D. Mutz

2.5k citations
26 papers · 940 indexed · h-index 12

D. Mutz

23 papers receiving 796 citations

Peers

D. Mutz
Comparison fields: 5 of 55
  • Signal Processing 395
  • Computer Networks and Communications 593
  • Software 82
  • Artificial Intelligence 565
  • Hardware and Architecture 96
Replace Marios Iliofotou with:
Marios Iliofotou United States
Michel Barbeau Canada
Gerald M. Masson United States
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Hongjun Choi South Korea
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Yasser Shoukry United States
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Citations per field
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Marios Iliofotou · 1×
Citations per year

Countries citing papers authored by D. Mutz

Since Specialization
Citations

This map shows the geographic impact of D. Mutz's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by D. Mutz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Mutz more than expected).

Fields of papers citing papers by D. Mutz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. Mutz. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by D. Mutz. The network helps show where D. Mutz may publish in the future.

Co-authorship network

The 25 scholars most cited alongside D. Mutz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with D. Mutz Line = papers co-authored together D. Mutz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1
Automating mimicry attacks using static binary analysis
2005111
2
Reverse Engineering of Network Signatures
200522
3
Polymorphic Worm Detection Using Structural Information of Executables
200511
4 200462
5
Run-time Detection of Heap-based Overflows
200341
6
On the Detection of Anomalous System Call Arguments
20031
7 20031
8 200223
9 20012
10
Reducing costs of the modified Antarctic Mapping mission through automated planning
20012
11
ASPEN-Automated Planning and Scheduling for Space Mission Operation
200036
12
Hypothesis Generation Strategies for Adaptive Problem Solving
20001
13
An Integrated Architecture for Co-operating Rovers
19994
14
Using artificial intelligence planning to generate antenna tracking plans
19996
15 19995
16
Using Continous Planning Techniques to Coordinate Multiple Rovers
199925
17 19998
18 19991
19
On Efficient Heuristic Ranking of Hypotheses
19971
20 199718

About D. Mutz

D. Mutz is a scholar working on Software, Computer Networks and Communications and Artificial Intelligence, having authored 26 papers that have together received 940 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (13 papers), Constraint Satisfaction and Optimization (7 papers), Network Security and Intrusion Detection (6 papers), Advanced Malware Detection Techniques (4 papers), Model-Driven Software Engineering Techniques (3 papers), Health, Medicine and Society (3 papers), Distributed systems and fault tolerance (3 papers) and Distributed and Parallel Computing Systems (3 papers). The work is most often cited by research in Signal Processing (395 citations), Computer Networks and Communications (593 citations) and Software (82 citations). D. Mutz has collaborated with scholars based in United States and Austria. Frequent co-authors include Christopher Kruegel, William Robertson, Giovanni Vigna, Tara Estlin, Fredrik Valeur, Issa Nesnas, R. Volpe, R. Petráš, H. Das and Richard A. Kemmerer. Their work appears in journals such as AI Magazine, Journal of Artificial Intelligence Research, ACM Transactions on Information and System Security, USENIX Security Symposium and USENIX Large Installation Systems Administration Conference.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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