Abstract: This paper presents a context-sensitive media similarity search algorithm. One of the central problems regarding media search is the semantic gap between the low-level features computed automatically from media data and the human interpretation of them. This is because the notion of similarity is usually based on high-level abstraction but the low-level features do not sometimes reflect the human perception. Many media search algorithms have used the Minkowski metric to measure similarity between image pairs. However those functions cannot adequately capture the aspects of the characteristics of the human visual system as well as the nonlinear relationships in contextual information given by images in a collection. Our search algorithm tackles this problem by employing a similarity measure and a ranking strategy that reflect the nonlinearity of human perception and contextual information in a dataset. Similarity search in an image database based on this contextual information shows encouraging experimental results.
Abstract: Control Flow Integrity (CFI) is one of the most
promising technique to defend Code-Reuse Attacks (CRAs).
Traditional CFI Systems and recent Context-Sensitive CFI use coarse
control flow graphs (CFGs) to analyze whether the control flow
hijack occurs, left vast space for attackers at indirect call-sites. Coarse
CFGs make it difficult to decide which target to execute at indirect
control-flow transfers, and weaken the existing CFI systems actually.
It is an unsolved problem to extract CFGs precisely and perfectly
from binaries now. In this paper, we present an algorithm to get a
more precise CFG from binaries. Parameters are analyzed at indirect
call-sites and functions firstly. By comparing counts of parameters
prepared before call-sites and consumed by functions, targets of
indirect calls are reduced. Then the control flow would be more
constrained at indirect call-sites in runtime. Combined with CCFI,
we implement our policy. Experimental results on some popular
programs show that our approach is efficient. Further analysis show
that it can mitigate COOP and other advanced attacks.
Abstract: Apps are today the most important possibility to adapt
mobile phones and computers to fulfill the special needs of their
users. Location- and context-sensitive programs are hereby the key to
support the interaction of the user with his/her environment and also
to avoid an overload with a plenty of dispensable information. The
contribution shows, how a trusted, secure and really bi-directional
communication and interaction among users and their environment
can be established and used, e.g. in the field of home automation.