The DOI matches its Crossref record.
Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security
Abstract
It is our pleasure to present the proceedings of the 23rd ACM Conference on Computer and Communications Security (CCS 2016), held in Vienna, Austria, on October 24-28, 2016. All papers in the proceedings were subject to a rigorous process of peer review. We received 831 fully reviewed submissions, the largest number of submissions received to date by a computer security conference. A Program Committee comprising 141 experts from 20 countries, helped by 360 external reviewers, evaluated these submissions, employing the customary double-blind review procedure. The review process had a 16.5% acceptance rate, resulting in 137 papers being accepted to the program, and very broad coverage of the entire security area. The review process was organized in three phases. In the first review round, at least two preliminary reviews were written for each paper. Most papers went on to a second round, during which at least one additional review was solicited. At this point, the authors were given an opportunity to respond to the comments received (in a rebuttal phase). Finally, in the third round, the program committee actively and comprehensively discussed the papers, and, if necessary, requested additional reviews. Within the program committee, a "rebuttal committee" subgroup helped to spur discussion, to ensure that author responses were considered carefully, and to reflect the post-review discussion in the feedback to authors. New this year, we relied heavily on the TPMS system for assigning submissions to reviews, and we thank Laurent Charlin for writing this system and for all his help with using it.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Ølnes, S., Ubacht, J., & Janssen, M. (2017) · Government Information Quarterly · doi:10.1016/j.giq.2017.09.007 · Cited by 1,107
Deep neural network models for computational histopathology: A survey
Srinidhi, C. L., Ciga, O., & Martel, A. L. (2021) · Medical Image Analysis · doi:10.1016/j.media.2020.101813 · Cited by 749
Blockchain's adoption in iot: the challenges, and a way forward
Makhdoom, I., Abolhasan, M., Abbas, H., & Ni, W. (2019) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2018.10.019 · Cited by 501
Security and Privacy Challenges of Large Language Models: A Survey
Das, B. C., Amini, M. H., & Wu, Y. (2025) · ACM Computing Surveys · doi:10.1145/3712001 · Cited by 445
Blockchain technology: A survey on applications and security privacy Challenges
Mohanta, B. K., Jena, D., Panda, S. S., & Sobhanayak, S. (2019) · Internet of Things · doi:10.1016/j.iot.2019.100107 · Cited by 394
Metadata
- Publisher
- ACM
- Published
- 2016-10-24
- OpenAlex
- W2914452207
- Cited by
- 818
- References
- 0
- Type
- paratext
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. https://app.cochat.ai/papers/10.1145/2976749
- The paper
- Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. (2016). https://doi.org/10.1145/2976749
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.