Optimal hackback

Professor Jay Kesan from the University of Illinois College of Law, in joint work with Ruperto Majuca of the University of Illinois Department of Economics, argue in favor of legal rules that allow “hacking [data] back" in certain business circumstances. They analyze the strategic interaction b...

Full description

Saved in:
Bibliographic Details
Main Authors: Kesana, Jap P., Majuca, Ruperto P.
Format: text
Published: Animo Repository 2010
Subjects:
Online Access:https://animorepository.dlsu.edu.ph/faculty_research/8000
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: De La Salle University
id oai:animorepository.dlsu.edu.ph:faculty_research-8791
record_format eprints
spelling oai:animorepository.dlsu.edu.ph:faculty_research-87912023-01-10T00:18:41Z Optimal hackback Kesana, Jap P. Majuca, Ruperto P. Professor Jay Kesan from the University of Illinois College of Law, in joint work with Ruperto Majuca of the University of Illinois Department of Economics, argue in favor of legal rules that allow “hacking [data] back" in certain business circumstances. They analyze the strategic interaction between the hack and the attacked company or individual and conclude that neither total prohibition nor unrestrained permission of hack-back is optimal. Instead, they argue that when other alternatives such as criminal enforcement and litigation are ineffective, self-defense is the best response to cybercrime because there is, a high likelihood of correctly attacking the criminal, and the mitigation of damages to the hacked victim’s systems may outweigh the potential damages to third parties during the hack-back. In addition, the law should require that counterstrikers use only the requisite measures that arc necessary to avoid damages of third parties in their decision-making. Finally, better and ever-improving intrusion detection systems (IDS) and traceback technology improve the deterrent effect and efficiency of hack-bad. 2010-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/8000 Faculty Research Work Animo Repository Hacking Computer security—Law and legislation Computer Law
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Hacking
Computer security—Law and legislation
Computer Law
spellingShingle Hacking
Computer security—Law and legislation
Computer Law
Kesana, Jap P.
Majuca, Ruperto P.
Optimal hackback
description Professor Jay Kesan from the University of Illinois College of Law, in joint work with Ruperto Majuca of the University of Illinois Department of Economics, argue in favor of legal rules that allow “hacking [data] back" in certain business circumstances. They analyze the strategic interaction between the hack and the attacked company or individual and conclude that neither total prohibition nor unrestrained permission of hack-back is optimal. Instead, they argue that when other alternatives such as criminal enforcement and litigation are ineffective, self-defense is the best response to cybercrime because there is, a high likelihood of correctly attacking the criminal, and the mitigation of damages to the hacked victim’s systems may outweigh the potential damages to third parties during the hack-back. In addition, the law should require that counterstrikers use only the requisite measures that arc necessary to avoid damages of third parties in their decision-making. Finally, better and ever-improving intrusion detection systems (IDS) and traceback technology improve the deterrent effect and efficiency of hack-bad.
format text
author Kesana, Jap P.
Majuca, Ruperto P.
author_facet Kesana, Jap P.
Majuca, Ruperto P.
author_sort Kesana, Jap P.
title Optimal hackback
title_short Optimal hackback
title_full Optimal hackback
title_fullStr Optimal hackback
title_full_unstemmed Optimal hackback
title_sort optimal hackback
publisher Animo Repository
publishDate 2010
url https://animorepository.dlsu.edu.ph/faculty_research/8000
_version_ 1767196831133990912