Improving Security Using Extensible Lightweight Static Analysis

By David E. Evans, David Larochelle. IEEE Software, 2002

538 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/6119e9eedf900a2b47fc52ffa186e5bceeb76a8b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. C. Leckie
2. Lin Tan
3. T. Hoare
4. Tao Peng
5. Konrad Rieck
6. Yuanyuan Zhou
7. Jun Xu
8. Shih-Kun Huang

In Information Systems

1. Lin Tan
2. T. Hoare
3. Konrad Rieck
4. Yuanyuan Zhou
5. Jun Xu
6. C. Leckie
7. Shih-Kun Huang
8. Kotagiri Ramamohanarao

In Signal Processing

1. C. Leckie
2. T. Hoare
3. Konrad Rieck
4. Lin Tan
5. Yuanyuan Zhou
6. Jun Xu
7. Shih-Kun Huang
8. Kotagiri Ramamohanarao

Citations in the corpus

• Survey of network-based defense mechanisms countering the DoS and DDoS problems (2007, background): “A prominent example is that during the spread of the Code Red worm [CERT 2001], over 300,000 zombie machines were compromised to launch a denial of service attack on the White House Web site [Evans and Larochelle 2002].”
• The verifying compiler: A grand challenge for computing research (2003, background): “already available, and can be applied now to legacy code [22-27].”
• Software Vulnerability Analysis and Discovery Using Machine-Learning and Data-Mining Techniques (2017, background): “…is a static program analysis approach where untrusted data from input sources is marked as tainted and its flow to sensitive program statements known as sinks is tracked as a potential indicator of vulnerability (Evans and Larochelle 2002; Larus et al. 2004; Ayewah et al. 2008; Bessey et al. 2010).”
• Modeling and Discovering Vulnerabilities with Code Property Graphs (2014, background): “For example, Evans and Larochelle [8] describe Splint, which allows analysts to provide annotations to find incarnations of buffer overflows and format string vulnerabilities in different applications.”
• Formal methods: Practice and experience (2009, unknown): “Examples include heuristic tools such as the 30-year-old UNIX utility lint [Johnson 1978], which .ags potential defects in C programs, and more recent tools such as Splint [Evans and Larochelle 2002], which provides annotation-assisted lightweight static checking.”
• /*icomment: bugs or bad comments?*/ (2007, background): “Annotation languages [5, 7, 8, 11, 14, 18, 21, 30, 31, 36, 39] are proposed for developers to comment source code using a formal language to specify some special information such as type safety [46], information flow [30], performance expectations [31], etc.”
• Web application security assessment by fault injection and behavior monitoring (2003, methodology): “…walk-throughs, and Testing tools; H.3.1 [Information Storage and Retrieval]: Content Analysis and Indexing Dictionaries and Indexing Method; K.6.5 [Management of Computing and Information Systems]: Security and Protection Invasive software and Unauthorized access General Terms Security, Design.”
• Non-Control-Data Attacks Are Realistic Threats (2005, background): “The idea is to tag the data directly or indirectly derived from I/O as spurious data, a concept more commonly referred to as tainted data in other literature [16][30][44].”