22,899 research outputs found
Model the System from Adversary Viewpoint: Threats Identification and Modeling
Security attacks are hard to understand, often expressed with unfriendly and
limited details, making it difficult for security experts and for security
analysts to create intelligible security specifications. For instance, to
explain Why (attack objective), What (i.e., system assets, goals, etc.), and
How (attack method), adversary achieved his attack goals. We introduce in this
paper a security attack meta-model for our SysML-Sec framework, developed to
improve the threat identification and modeling through the explicit
representation of security concerns with knowledge representation techniques.
Our proposed meta-model enables the specification of these concerns through
ontological concepts which define the semantics of the security artifacts and
introduced using SysML-Sec diagrams. This meta-model also enables representing
the relationships that tie several such concepts together. This representation
is then used for reasoning about the knowledge introduced by system designers
as well as security experts through the graphical environment of the SysML-Sec
framework.Comment: In Proceedings AIDP 2014, arXiv:1410.322
Analysis of the NIST database towards the composition of vulnerabilities in attack scenarios
The composition of vulnerabilities in attack scenarios has been traditionally performed based on detailed pre- and post-conditions. Although very precise, this approach is dependent on human analysis, is time consuming, and not at all scalable. We investigate the NIST National Vulnerability Database (NVD) with three goals: (i) understand the associations among vulnerability attributes related to impact, exploitability, privilege, type of vulnerability and clues derived from plaintext descriptions, (ii) validate our initial composition model which is based on required access and resulting effect, and (iii) investigate the maturity of XML database technology for performing statistical analyses like this directly on the XML data. In this report, we analyse 27,273 vulnerability entries (CVE 1) from the NVD. Using only nominal information, we are able to e.g. identify clusters in the class of vulnerabilities with no privilege which represent 52% of the entries
Centralized prevention of denial of service attacks
The world has come to depend on the Internet at an increasing rate for communication, e-commerce, and many other essential services. As such, the Internet has become an integral part of the workings of society at large. This has lead to an increased vulnerability to remotely controlled disruption of vital commercial and government operations---with obvious implications. This disruption can be caused by an attack on one or more specific networks which will deny service to legitimate users or an attack on the Internet itself by creating large amounts of spurious traffic (which will deny services to many or all networks). Individual organizations can take steps to protect themselves but this does not solve the problem of an Internet wide attack. This thesis focuses on an analysis of the different types of Denial of Service attacks and suggests an approach to prevent both categories by centralized detection and limitation of excessive packet flows
- âŠ