Human Cognition in Automated Truing Test Design

2014 ◽  
Vol 6 (4) ◽  
pp. 1-19 ◽  
Author(s):  
Mir Tafseer Nayeem ◽  
Mamunur Rashid Akand ◽  
Nazmus Sakib ◽  
Wasi Ul Kabir
Keyword(s):  
Large Scale ◽  
User Study ◽  
Contextual Information ◽  
Denial Of Service ◽  
Human Cognition ◽  
Dos Attacks ◽  
Result Section ◽  
Authentication Mechanism ◽  
Interactive Proofs ◽  
Human Interactive Proofs

Nowadays, many services in the internet including Email, search engine, social networking are provided with free of charge due to enormous growth of web users. With the expansion of Web services, denial of service (DoS) attacks by malicious automated programs (e.g., web bots) is becoming a serious problem of web service accounts. A HIP, or Human Interactive Proofs, is a human authentication mechanism that generates and grades tests to determine whether the user is a human or a malicious computer program. Unfortunately, the existing HIPs tried to maximize the difficulty for automated programs to pass tests by increasing distortion or noise. Consequently, it has also become difficult for potential users too. So there is a tradeoff between the usability and robustness in designing HIP tests. In their propose technique the authors tried to balance the readability and security by adding contextual information in the form of natural conversation without reducing the distortion and noise. In the result section, a microscopic large-scale user study was conducted involving 110 users to investigate the actual user views compare to existing state of the art CAPTCHA systems like Google's reCAPTCHA and Microsoft's CAPTCHA in terms of usability and security and found the authors' system capable of deploying largely over internet.

Script Familiarity and Its Effect on CAPTCHA Usability

2012 ◽  
Vol 4 (2) ◽  
pp. 74-87 ◽  
Author(s):  
Ashraf Khalil ◽  
Salam Abdallah ◽  
Soha Ahmed ◽  
Hassan Hajjdiab
Keyword(s):  
Language Proficiency ◽  
English Language ◽  
User Study ◽  
Research Area ◽  
English Language Proficiency ◽  
Web Based ◽  
Interactive Proofs ◽  
Proficiency Level ◽  
New Research ◽  
Human Interactive Proofs

Many web-based services such as email, search engines, and polling sites are being abused by spammers via computer programs known as bots. This problem has bred a new research area called Human Interactive Proofs (HIP) and a testing device called CAPTCHA, which aims to protect services from malevolent attacks by distinguishing bots from human users. In the past decade, researchers have focused on developing robust and safe HIP systems but have barely evaluated their usability. To begin to fill this gap, the authors report the results of a user study conducted to determine the extent that English language proficiency affects CAPTCHA usability for users whose native language is not English. The results showed a significant effect of participants’ English language proficiency level on the time the participant takes to solve CAPTCHA, which appear to be related to multiple usability issues including satisfaction and efficiency. Yet, they found that English language proficiency level does not affect the number of errors made while entering CAPTCHA or reCAPTCHA. The authors’ results have numerous implications that may inform future CAPTCHA design.

scholarly journals At Home and Abroad: The Use of Denial-of-service Attacks during Elections in Nondemocratic Regimes

2019 ◽  
Vol 64 (2-3) ◽  
pp. 373-401
Author(s):  
Philipp M. Lutscher ◽  
Nils B. Weidmann ◽  
Margaret E. Roberts ◽  
Mattijs Jonker ◽  
Alistair King ◽  
...  
Keyword(s):  
Large Scale ◽  
Denial Of Service ◽  
The Political ◽  
Traffic Data ◽  
Focal Points ◽  
Data Traffic ◽  
Dos Attacks ◽  
Threatening Information ◽  
News Websites ◽  
Nondemocratic Regimes

In this article, we study the political use of denial-of-service (DoS) attacks, a particular form of cyberattack that disables web services by flooding them with high levels of data traffic. We argue that websites in nondemocratic regimes should be especially prone to this type of attack, particularly around political focal points such as elections. This is due to two mechanisms: governments employ DoS attacks to censor regime-threatening information, while at the same time, activists use DoS attacks as a tool to publicly undermine the government’s authority. We analyze these mechanisms by relying on measurements of DoS attacks based on large-scale Internet traffic data. Our results show that in authoritarian countries, elections indeed increase the number of DoS attacks. However, these attacks do not seem to be directed primarily against the country itself but rather against other states that serve as hosts for news websites from this country.

scholarly journals A Secure Protocol against Selfish and Pollution Attacker Misbehavior in Clustered WSNs

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1244
Author(s):  
Hana Rhim ◽  
Damien Sauveron ◽  
Ryma Abassi ◽  
Karim Tamine ◽  
Sihem Guemara
Keyword(s):  
Denial Of Service ◽  
Base Station ◽  
Hierarchical Organization ◽  
Secure Routing ◽  
Sensor Nodes ◽  
Dos Attacks ◽  
Linear Network ◽  
Secure Protocol ◽  
Misbehaving Nodes ◽  
Pollution Attacks

Wireless sensor networks (WSNs) have been widely used for applications in numerous fields. One of the main challenges is the limited energy resources when designing secure routing in such networks. Hierarchical organization of nodes in the network can make efficient use of their resources. In this case, a subset of nodes, the cluster heads (CHs), is entrusted with transmitting messages from cluster nodes to the base station (BS). However, the existence of selfish or pollution attacker nodes in the network causes data transmission failure and damages the network availability and integrity. Mainly, when critical nodes like CH nodes misbehave by refusing to forward data to the BS, by modifying data in transit or by injecting polluted data, the whole network becomes defective. This paper presents a secure protocol against selfish and pollution attacker misbehavior in clustered WSNs, known as (SSP). It aims to thwart both selfish and pollution attacker misbehaviors, the former being a form of a Denial of Service (DoS) attack. In addition, it maintains a level of confidentiality against eavesdroppers. Based on a random linear network coding (NC) technique, the protocol uses pre-loaded matrices within sensor nodes to conceive a larger number of new packets from a set of initial data packets, thus creating data redundancy. Then, it transmits them through separate paths to the BS. Furthermore, it detects misbehaving nodes among CHs and executes a punishment mechanism using a control counter. The security analysis and simulation results demonstrate that the proposed solution is not only capable of preventing and detecting DoS attacks as well as pollution attacks, but can also maintain scalable and stable routing for large networks. The protocol means 100% of messages are successfully recovered and received at the BS when the percentage of lost packets is around 20%. Moreover, when the number of misbehaving nodes executing pollution attacks reaches a certain threshold, SSP scores a reception rate of correctly reconstructed messages equal to 100%. If the SSP protocol is not applied, the rate of reception of correctly reconstructed messages is reduced by 90% at the same case.

scholarly journals Secure and DoS-Resilient Fragment Authentication in CCN-Based Vehicular Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Sangwon Hyun ◽  
Hyoungshick Kim
Keyword(s):  
Vehicular Networks ◽  
Denial Of Service ◽  
Content Delivery ◽  
Dos Attacks ◽  
Promising Alternative ◽  
Content Centric Networking ◽  
Transmission Unit ◽  
Communication Environments ◽  
Maximum Transmission

Content-Centric Networking (CCN) is considered as a promising alternative to traditional IP-based networking for vehicle-to-everything communication environments. In general, CCN packets must be fragmented and reassembled based on the Maximum Transmission Unit (MTU) size of the content delivery path. It is thus challenging to securely protect fragmented packets against attackers who intentionally inject malicious fragments to disrupt normal services on CCN-based vehicular networks. This paper presents a new secure content fragmentation method that is resistant to Denial-of-Service (DoS) attacks in CCN-based vehicular networks. Our approach guarantees the authenticity of each fragment through the immediate fragment verification at interim nodes on the routing path. Our experiment results demonstrate that the proposed approach provides much stronger security than the existing approach named FIGOA, without imposing a significant overhead in the process. The proposed method achieves a high immediate verification probability of 98.2% on average, which is 52% higher than that of FIGOA, while requiring only 14% more fragments than FIGOA.

Spectator View: Enabling Asymmetric Interaction between HMD Wearers and Spectators with a Large Display

2021 ◽  
Vol 5 (ISS) ◽  
pp. 1-17
Author(s):  
Finn Welsford-Ackroyd ◽  
Andrew Chalmers ◽  
Rafael Kuffner dos Anjos ◽  
Daniel Medeiros ◽  
Hyejin Kim ◽  
...  
Keyword(s):  
Virtual World ◽  
Large Scale ◽  
User Study ◽  
Point Of View ◽  
Virtual Camera ◽  
Head Mounted Display ◽  
Joint Task ◽  
Reference Space ◽  
Collaborative Interaction ◽  
The Spectator

In this paper, we present a system that allows a user with a head-mounted display (HMD) to communicate and collaborate with spectators outside of the headset. We evaluate its impact on task performance, immersion, and collaborative interaction. Our solution targets scenarios like live presentations or multi-user collaborative systems, where it is not convenient to develop a VR multiplayer experience and supply each user (and spectator) with an HMD. The spectator views the virtual world on a large-scale tiled video wall and is given the ability to control the orientation of their own virtual camera. This allows spectators to stay focused on the immersed user's point of view or freely look around the environment. To improve collaboration between users, we implemented a pointing system where a spectator can point at objects on the screen, which maps an indicator directly onto the objects in the virtual world. We conducted a user study to investigate the influence of rotational camera decoupling and pointing gestures in the context of HMD-immersed and non-immersed users utilizing a large-scale display. Our results indicate that camera decoupling and pointing positively impacts collaboration. A decoupled view is preferable in situations where both users need to indicate objects of interest in the scene, such as presentations and joint-task scenarios, as it requires a shared reference space. A coupled view, on the other hand, is preferable in synchronous interactions such as remote-assistant scenarios.

Assessing Triangulation Across Methodologies, Methods, and Stakeholder Groups: The Joys, Woes, and Politics of Interpreting Convergent and Divergent Data

2018 ◽  
Vol 41 (1) ◽  
pp. 125-144 ◽  
Author(s):  
Rebecca Campbell ◽  
Rachael Goodman-Williams ◽  
Hannah Feeney ◽  
Giannina Fehler-Cabral
Keyword(s):  
Large Scale ◽  
Contextual Information ◽  
Policy Makers ◽  
Specific Data ◽  
Qualitative And Quantitative ◽  
Stakeholder Groups ◽  
Data Points ◽  
Evaluation Project ◽  
Collection Methods

The purpose of this study was to develop triangulation coding methods for a large-scale action research and evaluation project and to examine how practitioners and policy makers interpreted both convergent and divergent data. We created a color-coded system that evaluated the extent of triangulation across methodologies (qualitative and quantitative), data collection methods (observations, interviews, and archival records), and stakeholder groups (five distinct disciplines/organizations). Triangulation was assessed for both specific data points (e.g., a piece of historical/contextual information or qualitative theme) and substantive findings that emanated from further analysis of those data points (e.g., a statistical model or a mechanistic qualitative assertion that links themes). We present five case study examples that explore the complexities of interpreting triangulation data and determining whether data are deemed credible and actionable if not convergent.

scholarly journals MANETs performance analysis with dos attack at different routing protocols

2015 ◽  
Vol 4 (2) ◽  
pp. 390 ◽  
Author(s):  
Alaa Zain ◽  
Heba El-khobby ◽  
Hatem M. Abd Elkader ◽  
Mostafa Abdelnaby
Keyword(s):  
Routing Protocol ◽  
Routing Protocols ◽  
Ad Hoc ◽  
Denial Of Service ◽  
Geographic Routing ◽  
Security Threat ◽  
Dos Attacks ◽  
Reactive Routing ◽  
Hoc Networks ◽  
The Impact

A Mobile Ad-Hoc Networks (MANET) is widely used in many industrial and people's life applications, such as earth monitoring, natural disaster prevention, agriculture biomedical related applications, and many other areas. Security threat is one of the major aspects of MANET, as it is one of the basic requirements of wireless sensor network, yet this problem has not been sufficiently explored. The main purpose of this paper is to study different MANETs routing protocols with three scenarios of Denial of Service (DoS) attacks on network layer using proactive routing protocol i.e. Optimized Link State Routing (OLSR) and Reactive routing protocols like Ad hoc On-Demand Distance Vector (AODV), Hybrid routing protocols like Geographic Routing Protocol (GRP). Moreover, a comparative analysis of DoS attacks for throughput, Data loss, delay and network load is taken into account. The performance of MANET under the attack is studied to find out which protocol is more vulnerable to the attack and how much is the impact of the attack on both protocols. The simulation is done using OPNET 17.

scholarly journals Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition

2016 ◽  
Author(s):  
Timothy N. Rubin ◽  
Oluwasanmi Koyejo ◽  
Krzysztof J. Gorgolewski ◽  
Michael N. Jones ◽  
Russell A. Poldrack ◽  
...  
Keyword(s):  
Large Scale ◽  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Brain Activity ◽  
Human Cognition ◽  
Brain Images ◽  
Whole Brain ◽  
Context Sensitive ◽  
Cognitive States ◽  
Small Set

AbstractA central goal of cognitive neuroscience is to decode human brain activity--i.e., to infer mental processes from observed patterns of whole-brain activation. Previous decoding efforts have focused on classifying brain activity into a small set of discrete cognitive states. To attain maximal utility, a decoding framework must be open-ended, systematic, and context-sensitive--i.e., capable of interpreting numerous brain states, presented in arbitrary combinations, in light of prior information. Here we take steps towards this objective by introducing a Bayesian decoding framework based on a novel topic model---Generalized Correspondence Latent Dirichlet Allocation---that learns latent topics from a database of over 11,000 published fMRI studies. The model produces highly interpretable, spatially-circumscribed topics that enable flexible decoding of whole-brain images. Importantly, the Bayesian nature of the model allows one to “seed” decoder priors with arbitrary images and text--enabling researchers, for the first time, to generative quantitative, context-sensitive interpretations of whole-brain patterns of brain activity.

scholarly journals Peningkatan Keamanan Router Mikrotik Terhadap Serangan Denial of Service (DoS)

2020 ◽  
pp. 115-123
Author(s):  
Budi Jaya ◽  
Y Yuhandri ◽  
S Sumijan
Keyword(s):  
Denial Of Service ◽  
Digital Evidence ◽  
Dos Attack ◽  
Dos Attacks ◽  
Research Results ◽  
Security Enhancement ◽  
Software And Hardware ◽  
Operational Activities ◽  
Network Router ◽  
Live Forensics

Denial of Service (DoS) attacks are one of the most common attacks on website, networks, routers and servers, including on router mikrotik. A DoS attack aims to render a network router unable to service requests from authorized users. The result will disrupt the operational activities of the organization and cause material and non-material losses. In this study, a simulation and analysis of DoS attacks using the Live Forensics method were carried out and the router security enhancement from rectangular software and hardware. From the research results obtained digital evidence of DoS attacks in the form of IP addresses and attacker activity logs. In addition, the increase in router security in terms of software by using Firewall Filter and Firewall Raw has proven effective in preventing attacks. While improving router security in terms of hardware by setting a reset button on the router and firewall devices is also very necessary so that the router can avoid physical attacks by irresponsible persons

scholarly journals Attention Enhanced Serial Unet++ Network for Removing Unevenly Distributed Haze

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2868
Author(s):  
Wenxuan Zhao ◽  
Yaqin Zhao ◽  
Liqi Feng ◽  
Jiaxi Tang
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Real World ◽  
Large Scale ◽  
Learning Strategy ◽  
Contextual Information ◽  
Small Scale ◽  
Image Dehazing ◽  
Atmospheric Scattering ◽  
Real World Datasets

The purpose of image dehazing is the reduction of the image degradation caused by suspended particles for supporting high-level visual tasks. Besides the atmospheric scattering model, convolutional neural network (CNN) has been used for image dehazing. However, the existing image dehazing algorithms are limited in face of unevenly distributed haze and dense haze in real-world scenes. In this paper, we propose a novel end-to-end convolutional neural network called attention enhanced serial Unet++ dehazing network (AESUnet) for single image dehazing. We attempt to build a serial Unet++ structure that adopts a serial strategy of two pruned Unet++ blocks based on residual connection. Compared with the simple Encoder–Decoder structure, the serial Unet++ module can better use the features extracted by encoders and promote contextual information fusion in different resolutions. In addition, we take some improvement measures to the Unet++ module, such as pruning, introducing the convolutional module with ResNet structure, and a residual learning strategy. Thus, the serial Unet++ module can generate more realistic images with less color distortion. Furthermore, following the serial Unet++ blocks, an attention mechanism is introduced to pay different attention to haze regions with different concentrations by learning weights in the spatial domain and channel domain. Experiments are conducted on two representative datasets: the large-scale synthetic dataset RESIDE and the small-scale real-world datasets I-HAZY and O-HAZY. The experimental results show that the proposed dehazing network is not only comparable to state-of-the-art methods for the RESIDE synthetic datasets, but also surpasses them by a very large margin for the I-HAZY and O-HAZY real-world dataset.

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