%0 Journal Article
%T Declassification Policy Based on Content and Location Dimensions<br>基于内容和地点维度的机密信息降级策略
%A ZHU Hao
%A ZHUANG Yi
%A XUE Yu
%A DING Wei-ping
%A <br>朱浩
%A 庄毅
%A 薛羽
%A 丁卫平
%J 计算机科学
%D 2012
%I 
%X Current research on declassification policies mainly involves content, location, time and other dimensions, and each of them has some limitations. Attacker could learn more confidential information than intended by using the vulner}r bility of other dimensions. A synthesis of different dimensions in declassification policy would further improve assu- rance that confidential information is being declassified properly. This paper proposed a declassification policy based on the content and location dimensions, using attacker knowledge model. The key idea of content dimension of the policy is that attacker is not allowed to increase observations about confidential information by causing misuse of the declassifica- lion mechanism,and that location dimension of the policy controls confidential information is declassified only through the declassification statement. Additionally,we established type rules of policy enforcement and proved its soundness.
%K Information-flow controls
%K Declassification policy
%K Confidentiality
%K Non-interference<br>信息流控制
%K 降级策略
%K 机密性
%K 无干扰
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=FDABA0B07E06BAF8EEF7FA6B37F69498&yid=99E9153A83D4CB11&vid=7C3A4C1EE6A45749&iid=5D311CA918CA9A03&sid=D59111839E7C8BDF&eid=A6301713E4DF1FE3&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=0