Evaluating the Effectiveness and Robustness of Visual Similarity-based Phishing Detection Models

Phishing attacks pose a significant threat to Internet users, with cybercriminals elaborately replicating the visual appearance of legitimate websites to deceive victims. Visual similarity-based detection systems have emerged as an effective countermeasure, but their effectiveness and robustness in real-world scenarios have been unexplored. In this paper, we comprehensively scrutinize and evaluate state-of-the-art visual similarity-based anti-phishing models using a large-scale dataset of 450K real-world phishing websites. Our analysis reveals that while certain models maintain high accuracy, others exhibit notably lower performance than results on curated datasets, highlighting the importance of real-world evaluation. In addition, we observe the real-world tactic of manipulating visual components that phishing attackers employ to circumvent the detection systems. To assess the resilience of existing models against adversarial attacks and robustness, we apply visible and perturbation-based manipulations to website logos, which adversaries typically target. We then evaluate the models' robustness in handling these adversarial samples. Our findings reveal vulnerabilities in several models, emphasizing the need for more robust visual similarity techniques capable of withstanding sophisticated evasion attempts. We provide actionable insights for enhancing the security of phishing defense systems, encouraging proactive actions. To the best of our knowledge, this work represents the first large-scale, systematic evaluation of visual similarity-based models for phishing detection in real-world settings, necessitating the development of more effective and robust defenses.Comment: 12 page

UiO-66-NH2/GO Composite: Synthesis, Characterization and CO2 Adsorption Performance

In this work, a new composite materials of graphene oxide (GO)-incorporated metal-organic framework (MOF)(UiO-66-NH2/GO) were in-situ synthesized, and were found to exhibit enhanced high performances for CO2 capture. X-ray diffraction (XRD), scanning electron microscope (SEM), N2 physical adsorption, and thermogravimetric analysis (TGA) were applied to investigate the crystalline structure, pore structure, thermal stability, and the exterior morphology of the composite. We aimed to investigate the influence of the introduction of GO on the stability of the crystal skeleton and pore structure. Water, acid, and alkali resistances were tested for physical and chemical properties of the new composites. CO2 adsorption isotherms of UiO-66, UiO-66-NH2, UiO-66/GO, and UiO-66-NH2/GO were measured at 273 K, 298 K, and 318 K. The composite UiO-66-NH2/GO exhibited better optimized CO2 uptake of 6.41 mmol/g at 273 K, which was 5.1% higher than that of UiO-66/GO (6.10 mmol/g). CO2 adsorption heat and CO2/N2 selectivity were then calculated to further evaluate the CO2 adsorption performance. The results indicated that UiO-66-NH2/GO composites have a potential application in CO2 capture technologies to alleviate the increase in temperature of the earth’s atmosphere