistan and to what extent different organizational factors serve as barrier in the strategic adoption of BSC as administrative tool to measure performance of organizations. Different organizational theories, strategic adoption, innovation diffusion theory and general system theory were reviewed and to develop theoretical framework these theories were considered as starting point. The literature related to these theories aided in the development of four hypotheses. All organizations of Pakistan irrespective of type, nature and location were selected to test the hypotheses. These organizations were selected by systematic random sampling and a sample of 287 was calculated from a sampling frame taken from Karachi Stock Exchange. After pretesting the adapted instrument was furthermore validated through Cronbach alpha and factor analysis. The impact of different factors as barrier was tested through correlation and regression analysis. It was found through analysis that all four organizational factors were very strong barriers in the adoption of BSC. The salient nature of organizational factors supporting the resource based view in organization for strategic decision for adoption. Keywords: Organizational Performance, Balance Scorecard, organizational barriers

ISO, As an Agent of Change for Manufacturing Sector: A Case Study from Pakistani Perspective

Purpose - The purpose and aim of this study is to investigate how and why any organization needs to become registered with ISO. The case is written especially for the students of business management to enhance their capabilities that help them when they go in practical life. Methodology and Approach - This study contains qualitative approach. Data required to write this paper was collected from direct meetings and by conducting interviews from relevant persons. Findings - This whole study concluded that if any organization wants to make their products up to mark and never having to say sorry to customer than they must follow the quality standards of ISO and needs to become register with it. Paper Limitation - This case study is self-reported. Name of organization and names of persons are supposed and these are not basis on truth. It does not consist actual events occurred in the organization. And this study is also limited by the fact that findings relate to only one country. Originality/value - This case study elaborates the complete understanding of how any organization can get ISO quality standards certification. Keywords - Bureau verities quality information, International organizations of standards, Quality, Quality manua

Voice Spoofing Countermeasures: Taxonomy, State-of-the-art, experimental analysis of generalizability, open challenges, and the way forward

Malicious actors may seek to use different voice-spoofing attacks to fool ASV systems and even use them for spreading misinformation. Various countermeasures have been proposed to detect these spoofing attacks. Due to the extensive work done on spoofing detection in automated speaker verification (ASV) systems in the last 6-7 years, there is a need to classify the research and perform qualitative and quantitative comparisons on state-of-the-art countermeasures. Additionally, no existing survey paper has reviewed integrated solutions to voice spoofing evaluation and speaker verification, adversarial/antiforensics attacks on spoofing countermeasures, and ASV itself, or unified solutions to detect multiple attacks using a single model. Further, no work has been done to provide an apples-to-apples comparison of published countermeasures in order to assess their generalizability by evaluating them across corpora. In this work, we conduct a review of the literature on spoofing detection using hand-crafted features, deep learning, end-to-end, and universal spoofing countermeasure solutions to detect speech synthesis (SS), voice conversion (VC), and replay attacks. Additionally, we also review integrated solutions to voice spoofing evaluation and speaker verification, adversarial and anti-forensics attacks on voice countermeasures, and ASV. The limitations and challenges of the existing spoofing countermeasures are also presented. We report the performance of these countermeasures on several datasets and evaluate them across corpora. For the experiments, we employ the ASVspoof2019 and VSDC datasets along with GMM, SVM, CNN, and CNN-GRU classifiers. (For reproduceability of the results, the code of the test bed can be found in our GitHub Repository

Role of Global Value Chains and Exchange Rate: An Empirical Examination in case of Pakistan

Pakistan’s economy has a history of facing continuous external sector shocks that often resulted in large exchange rate depreciations. Whether these depreciations have supported growth in exports from Pakistan or do more harm than providing any benefit to the economy is always a matter of domestic debate with inconclusive results. One major apprehension sighted in this regard is the role of intermediate imported goods that become expensive after depreciations and thus offset any competitive gains expected to be achieved from the exchange rate adjustment. To empirically investigate this argument, we evaluate that whether and how the Global Value Chains (GVCs) participation, i.e. the export and import of intermediate goods, affects the REER elasticity for exports in Pakistan using input-output model techniques. We find that, like elsewhere, REER elasticity of exports has declined in Pakistan overtime. However, only around 16 percent of this decline in REER elasticity is explained by the role of GVCs participation. One major reason for this lower impact could be coming from the fact that, unlike other emerging economies and in contrast to general perception, role of backward participation (i.e. use of imported inputs to produce exports) is one of the lowest in Pakistan. While the results still signify the role of PKR exchange rate in external adjustment, the low backward participation is not helping the exports to become competitive overtime

The dark triad and counterproductive work behaviours: A multiple mediation analysis

Prior studies on the dark side of the organisation tend to overlook some important mediator(s) in the relationship between the dark triad personalities (D.T.P.s) and counterproductive work behaviour (C.W.B.). Hence, this study examines the multiple-mediation model by incorporating perceived organisational politics and perceived accountability in the relationship between D.T.P.s and C.W.B. The sample of 290 employees is selected through a random sampling technique from the hospitality industry. Partial least squares structural equation modelling (P.L.S.-S.E.M.) and bootstrapping are employed to examine the multiple-mediation model. The results show that perceived organisational politics and perceived accountability mediate the association of the D.T.P.s and C.W.B. Our findings provide policymakers with a vision into the existence of the D.T.P.s and their potential consequences for C.W.B. This study encourages decision-makers and practitioners to develop an ethical climate, job standards, and systems of accountability to achieve productive goals