3,005 research outputs found
Harvey: A Greybox Fuzzer for Smart Contracts
We present Harvey, an industrial greybox fuzzer for smart contracts, which
are programs managing accounts on a blockchain. Greybox fuzzing is a
lightweight test-generation approach that effectively detects bugs and security
vulnerabilities. However, greybox fuzzers randomly mutate program inputs to
exercise new paths; this makes it challenging to cover code that is guarded by
narrow checks, which are satisfied by no more than a few input values.
Moreover, most real-world smart contracts transition through many different
states during their lifetime, e.g., for every bid in an auction. To explore
these states and thereby detect deep vulnerabilities, a greybox fuzzer would
need to generate sequences of contract transactions, e.g., by creating bids
from multiple users, while at the same time keeping the search space and test
suite tractable. In this experience paper, we explain how Harvey alleviates
both challenges with two key fuzzing techniques and distill the main lessons
learned. First, Harvey extends standard greybox fuzzing with a method for
predicting new inputs that are more likely to cover new paths or reveal
vulnerabilities in smart contracts. Second, it fuzzes transaction sequences in
a targeted and demand-driven way. We have evaluated our approach on 27
real-world contracts. Our experiments show that the underlying techniques
significantly increase Harvey's effectiveness in achieving high coverage and
detecting vulnerabilities, in most cases orders-of-magnitude faster; they also
reveal new insights about contract code.Comment: arXiv admin note: substantial text overlap with arXiv:1807.0787
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent âdevicesâ, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew âcognitive devicesâ are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
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