Biblio

Software has become an integral part of every industry and organization. Due to improvement in technology and lack of expertise in coding techniques, software vulnerabilities are increasing day-by-day in the software development sector. The time gap between the identification of the vulnerabilities and their automated exploit attack is decreasing. This gives rise to the need for detection and prevention of security risks and development of secure software. Earlier the security risk is identified and corrected the better it is. Developers needs a framework which can report the security flaws in their system and reduce the chances of exploitation of these flaws by some malicious user. Common Vector Scoring System (CVSS) is a De facto metrics system used to assess the exploitability of vulnerabilities. CVSS exploitability measures use subjective values based on the views of experts. It considers mainly two factors, Access Vector (AV) and Authentication (AU). CVSS does not specify on what basis the third-factor Access Complexity (AC) is measured, whether or not it considers software properties. Our objective is to come up with a framework that automates the process of identifying vulnerabilities using software structural properties. These properties could be attack entry points, vulnerability locations, presence of dangerous system calls, and reachability analysis. This framework has been tested on two open source softwares - Apache HTTP server and Mozilla Firefox.

Distributed Denial-of-Service (DDoS) attacks continue to be a major threat on the Internet today. DDoS attacks overwhelm target services with requests or other traffic, causing requests from legitimate users to be shut out. A common defense against DDoS is to replicate a service in multiple physical locations/sites. If all sites announce a common prefix, BGP will associate users around the Internet with a nearby site, defining the catchment of that site. Anycast defends against DDoS both by increasing aggregate capacity across many sites, and allowing each site's catchment to contain attack traffic, leaving other sites unaffected. IP anycast is widely used by commercial CDNs and for essential infrastructure such as DNS, but there is little evaluation of anycast under stress. This paper provides the first evaluation of several IP anycast services under stress with public data. Our subject is the Internet's Root Domain Name Service, made up of 13 independently designed services ("letters", 11 with IP anycast) running at more than 500 sites. Many of these services were stressed by sustained traffic at 100× normal load on Nov. 30 and Dec. 1, 2015. We use public data for most of our analysis to examine how different services respond to stress, and identify two policies: sites may absorb attack traffic, containing the damage but reducing service to some users, or they may withdraw routes to shift both good and bad traffic to other sites. We study how these deployment policies resulted in different levels of service to different users during the events. We also show evidence of collateral damage on other services located near the attacks.