Update Readme paper CCS 2023 (#27)

* Turning Privacy-preserving Mechanisms against Federated Learning
---------

Co-authored-by: marazzi <[email protected]>

README.md

@@ -81,7 +81,7 @@ We use another project to automatically track updates to FL papers, click on [FL
 | [KDD](https://dblp.uni-trier.de/search?q=federate%20venue%3AKDD%3A) | [23](https://dl.acm.org/doi/proceedings/10.1145/3580305), [22](https://kdd.org/kdd2022/paperRT.html), [21](https://kdd.org/kdd2021/accepted-papers/index), [20](https://www.kdd.org/kdd2020/accepted-papers) |                                                              |
 | [WSDM](https://dblp.uni-trier.de/search?q=federate%20venue%3AWSDM%3A) | [23](https://www.wsdm-conference.org/2023/program/accepted-papers), [22](https://www.wsdm-conference.org/2022/accepted-papers/), [21](https://www.wsdm-conference.org/2021/accepted-papers.php) | [19](https://www.wsdm-conference.org/2019/accepted-papers.php) |
 | [S&P](https://dblp.uni-trier.de/search?q=federated%20streamid%3Aconf%2Fsp%3A) | [23](https://sp2023.ieee-security.org/program-papers.html), [22](https://www.ieee-security.org/TC/SP2022/program-papers.html) | [19](https://www.ieee-security.org/TC/SP2019/program-papers.html) |
-| [CCS](https://dblp.uni-trier.de/search?q=federate%20venue%3ACCS%3A) | [22](https://www.sigsac.org/ccs/CCS2022/program/accepted-papers.html), [21](https://sigsac.org/ccs/CCS2021/accepted-papers.html), [19](https://www.sigsac.org/ccs/CCS2019/index.php/program/accepted-papers/) | [17](https://acmccs.github.io/papers/)                       |
+| [CCS](https://dblp.uni-trier.de/search?q=federate%20venue%3ACCS%3A) | [23](https://www.sigsac.org/ccs/CCS2023/program.html#acceptPaperTabContent), [22](https://www.sigsac.org/ccs/CCS2022/program/accepted-papers.html), [21](https://sigsac.org/ccs/CCS2021/accepted-papers.html), [19](https://www.sigsac.org/ccs/CCS2019/index.php/program/accepted-papers/) | [17](https://acmccs.github.io/papers/)                       |
 | [USENIX Security](https://dblp.uni-trier.de/search?q=federated%20streamid%3Aconf%2Fuss%3A) | [23](https://www.usenix.org/conference/usenixsecurity23/technical-sessions), [22](https://www.usenix.org/conference/usenixsecurity22/technical-sessions), [20](https://www.usenix.org/conference/usenixsecurity20/technical-sessions) | -                                                            |
 | [NDSS](https://dblp.uni-trier.de/search?q=federate%20venue%3ANDSS%3A) | [23](https://www.ndss-symposium.org/ndss2023/accepted-papers/), [22](https://www.ndss-symposium.org/ndss2022/accepted-papers/), [21](https://www.ndss-symposium.org/ndss2021/accepted-papers/) | -                                                            |
 | [CVPR](https://dblp.uni-trier.de/search?q=federate%20venue%3ACVPR%3A) | [23](https://openaccess.thecvf.com/CVPR2023?day=all), [22](https://openaccess.thecvf.com/CVPR2022), [21](https://openaccess.thecvf.com/CVPR2021?day=all) | -                                                            |
@@ -828,6 +828,7 @@ Federated Learning papers accepted by top Secure conference and journal, Includi
 | FedVal: Different good or different bad in federated learning | AI Sweden | USENIX Security | 2023 | [[PUB](https://www.usenix.org/conference/usenixsecurity23/presentation/valadi)] [[PDF](https://arxiv.org/abs/2306.04040)] [[CODE](https://github.com/viktorvaladi/fedval)] |
 | Securing Federated Sensitive Topic Classification against Poisoning Attacks | IMDEA Networks Institute | NDSS | 2023 | [[PUB](https://www.ndss-symposium.org/ndss-paper/securing-federated-sensitive-topic-classification-against-poisoning-attacks/)] [[PDF](https://arxiv.org/abs/2201.13086)] [[CODE](https://github.com/FRM-Sec/FRM)] |
 | PPA: Preference Profiling Attack Against Federated Learning | NJUST | NDSS | 2023 | [[PUB](https://www.ndss-symposium.org/ndss-paper/ppa-preference-profiling-attack-against-federated-learning/)] [[PDF](https://arxiv.org/abs/2202.04856)] |
+| Turning Privacy-preserving Mechanisms against Federated Learning | University of Pavia; TU Delft; University of Padua; Radboud University | CCS | 2023 | [[PUB](https://dl.acm.org/doi/10.1145/3576915.3623114)] [[PDF](https://arxiv.org/abs/2305.05355)] [[CODE](https://github.com/DCALab-UNIPV/Turning-Privacy-preserving-Mechanisms-against-Federated-Learning)] |
 | CERBERUS: Exploring Federated Prediction of Security Events | UCL London | CCS | 2022 | [[PUB](https://dl.acm.org/doi/10.1145/3548606.3560580)] [[PDF](https://arxiv.org/abs/2209.03050)] |
 | EIFFeL: Ensuring Integrity for Federated Learning | UW-Madison | CCS | 2022 | [[PUB](https://dl.acm.org/doi/10.1145/3548606.3560611)] [[PDF](https://arxiv.org/abs/2112.12727)] |
 | Eluding Secure Aggregation in Federated Learning via Model Inconsistency | SPRING Lab; EPFL | CCS | 2022 | [[PUB](https://dl.acm.org/doi/10.1145/3548606.3560557)] [[PDF](https://arxiv.org/abs/2111.07380)] [[CODE](https://github.com/pasquini-dario/eludingsecureaggregation)] |