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20092026
most citedN-BaIoT: Network-based Detection of IoT Botnet Attacks Using Deep Autoencoders

1.5k citations · 3.1k across the 169 of their papers we have counts for

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Showing 2017Show all

14 papers · 1 filter

cs.CR2017

aIR-Jumper: Covert Air-Gap Exfiltration/Infiltration via Security Cameras & Infrared (IR)

Mordechai Guri, Dima Bykhovsky, Yuval Elovici

Infrared (IR) light is invisible to humans, but cameras are optically sensitive to this type of light. In this paper, we show how attackers can use surveillance cameras and infrare…

cs.CR2017★ 198 cited

Detection of Unauthorized IoT Devices Using Machine Learning Techniques

Yair Meidan, Michael Bohadana, Asaf Shabtai +4

Security experts have demonstrated numerous risks imposed by Internet of Things (IoT) devices on organizations. Due to the widespread adoption of such devices, their diversity, sta…

cs.CR2017★ 17 cited

Power Consumption-based Detection of Sabotage Attacks in Additive Manufacturing

Samuel B. Moore, Jacob Gatlin, Sofia Belikovetsky +3

Additive Manufacturing (AM), a.k.a. 3D Printing, is increasingly used to manufacture functional parts of safety-critical systems. AM's dependence on computerization raises the conc…

cs.LG2017★ 8 cited

Temporal Pattern Discovery for Accurate Sepsis Diagnosis in ICU Patients

Eitam Sheetrit, Nir Nissim, Denis Klimov +3

Sepsis is a condition caused by the body's overwhelming and life-threatening response to infection, which can lead to tissue damage, organ failure, and finally death. Common signs…

cs.CR2017★ 34 cited

Protecting Military Avionics Platforms from Attacks on MIL-STD-1553 Communication Bus

Orly Stan, Yuval Elovici, Asaf Shabtai +3

MIL-STD-1553 is a military standard that defines the physical and logical layers, and a command/response time division multiplexing of a communication bus used in military and aero…

cs.CR2017★ 12 cited

Generic Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers

Ishai Rosenberg, Asaf Shabtai, Lior Rokach +1

In this paper, we present a black-box attack against API call based machine learning malware classifiers, focusing on generating adversarial sequences combining API calls and stati…