FPGAPRO: A Defense Framework Against Crosstalk-Induced Secret Leakage in FPGA

With the emerging cloud-computing development, FPGAs are being integrated with cloud servers for higher performance. Recently, it has been explored to enable multiple users to share the hardware resources of a remote FPGA, i.e., to execute their own applications simultaneously. Although being a promising technique, multi-tenant FPGA unfortunately brings its unique security concerns. It has been demonstrated that the capacitive crosstalk between FPGA long-wires can be a side-channel to extract secret information, giving adversaries the opportunity to implement crosstalk-based side-channel attacks. Moreover, recent work reveals that medium-wires and multiplexers in configurable logic block (CLB) are also vulnerable to crosstalk-based information leakage. In this work, we propose FPGAPRO: a defense framework leveraging P lacement, R outing, and O bfuscation to mitigate the secret leakage on FPGA components, including long-wires, medium-wires, and logic elements in CLB. As a user-friendly defense strategy, FPGAPRO focuses on protecting the security-sensitive instances meanwhile considering critical path delay for performance maintenance. As the proof-of-concept, the experimental result demonstrates that FPGAPRO can effectively reduce the crosstalk-caused side-channel leakage by 138 times. Besides, the performance analysis shows that this strategy prevents the maximum frequency from timing violation.

Brown Seaweeds (Phaeophyceae) of Britain and Ireland

Brown Seaweeds (Phaeophyceae) of Britain and Ireland provides the first complete, up-to-date, detailed illustrated guide and keys to the nearly 200 species of brown algae present around the coasts of Britain and Ireland. It is the culmination of over 30 years of field and laboratory studies by the author. Following an exhaustive introduction that covers the biology and ecology of brown seaweeds, a checklist of species is set out, followed by clear and user-friendly keys to the genera. Particular attention is then paid to providing detailed illustrations, and the volume holds more than 300 compound plates of line drawings and photographs in its extensive taxonomic treatment. Comprehensive information is given on the geographical and seasonal distributions, synonymy, morphology, anatomy, cytology, reproduction, life histories, taxonomy, systematics and bibliographic material pertaining to each species. Notably, this flora offers a much fuller consideration of many of the lesser known, more cryptic microscopic brown algae than previously available. Further, the book also contains the results of much original research undertaken by the author. This will surely remain a standard reference work on brown seaweeds for many years to come – an indispensable research tool and field guide for phycologists and students throughout the North Atlantic region and beyond.

Traffic Simulation with Open-Source and Commercial Traffic Microsimulators: A Case Study

The analysis of traffic problems in large urban centers often requires the use of computational tools, which give the possibility to make a more detailed analysis of the issue, suggest solutions, predict behaviors and, above all, support efficient decision-making. Transport microsimulation software programs are a handy set of tools for this type of analysis. This research paper shows a case study where functions and limitations of Aimsun version 8.2.0, a commercial-like European software and Sumo version 1.3.1, a European open-source software, are presented. The input and output data are similar in both software and the interpretation of results is quite intuitive for both, as well. However, Aimsun's graphical interface interprets results more user-friendly, because Sumo is an open-access software presented as an effective alternative tool for transport modeling.

Gotta CAPTCHA ’Em All: A Survey of 20 Years of the Human-or-computer Dilemma

A recent study has found that malicious bots generated nearly a quarter of overall website traffic in 2019 [102]. These malicious bots perform activities such as price and content scraping, account creation and takeover, credit card fraud, denial of service, and so on. Thus, they represent a serious threat to all businesses in general, but are especially troublesome for e-commerce, travel, and financial services. One of the most common defense mechanisms against bots abusing online services is the introduction of Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA), so it is extremely important to understand which CAPTCHA schemes have been designed and their actual effectiveness against the ever-evolving bots. To this end, this work provides an overview of the current state-of-the-art in the field of CAPTCHA schemes and defines a new classification that includes all the emerging schemes. In addition, for each identified CAPTCHA category, the most successful attack methods are summarized by also describing how CAPTCHA schemes evolved to resist bot attacks, and discussing the limitations of different CAPTCHA schemes from the security, usability, and compatibility point of view. Finally, an assessment of the open issues, challenges, and opportunities for further study is provided, paving the road toward the design of the next-generation secure and user-friendly CAPTCHA schemes.

Guided Feature Identification and Removal for Resource-constrained Firmware

IoT firmware oftentimes incorporates third-party components, such as network-oriented middleware and media encoders/decoders. These components consist of large and mature codebases, shipping with a variety of non-critical features. Feature bloat increases code size, complicates auditing/debugging, and reduces stability. This is problematic for IoT devices, which are severely resource-constrained and must remain operational in the field for years. Unfortunately, identification and complete removal of code related to unwanted features requires familiarity with codebases of interest, cumbersome manual effort, and may introduce bugs. We address these difficulties by introducing PRAT, a system that takes as input the codebase of software of interest, identifies and maps features to code, presents this information to a human analyst, and removes all code belonging to unwanted features. PRAT solves the challenge of identifying feature-related code through a novel form of differential dynamic analysis and visualizes results as user-friendly feature graphs . Evaluation on diverse codebases shows superior code removal compared to both manual feature deactivation and state-of-art debloating tools, and generality across programming languages. Furthermore, a user study comparing PRAT to manual code analysis shows that it can significantly simplify the feature identification workflow.

Smart Voting System Using Facial Recognition

In this paper a new authentication technique is discussed i-e; facial recognition verification for online voting system. It aims to develop a computerized voting system to make the election process more secure and user friendly. The electorate want to visit distinct locations like polling cubicles and stand in an extended queue to cast their vote, because of such reasons most of the people skip their chance of voting. The voter who isn't eligible also can forged its vote via way of means of faux way which can also additionally cause many problems. That's why in this project we have proposed a system or way for voting which is very effective or useful in voting. This system can also save money of the government which is spent in the election process. Overall this project is being developed to help staff of election commission of India and also reduce the human efforts. Keywords: Online Voting, Biometric Authentication, Security System.

DNA Methylation-Driven Genes for Developing Survival Nomogram for Low-Grade Glioma

Low-grade gliomas (LGG) are heterogeneous, and the current predictive models for LGG are either unsatisfactory or not user-friendly. The objective of this study was to establish a nomogram based on methylation-driven genes, combined with clinicopathological parameters for predicting prognosis in LGG. Differential expression, methylation correlation, and survival analysis were performed in 516 LGG patients using RNA and methylation sequencing data, with accompanying clinicopathological parameters from The Cancer Genome Atlas. LASSO regression was further applied to select optimal prognosis-related genes. The final prognostic nomogram was implemented together with prognostic clinicopathological parameters. The predictive efficiency of the nomogram was internally validated in training and testing groups, and externally validated in the Chinese Glioma Genome Atlas database. Three DNA methylation-driven genes, ARL9, CMYA5, and STEAP3, were identified as independent prognostic factors. Together with IDH1 mutation status, age, and sex, the final prognostic nomogram achieved the highest AUC value of 0.930, and demonstrated stable consistency in both internal and external validations. The prognostic nomogram could predict personal survival probabilities for patients with LGG, and serve as a user-friendly tool for prognostic evaluation, optimizing therapeutic regimes, and managing LGG patients.

The multi-actor approach in thematic networks for agriculture and forestry innovation

The co-creation and sharing of knowledge among different types of actors with complementary expertise is known as the Multi-Actor Approach (MAA). This paper presents how Horizon2020 Thematic-Networks (TNs) deal with the MAA and put forward best practices during the different project phases, based on the results of a desktop study, interviews, surveys and expert workshops. The study shows that not all types of actors are equally involved in TN consortia and participatory activities, meaning TNs might be not sufficiently demand-driven and the uptake of the results is not optimal. Facilitators are key to contributing to the relationships and the mutual understanding between different actors. Moreover, a user-friendly digital knowledge platform linked to demonstration activities and peer-to-peer exchange can improve the sharing of knowledge, enhancing impact in agricultural and forestry innovation in the longer term.

Garbage Collector Machine with Instant Reward

Now a days, waste management is becoming a big issue. Due to improper waste disposal and management, society is facing environmental contamination problems which affects directly on human beings. Garbage separation is also a difficult task for the workers. People are not aware of these problems and do not dispose the garbage at proper places which leads to garbage accumulation at public places. So, to encourage people for proper garbage disposal this paper deals with the concept which will provide platform to dispose of waste in a more scientific and user-friendly. In return they will be rewarded in a cashless manner through means of digital payments and free coupons etc. The nature(wet or dry) and weight of garbage disposed in the machine will be sensed for segregating it in two section. The user will be rewarded according to the weight of garbage. Flow of the operations will be programmed in Arduino Uno micro-controller, sensors and GSM technology. This system leads to collection and segregation of waste at one place, for effective recycling and to reduce environmental. Also this will helps us to contribute in Swachh Bharat Abhiyaan scheme launched by the government of India.

How to Implement User-Friendly BLMs in the Absence of DOC Monitoring Data: A Case Study on Bulgarian Surface Waters

The metal bioavailability concept is implemented in the Water Framework Directive (WFD) compliance assessment. The bioavailability assessment is usually performed by the application of user-friendly Biotic Ligand Models (BLMs), which require dissolved metal concentrations to be used with the “matching” data of the supporting physicochemical parameters of dissolved organic carbon (DOC), pH and Cadissolved. Many national surface water monitoring networks do not have sufficient matching data records, especially for DOC. In this study, different approaches for dealing with the missing DOC data are presented: substitution using historical data; the appropriate percentile of DOC concentrations; and combinations of the two. The applicability of the three following proposed substitution approaches is verified by comparison with the available matching data: (i) calculations from available TOC data; (ii) the 25th percentile of the joint Bulgarian monitoring network DOC data (measured and calculated by TOC); and (iii) the 25th percentile of the calculated DOC from the matching TOC data for the investigated surface water body (SWB). The application of user-friendly BLMs (BIO-MET, M-BAT and PNEC Pro) to 13 surface water bodies (3 reservoirs and 10 rivers) in the Bulgarian surface waters monitoring network outlines that the suitability of the substitution approaches decreases in order: DOC calculated by TOC > the use of the 25th percentile of the data for respective SWB > the use of the 25th percentile of the Bulgarian monitoring network data. Additionally, BIO-MET is the most appropriate tool for the bioavailability assessment of Cu, Zn and Pb in Bulgarian surface water bodies.