ICA3PP 2022
The 22nd International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP 2022)
Copenhagen, Denmark (Online)
| 10-12 October 2022
Keynote Speakers
Schahram Dustdar
Vienna University of Technology, Austria
Edge Intelligence - A Research Roadmap
As humans, things, software and AI continue to become the entangled fabric of distributed systems, systems engineers and researchers are facing novel challenges. In this talk, we analyze the role of IoT, Edge, and Cloud, as well as AI in the co-evolution of distributed systems for the new decade. We identify challenges and discuss a roadmap that these new distributed systems have to address. We take a closer look at how a cyber-physical fabric will be complemented by AI operationalization to enable seamless end-to-end distributed systems.
About Schahram Dustdar
Schahram Dustdar is Full Professor of Computer Science heading the Research Division of Distributed Systems at the TU Wien, Austria. He holds several honorary positions: Francqui Chair Professor at University of Namur, Belgium (2021-2022), University of California (USC) Los Angeles; Monash University in Melbourne, Shanghai University, Macquarie University in Sydney, University Pompeu Fabra, Barcelona, Spain. From Dec 2016 until Jan 2017 he was a Visiting Professor at the University of Sevilla, Spain and from January until June 2017 he was a Visiting Professor at UC Berkeley, USA.
Zheng Yan
Xidian University, China
Trust, Security and Privacy of 5G Positioning
The fifth-generation (5G) cellular network is expected to provide sub-meter positioning accuracy without draining the battery of user equipment. As a solution, ultra-dense network (UDN) deployment and network-based positioning were proposed. However, the openness of UDN and the vulnerability of network devices (e.g., access nodes) make such a positioning system easy to be attacked. Moreover, due to the sensitivity of positions, the privacy protection in both 5G positioning and its further application in location-based services (LBSs) has been paid special attention. However, existing work lacks deep investigation on the trust, security and privacy of 5G positioning and its related LBS provision. In this talk, I will report our research results on these issues, including a number of schemes to overcome jamming and collusion attacks in 5G positioning with positioning data truth discovery and potential attacker tracing, to protect privacy for both end users and LBS providers during LBS provision, and verifiable positioning with privacy preservation. Theoretical analysis and experimental tests show the effectiveness of our schemes and their potential in practical deployment.
About Zheng Yan
Zheng Yan is a Huashan distinguished professor in the School of Cyber Engineering, Xidian University, China and was a visiting professor and Finnish Academy Research Fellow at the Aalto University, Finland. She received the DSc in Technology from the Helsinki University of Technology, Finland. Before joining academia in 2011, she was a senior researcher at the Nokia Research Center, Helsinki, Finland, since 2000. She has published more than 320 peer-reviewed articles in the fields of trust, security, privacy, and data analytics. She is an inventor of over 100 patents, 80+ of them have been adopted in industry, some of them have been practically used. She is serving and served as an area/associate editor of Information Fusion, IEEE Internet of Things Journal, IEEE Network, Information Sciences, etc. She served as a general chair or program chair for over 30 international conferences. She is a founding steering committee co-chair of IEEE Blockchain conference. She recently received several awards, including 2021 N²Women Star in Computer Networking and Communications, Aalto ELEC Impact Award (2021), Nokia Distinguished Inventor Award (2020), the 2017 Best Journal Paper Award issued by IEEE Communication Society Technical Committee on Big Data, the best paper award of SpaCCS2019, and the Outstanding Associate Editor of 2017 and 2018 for IEEE Access. She is a Fellow of IET and a senior member of IEEE.
Muttukrishnan Rajarajan
City University of London, United Kingdom
Future of digital identity management in decentralised and distributed settings
Covid-19 has accelerated the digital transformation in all industry verticals. With the digital transformation there is an increasing need to have secure, trustworthy and reliable forms of digital identities. In addition the current data protection regulations expect the data owner to have total control in the way they share any personal data. Traditional identity management techniques have too much reliance on identity providers and were centralised and are not suitable for user-centric decentralised and distributed next generation internet. This talk will discuss the existing identity management architectures and provide a foundation based on the self-sovereign identity which can help to develop a sustainable, greener and distributed identity management framework.
About Muttukrishnan Rajarajan
Professor Rajarajan (Raj) is the founding Director of the Institute for Cyber Security at City University of London and the CEO of Citydefend Cybersecurity Solutions Limited. Raj’s expertise are in the areas of identity management, network security, data privacy and IoT Security. Raj has led several cyber security and privacy related research and commercialisation projects in the UK and internationally. He has published more than 350 conference and journal papers, four books and hold two patents in the area of cloud data privacy. He continues to work closely with many deep tech start-ups to innovate through digital transformation by applying blockchain, AI and cyber security in an integrated manner addressing many legal and regulatory data protection challenges. He is a Senior Member of the Institute of Electrical and Electronic Engineers and a full member of the Charted Institute of Information Security, UK.
Ding Wang
Nankai University, China
How to Attack and Generate Honeywords
In recent years, a large number of high-profile sites have leaked user password files. What's more, these leaks often take months or even years for websites to detect and remind users to update their passwords, but it's too late. For example, Yahoo leaked three billion user passwords and various personally identifiable information (e.g., birthday and name) in August 2013, yet only detected until October 2021. This provides attackers enough time to crack/exploit user passwords.
A promising approach, named honeywords, was first proposed by Juels and Rivest at CCS’13 to achieve timely password breach detection. We found that Juels-Rivest’s four primary honeyword-generation methods have serious security flaws, and such heuristic methods cannot be easily patched. We propose a series of theoretic models for characterizing the attacker’s best attack strategies in telling apart the real password from a set of honeywords. This resolves the open question of “given the attack capabilities, how does the attacker perform the optimal attack”. In turn, the attacker's best attacking strategies can be used to design best honeyword-generation methods, successfully getting rid of the heuristic design. This addresses the question of how best to attack, design and evaluate honeyword-generation methods. We believe this work provides both theoretical and methodological basis for timely detecting password-file leakage, pushing the honeyword research towards statistical rigor.
About Ding Wang
Biography: Ding Wang received his Ph.D. degree in Information Security at Peking University in 2017, and currently, he is a full professor at Nankai University. As the corresponding author or first author, he has published more than 80 papers at venues like IEEE S&P, ACM CCS, NDSS, USENIX Security, IEEE TDSC and IEEE TIFS. His research has been reported by over 200 medias like Daily Mail, Forbes, IEEE Spectrum and ACM Technews, appeared in the Elsevier 2017 "Article Selection Celebrating Computer Science Research in China", and resulted in the revision of part of the authentication guideline NIST SP800-63-2. He has been invited as a TPC member for over 40 international conferences such as ACM CCS, ACSAC, PETS, AsiaCCS, and ISC. He has been given the ACM China Doctoral Dissertation Award, CCF Doctoral Dissertation Award, the INSCRYPT 2018 Best Paper Award, and the Outstanding Youth Award of China Association for Cryptologic Research. His research interests focus on Identity Security, including password, multi-factor authentication and cryptographic protocols.
Song Guo
The Hong Kong Polytechnic University, Hong Kong SAR
Neural-enhanced Edge Perception Systems
As to paving the last mile of enabling intelligent applications on ubiquitous edge devices, it is necessary to deploy the entire lifecycle (ecosystem) of data generation, representation extraction and model consumption near the user side, with the support of diverse machine learning techniques. This emerging scenario promotes the rise of Neural-enhanced Edge Perception (NEP) system, which handles the end-to-end processing procedure by synthetically optimizing the key components of large-scale learning paradigm, hardware-adaptive neural architecture and communication-efficient cross-device interaction. As a fundamental infrastructure to bring edge intelligence to the production environment, the NEP system offers great advantages in terms of multi-modality knowledge fusion, lightweight on-device analysis, real-time streaming processing and perfect rate-distortion balance on distributed collaborative devices. This talk gives a comprehensive inspection of implementing high-performance NEP systems, covering the realistic design challenges, possible solutions and promising research opportunities
About Song Guo
Song Guo is a Full Professor at Department of Computing, The Hong Kong Polytechnic University. He also holds a Changjiang Chair Professorship awarded by the Ministry of Education of China. His research interests are mainly in federated learning, edge AI, mobile computing, and distributed systems. He published many papers in top venues with wide impact in these areas and was recognized as a Highly Cited Researcher (Clarivate Web of Science). Prof. Guo is the Editor-in-Chief of IEEE Open Journal of the Computer Society, and has been named on editorial board of IEEE TC, IEEE TPDS, IEEE TCC, IEEE TETC, ACM CSUR, etc. He is a Fellow of the Canadian Academy of Engineering, Fellow of the IEEE, and Member of Academia Europaea.
