A Hybrid Architecture for Out of Domain Intent Detection and Intent Discovery

Intent Detection is one of the tasks of the Natural Language Understanding (NLU) unit in task-oriented dialogue systems. Out of Scope (OOS) and Out of Domain (OOD) inputs may run these systems into a problem. On the other side, a labeled dataset is needed to train a model for Intent Detection in task-oriented dialogue systems. The creation of a labeled dataset is time-consuming and needs human resources. The purpose of this article is to address mentioned problems. The task of identifying OOD/OOS inputs is named OOD/OOS Intent Detection. Also, discovering new intents and pseudo-labeling of OOD inputs is well known by Intent Discovery. In OOD intent detection part, we make use of a Variational Autoencoder to distinguish between known and unknown intents independent of input data distribution. After that, an unsupervised clustering method is used to discover different unknown intents underlying OOD/OOS inputs. We also apply a non-linear dimensionality reduction on OOD/OOS representations to make distances between representations more meaning full for clustering. Our results show that the proposed model for both OOD/OOS Intent Detection and Intent Discovery achieves great results and passes baselines in English and Persian languages

ReWiFlow: Restricted Wildcard OpenFlow Rules

ABSTRACT The ability to manage individual flows is a major benefit of Software-Defined Networking. The overheads of this fine-grained control, e.g. initial flow setup delay, can overcome the benefits, for example when we have many time-sensitive short flows. Coarse-grained control of groups of flows, on the other hand, can be very complex: each packet may match multiple rules, which requires conflict resolution. In this paper, we present ReWiFlow, a restricted class of OpenFlow wildcard rules (the fundamental way to control groups of flows in OpenFlow), which allows managing groups of flows with flexibility and without loss of performance. We demonstrate how ReWiFlow can be used to implement applications such as dynamic proactive routing. We also present a generalization of ReWiFlow, called MultiReWiFlow, and show how it can be used to efficiently represent access control rules collected from Stanford's backbone network

CAPTCHaStar! A novel CAPTCHA based on interactive shape discovery

Over the last years, most websites on which users can register (e.g., email providers and social networks) adopted CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart) as a countermeasure against automated attacks. The battle of wits between designers and attackers of CAPTCHAs led to current ones being annoying and hard to solve for users, while still being vulnerable to automated attacks. In this paper, we propose CAPTCHaStar, a new image-based CAPTCHA that relies on user interaction. This novel CAPTCHA leverages the innate human ability to recognize shapes in a confused environment. We assess the effectiveness of our proposal for the two key aspects for CAPTCHAs, i.e., usability, and resiliency to automated attacks. In particular, we evaluated the usability, carrying out a thorough user study, and we tested the resiliency of our proposal against several types of automated attacks: traditional ones; designed ad-hoc for our proposal; and based on machine learning. Compared to the state of the art, our proposal is more user friendly (e.g., only some 35% of the users prefer current solutions, such as text-based CAPTCHAs) and more resilient to automated attacks.Comment: 15 page

A CAPTCHA model based on visual psychophysics: Using the brain to distinguish between human users and automated computer bots

Demand for the use of online services such as free emails, social networks, and online polling is increasing at an exponential rate. Due to this, online service providers and retailers feel pressurised to satisfy the multitude of end-user expectations. Meanwhile, automated computer robots (known as “bots”) are targeting online retailers and service providers by acting as human users and providing false information in order to abuse their service provisioning. CAPTCHA is a set of challenge/response protocol, which was introduced to protect online retailers and service providers from misuse and automated computer attacks. Text-based CAPTCHAs are the most popular form, and are used by most online service providers to differentiate between the human users and bots. However, the vast majority of text-based CAPTCHAs have been broken using the Optical Character Recognition (OCR) techniques and thus, reinforces the need for developing a secure and robust CAPTCHA model. Security and usability are the two fundamental issues that pose a trade-off in the design of a CAPTCHA; a hard CAPTCHA model could also be difficult for human users to resolve, which affects its usability, and vice versa. The model developed in this study uses the unsurpassed abilities of the Human Visual System (HVS) to superimpose and integrate complex information presented in individual frames, using the mechanism of trans-saccadic memory. In this context, the model integrates in its design the concept of persistence of vision, which enables humans to see the world in a continuous fashion. Preliminary results from the proposed model based on this technique are encouraging. To ensure the usability of the proposed CAPTCHA model, we set the threshold for the ORO parameter at 40%. This ensured that our CAPTCHA strings would be recognised by human observers at a rate of over 99% (or as close to 100% as is realistic). In turn, when examining the robustness of our VICAP model to computer programme attacks, we can observe that for the traditional case of OCR recognition, based on a single-frame scenario, the Computer Recognition Success Rate (CRSR) was about 0%, while in the case of a multi-frame scenario, the CRSR could increase to up to 50%

TAPCHA: An Invisible CAPTCHA Scheme

TAPCHA is a universal CAPTCHA scheme designed for touch-enabled smart devices such as smartphones, tablets and smartwatches. The main difference between TAPCHA and other CAPTCHA schemes is that TAPCHA retains its security by making the CAPTCHA test ‘invisible’ for the bot. It then utilises context effects to maintain the readability of the instruction for human users which eventually guarantees the usability of the scheme. Two reference designs, namely TAPCHA SHAPE & SHADE and TAPCHA MULTI are developed to demonstrate the use of this scheme

Persian/Arabic Baffletext CAPTCHA

Nowadays, many daily human activities such as education, trade, talks, etc are done by using the Internet. In such things as registration on Internet web sites, hackers write programs to make automatic false registration that waste the resources of the web sites while it may also stop it from functioning. Therefore, human users should be distinguished from computer programs. To this end, this paper presents a method for distinction of Persian and Arabic-language users from computer programs based on Persian and Arabic texts. Our proposed algorithm is based on adding a background to the image of a meaningless Persian/Arabic randomly generated word. This method relies on the difficulty of automatic separation of background from Persian/Arabic writing, due to the presence of many diacritical dots and signs

M-Quiz By SMS with Cheat Prevention Feature

Virtual learning is a new idea that has gotten a new form with the emergence of new technologies such as the wireless networks. The mobile phone (cell phone) is a device that is used by most people nowadays. Therefore, one can use the mobile phone for virtual learning on a wide scale. One of the popular and at the same time simple and inexpensive services on the mobile phone is the SMS (Short Message Service). In this paper, we propose a method for taking multiple-choice quizzes by using the SMS on mobile phones. In the provision of these tests, after coding the questions with a key, some SMS messages were sent to the student along with the answers of the questions, which were steganography in an image. The student, after receiving and answering the questions, receives his grade at the client-side and then the grade and student answers are hidden in an SMS picture message and sent back to the instructor. Also, the location of student and the time that he took the exam are sent to the instructor by another SMS to prevent the possibility of any cheating. Moreover, the correct answers of the questions are destroyed within the image after they are extracted from image so as to eliminate the possibility of any cheating. The instructor also, after receiving the image and extracting the grade, records the student’s grade. Moreover, the instructor can find any cheating by comparing students locations, times they took the exam and their answers. Because of using the steganography method in sending the answers and grades, and also sending the student’s location and time of quiz, this method is highly secure and the possibility of cheating in the exam is reduced. This method was implemented with the J2ME language on a Nokia 3250 mobile phone