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Proceedings ArticleDOI

Honeypot: a supplemented active defense system for network security

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TLDR
A honeypot is a supplemented active defense system for network security that traps attacks, records intrusion information about tools and activities of the hacking process, and prevents attacks outbound the compromised system.
Abstract
A honeypot is a supplemented active defense system for network security. It traps attacks, records intrusion information about tools and activities of the hacking process, and prevents attacks outbound the compromised system. Integrated with other security solutions, a honeypot can solve many traditional dilemmas. We expatiate key components of data capture and data control in a honeypot, and give a classification for honeypots according to security goals and application goals. We review the technical progress and security contribution of production honeypots and research honeypots. We present typical honeypot solutions and predict the technical trends of integration, virtualization and distribution for future honeypots.

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Citations
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Proceedings Article

OCHD:Preserving Obliviousness Characteristic of Honeypot Database

TL;DR: This paper proposes that a suspected user be provided with synthetic information (in place of denial of access) with the help of which the administrator could confirm the suspicion and give techniques for it being oblivious to the user.
Proceedings ArticleDOI

Deceptive Secret Sharing

TL;DR: This paper considers an approach that combines confidentiality and deception using secret sharing, which has traditionally been used strictly for confidentiality purposes, and presents techniques that work with both XOR secret sharing and Shamir's polynomial-based threshold secret sharing.
Proceedings ArticleDOI

A honeypot system for wearable networks

TL;DR: This paper proposes a solution for detecting adversaries attacking the communication channel of a BAN called a wearable honeypot system that works by communicating fake user health information between the base station and a set of designated decoy nodes in the BAN.

Early Warning and Prediction of Interest Attacks and Exploits

TL;DR: Using an accredited Honeypot, an Exploit Prediction System (EPS) is developed using a decision-tree matrix, which provides an excellent tool in choosing only those data packets needing further analysis and disregard the remaining packets.
Journal ArticleDOI

The Global State of Security in Industrial Control Systems: An Empirical Analysis of Vulnerabilities around the World

TL;DR: In this paper, the presence of OT-devices in the Internet is analyzed from an attacker's perspective, and public available tools, such as the search engine Shodan and vulnerability databases, are employed to find commonly used OT devices and map vulnerabilities to them.
References
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Proceedings ArticleDOI

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Proceedings ArticleDOI

Implementing a distributed firewall

TL;DR: This paper presents the design and implementation of a distributed rewall using the KeyNote trust management system to specify, distribute, and resolve policy, and OpenBSD, an open source UNIX operating system.
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Temporal sequence learning and data reduction for anomaly detection

TL;DR: An approach that transforms temporal sequences of discrete, unordered observations into a metric space via a similarity measure that encodes intra-attribute dependencies and demonstrates that it can accurately differentiate the profiled user from alternative users when the available features encode sufficient information.
Proceedings ArticleDOI

Temporal sequence learning and data reduction for anomaly detection

TL;DR: An approach that transforms temporal sequences of discrete, unordered observations into a metric space via a similarity measure that encodes intra-attribute dependencies and demonstrates that it can accurately differentiate the profiled user from alternative users when the available features encode sufficient information.