Phishing is a social engineering cyberattack where criminals deceive users to obtain their credentials through login form that submits the data malicious server. In this paper, we compare machine learning and deep techniques present method capable of detecting phishing websites URL analysis. most current state-of-the-art solutions dealing with detection, legitimate class made up homepages witho...

We present a side-channel-attack (SCA) resistant asynchronous-logic (async-logic) Advanced Encryption Standard (AES) accelerator with dual-hiding SCA countermeasures, i.e. the amplitude moderation (vertical dimension) and time (horizontal dimension). There are five contributions in this paper. First, we propose an async-logic design flow relative timing to simplify AES realization Field-Program...

Affordance detection refers to identifying the potential action possibilities of objects in an image, which is a crucial ability for robot perception and manipulation. To empower robots with this unseen scenarios, we first study challenging one-shot affordance problem paper, i.e., given support image that depicts purpose, all scene common should be detected. end, devise One-Shot Detection Netwo...

IoT is a rapidly emerging paradigm that now encompasses almost every aspect of our modern life. As such, ensuring the security devices crucial. can differ from traditional computing, thereby design and implementation proper measures be challenging in devices. We observed developers discuss their security-related challenges developer forums like Stack Overflow(SO). However, we find discussions a...

The widely cultivated pepper, Capsicum spp., important as a vegetable and spice crop world-wide, is one of the most diverse crops. To enhance breeding programs, a detailed characterization of Capsicum diversity including morphological, geographical and molecular data is required. Currently, molecular data characterizing Capsicum genetic diversity is limited. The development and application of h...

Despite the numerous developments in object tracking, further development of current tracking algorithms is limited by small and mostly saturated datasets. As a matter of fact, data-hungry trackers based on deep-learning currently rely on object detection datasets due to the scarcity of dedicated large-scale tracking datasets. In this work, we present TrackingNet, the first large-scale dataset ...