Software vulnerabilities can pose severe harms to a computing system. They lead system crash, privacy leakage, or even physical damage. Correctly identifying among enormous software codes in timely manner is so far the essential prerequisite patch them. Unfortantely, current vulnerability identification methods, either classic ones deep-learning-based ones, have several critical drawbacks, maki...

Today’s organizations are inherently open and connected, sharing knowledge and ideas in order to remain innovative. As a result, these organizations are also more vulnerable to information theft through different forms of security breaches caused by hackers and competitors. One way of understanding the vulnerability of an information system is to build and analyze the attack graph of that syste...

identification and analysis of farmers’ vulnerability associated with their risk aversion degree is one of the necessary requirements for planning and reducing impacts of drought in iran. so, this study was investigated three risk vulnerability parameters (economic, social and technical) among wheat farmers categorized in accordance with their risk aversion degree in the mashhad county (iran) b...

Constructing accurate similarity graph is an important process in graph-based clustering. However, traditional methods have three drawbacks, such as the inaccuracy of graph, vulnerability to noise and outliers, need for additional discretization process. In order eliminate these limitations, entropy regularized unsupervised clustering based on maximum correntropy criterion adaptive neighbors (E...

let $r$ be a commutative ring with identity. let $g(r)$ denote the maximal graph associated to $r$, i.e., $g(r)$ is a graph with vertices as the elements of $r$, where two distinct vertices $a$ and $b$ are adjacent if and only if there is a maximal ideal of $r$ containing both. let $gamma(r)$ denote the restriction of $g(r)$ to non-unit elements of $r$. in this paper we study the various graphi...

We describe the optimal placement of intrusion detection system (IDS) sensors and prioritization of IDS alarms, using attack graph analysis. Our attack graphs predict the various possible ways of penetrating a network to reach critical assets. In particular, automated analysis of network configuration and attacker exploits provides an attack graph showing all possible paths to critical assets. ...

The edge-tenacity Te(G) of a graph G was defined as Te(G) = min F⊂E(G) {| F | +τ(G− F ) ω(G− F ) } where the minimum is taken over all edge cutset F of G. We define G-F to be the graph induced by the edges of E(G) − F , τ(G − F ) is the number of edges in the largest component of the graph induced by G-F and ω(G−F ) is the number of components of G− F . A set F ⊂ E(G) is said to be a Te-set of ...

The desire for uncensored access to the Internet has motivated the development of both open proxies like Tor and social graph-based overlays like FreeNet. However, neither design is sufficient, as relays in open proxies are easily exposed and blocked, and overlays based just on social trust suffer from poor availability and performance. In this paper, we introduce the design for a new overlay s...

We introduce a new graph parameter, the rupture degree. The rupture degree for a complete graph Kn is defined as 1 − n, and the rupture degree for an incomplete connected graph G is defined by r(G) = max{ω(G − X)− |X| − m(G − X) : X ⊂ V(G),ω(G − X) > 1}, where ω(G − X) is the number of components of G − X and m(G − X) is the order of a largest component of G − X . It is shown that this paramete...