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What is Attacking Sensor

Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks
Sensor in a CSMA/CA WSN that may choose between respecting the binary exponential backoff procedure or using a uniform backoff procedure that provides the sensor with an advantage in terms of throughput.
Published in Chapter:
The Threat of Intelligent Attackers Using Deep Learning: The Backoff Attack Case
Juan Parras (Information Processing and Telecommunications Center, Universidad Politécnica de Madrid, Spain) and Santiago Zazo (Information Processing and Telecommunications Center, Universidad Politécnica de Madrid, Spain)
DOI: 10.4018/978-1-7998-5068-7.ch006
Abstract
The significant increase in the number of interconnected devices has brought new services and applications, as well as new network vulnerabilities. The increasing hardware capacities of these devices and the developments in the artificial intelligence field mean that new and complex attack methods are being developed. This chapter focuses on the backoff attack in a wireless network using CSMA/CA multiple access, and it shows that an intelligent attacker, making use of control theory, can successfully exploit a sequential probability ratio test-based defense mechanism. Also, recent developments in the deep reinforcement learning field allows that attackers that do not have full knowledge of the defense mechanism are able to successfully learn to attack it. Thus, this chapter illustrates by means of the backoff attack, the possibilities that the recent advances in the artificial intelligence field bring to intelligent attackers, and highlights the importance of researching in intelligent defense methods able to cope with such attackers.
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