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The user is not the enemy: fighting malware by tracking user intentions

Published: 22 September 2008 Publication History

Abstract

Current access control policies provide no mechanisms for incorporating user behavior in access control decisions, even though the way a user interacts with a program often indicates what the user expects that program to do. We develop a new approach to access control, focusing on single-user systems, in which the complete history of user and program actions can be used to improve the precision and expressiveness of access control policies. We describe mechanisms for securely capturing user actions, mapping those actions onto likely user intents, and a language for defining access control policies that incorporate user intentions. We implemented a prototype for capturing user intentions, and present results from experiments on malware mitigation using the prototype. Our results show that a very simple MAC policy can prevent a significant amount of system damage caused by malware while not interfering with most benign software.

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cover image ACM Conferences
NSPW '08: Proceedings of the 2008 New Security Paradigms Workshop
August 2009
144 pages
ISBN:9781605583419
DOI:10.1145/1595676
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 22 September 2008

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Author Tags

  1. access control
  2. security policies
  3. user intent

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  • Research-article

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NSPW '08
Sponsor:
NSPW '08: 2008 New Security Paradigms Workshop
September 22 - 25, 2008
California, Lake Tahoe, USA

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Overall Acceptance Rate 62 of 170 submissions, 36%

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Cited By

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  • (2021)Ransomware Mitigation in the Modern Era: A Comprehensive Review, Research Challenges, and Future DirectionsACM Computing Surveys10.1145/347939354:9(1-36)Online publication date: 8-Oct-2021
  • (2021)Can the User Help? Leveraging User Actions for Network Profiling2021 Eighth International Conference on Software Defined Systems (SDS)10.1109/SDS54264.2021.9732164(1-8)Online publication date: 6-Dec-2021
  • (2021)A Framework for Comparative Analysis of Intention Mining ApproachesResearch Challenges in Information Science10.1007/978-3-030-75018-3_2(20-37)Online publication date: 8-May-2021
  • (2019)Using EEG to Predict and Analyze Password Memorability2019 IEEE International Conference on Cognitive Computing (ICCC)10.1109/ICCC.2019.00019(42-49)Online publication date: Jul-2019
  • (2018)Behavior Intention Derivation of Android Malware Using Ontology InferenceJournal of Electrical and Computer Engineering10.1155/2018/92502972018Online publication date: 1-Apr-2018
  • (2016)Mining sandboxesProceedings of the 38th International Conference on Software Engineering10.1145/2884781.2884782(37-48)Online publication date: 14-May-2016
  • (2015)Mind Your $$R, \varPhi $$sRevised Selected Papers of the 23rd International Workshop on Security Protocols XXIII - Volume 937910.1007/978-3-319-26096-9_9(80-90)Online publication date: 31-Mar-2015
  • (2012)User-Driven Access ControlProceedings of the 2012 IEEE Symposium on Security and Privacy10.1109/SP.2012.24(224-238)Online publication date: 20-May-2012
  • (2011)Detecting infection onset with behavior-based policies2011 5th International Conference on Network and System Security10.1109/ICNSS.2011.6059960(57-64)Online publication date: Sep-2011
  • (2011)An Automatically Capture Method of User’s IntentionComputer Science for Environmental Engineering and EcoInformatics10.1007/978-3-642-22694-6_52(371-377)Online publication date: 2011
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