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PRODID:-//CYS Research Seminar//https://cys-seminars.kcl.ac.uk///
BEGIN:VEVENT
SUMMARY:Measuring\, understanding\, and addressing image-based sexual abus
 e by Rebecca Umbach
DTSTART;TZID=Europe/London:20250114T140000
DTEND;TZID=Europe/London:20250114T150000
DTSTAMP:20260404T155626Z
UID:202501141400@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nThis seminar focuses on two separate studies on the topic 
 of image-based sexual abuse (IBSA). IBSA refers to the nonconsensual creat
 ing\, taking\, or sharing of intimate images\, including threats to share 
 intimate images. The first study investigated the prevalence of\, impacts 
 from\, and responses to IBSA generally\, in 10 countries. The second half 
 of the talk will cover the topic of prevalence\, experiences\, and attitud
 es towards synthetic IBSA\, sometimes known as deepfake pornography. We’
 ll conclude with a discussion of potential preventative interventions. \n\
 nDr. Rebecca Umbach is a staff UX researcher at Google. Her research focus
 es on the experiences of vulnerable populations subjected to online abuse\
 , with a particular emphasis on image-based sexual abuse and child sexual 
 abuse material. In her role within the Trust & Safety team at Google\, she
  uses her research to ensure that the voice of users\, advocacy groups\, a
 nd subject matter experts are heard by internal stakeholders\, such as pro
 duct teams and policy developers. Her work is cross-disciplinary\, spannin
 g criminology\, developmental psychology\, gender studies\, computer studi
 es\, and human-computer interaction\, and includes a long-standing collabo
 ration with Professor Nicola Henry at RMIT University. Prior to Google\, s
 he completed a PhD in Criminology at the University of Pennsylvania. 
LOCATION:Bush House (S)2.01
END:VEVENT
BEGIN:VEVENT
SUMMARY:Leveraging Sociotechnical Threat Modeling to Combat Online Abuse b
 y Miranda Wei
DTSTART;TZID=Europe/London:20241216T140000
DTEND;TZID=Europe/London:20241216T150000
DTSTAMP:20260404T155626Z
UID:202412161400@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nDigital technologies are not equally safe for everyone. Th
 e prevalence and severity of online abuse are on the rise\, from toxic con
 tent on social media to image-based sexual abuse\, as new technologies are
  weaponized by people who do harm. Further\, this abuse disproportionately
  harms people already marginalized in society\, creating unacceptable disp
 arities in safety and reinforcing oppression. Working at the intersection 
 of computer security and privacy (S&P) and human-computer interaction (HCI
 )\, I address online abuse as the next frontier of S&P challenges. In this
  talk\, I discuss my research (1) characterizing emerging S&P threats in d
 igital safety\, with particular attention to the technical and societal fa
 ctors at play\, (2) evaluating the existing support for online abuse\, tak
 ing an ecosystem-level perspective\, and (3) developing conceptual tools t
 hat bridge S&P and HCI towards societally informed S&P research. Taking a 
 sociotechnical approach\, I conclude by outlining how security and privacy
  can work towards a world where all people using technology feel safe and 
 connected.\n\nMiranda Wei is a PhD candidate at the University of Washingt
 on\, co-advised by Tadayoshi Kohno and Franziska Roesner. Her research foc
 uses on human-centered security and privacy\, including combating online a
 buse and supporting sociotechnical safety. She mainly publishes at USENIX 
 Security\, CHI\, and SOUPS\, and her work has been awarded a John Karat Us
 able Privacy and Security Student Research Award\, a Google PhD Fellowship
 \, and paper awards. Previously\, she received a B.A. from the University 
 of Chicago.
LOCATION:Bush House (SE) 1.03
END:VEVENT
BEGIN:VEVENT
SUMMARY:Simulating The Law In A Multiple Agent System by Matteo Cristani
DTSTART;TZID=Europe/London:20240716T160000
DTEND;TZID=Europe/London:20240716T170000
DTSTAMP:20260404T155626Z
UID:202407161600@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nUnderstanding the effects of a new regulation is quite a s
 ignificant quest that arises from the drafters while processing ideas to b
 ecome effective. In fact\, there are several effects that could be conside
 red\, including the legal impact\, namely the modification of the legal ba
 ckground that takes place whenever we introduce a new norm\, the economic 
 effects\, in particular the costs that are imposed by the law to organisms
  including the state\, companies and other bodies\, the social effects lik
 e the change of job statuses of citizens\, or citizenship statuses of work
 ers or other subjects. Understanding these aspects preliminarily is a good
  deem of many drafters. In this seminar we illustrate the research activit
 ies of the KREARTI research group in Verona\, where we aim at delivering a
  prototype of a system to assist the drafter de iure condendo into develop
 ing a new law\, so that she can value the future effects of the issue of t
 hat law\, before to have it in force. The aforementioned goal can be achie
 ved by means of a simulator\, that\, while observing an artificial society
 \, digital twin of the actual society on which the law takes place\, allow
 s to measure the consequences of the issue of a new law\, in order to assi
 st the drafter in the process of designing the norm itself. The system is 
 described and the research plan that shall bring us to the prototype is il
 lustrated and discussed.\n\n
LOCATION:Bush House BH(S)5.01
END:VEVENT
BEGIN:VEVENT
SUMMARY:Generic attacks based on functional graphs by Rachelle Heim Boissi
 er
DTSTART;TZID=Europe/London:20240603T150000
DTEND;TZID=Europe/London:20240603T160000
DTSTAMP:20260404T155626Z
UID:202406031500@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nThe purpose of this talk is to introduce generic attacks b
 ased on functional graphs. Over the past ten years\, the statistical prope
 rties of random functions have been particularly fruitful tool to mount ge
 neric attacks. Initially\, these attacks targeted iterated hash constructi
 ons and their combiners\, developing a wide array of methods based on inte
 rnal collisions and on the average behavior of iterated random functions. 
 More recently\, we (Gilbert et al.\, EUROCRYPT 2023) introduced a forgery 
 attack on so-called duplex-based Authenticated Encryption modes which is b
 ased on exceptional random functions\, i.e.\, functions whose graph admits
  a large component with an exceptionally small cycle. We have since then i
 mproved this attack Bonnetain et al.\, CRYPTO 2024) using so-called nested
  exceptional functions. We also improved several attacks against hash comb
 iners using exceptional random functions. This talk will present a variety
  of generic attacks based on functional graphs against hash functions\, ha
 sh-based MACs and AEAD modes. \n\nPhD student at Université Versailles Sa
 int-Quentin-en-Yvelines working under the supervision of Christina Boura\,
  Henri Gilbert and Yann Rotella.
LOCATION:Bush House (S) 5.01 - CUSP Room
END:VEVENT
BEGIN:VEVENT
SUMMARY:A Human-centered Approach to Develop AI-based Decision-Support Sys
 tems by Nadin Kokciyan
DTSTART;TZID=Europe/London:20240524T110000
DTEND;TZID=Europe/London:20240524T120000
DTSTAMP:20260404T155626Z
UID:202405241100@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nThe talk introduces the research we do in CHAI Lab (Human-
 centered AI Lab) in the School of Informatics\, University of Edinburgh. I
  will introduce three ongoing projects\, while the main focus will be on t
 he first one: 1. "A Collaborative Human-AI Approach to Mitigate Large-Scal
 e Phishing Attacks"\, where we aim to develop AI-based tools to mitigate p
 hishing attacks\, 2. "Uncovering implicit inferences for improved relation
 al argument mining"\, where we aim to analyse unstructured text to discove
 r meaningful arguments and connections between them\, 3. "Enabling Answera
 bility in Sociotechnical Systems"\, where we develop a mediator agent tool
  to facilitate dialogues between organizations and users. \n\nNadin is a L
 ecturer in Artificial Intelligence in the School of Informatics at Univers
 ity of Edinburgh\; and a Senior Research Affiliate at the Centre for Techn
 omoral Futures\, Edinburgh Futures Institute. Her research interests inclu
 de human-centered AI\, Privacy\, Argument Mining\, Responsible AI and AI E
 thics. She received her PhD from Bogazici University in 2017\, and held a 
 postdoc position at King's College London prior to joining University of E
 dinburgh. Nadin regularly serves on the program committees for leading AI 
 conferences such as AAMAS\, IJCAI\, AAAI and ECAI. In 2021\, she was also 
 a guest editor for Sociotechnical Perspectives of AI Ethics and Accountabi
 lity in IEEE Internet Computing.
LOCATION:Bush House (S)2.05
END:VEVENT
BEGIN:VEVENT
SUMMARY:Securing the Future: IoT Cyber Security in Business Integrations  
 by Belal Asad
DTSTART;TZID=Europe/London:20240415T150000
DTEND;TZID=Europe/London:20240415T160000
DTSTAMP:20260404T155626Z
UID:202404151500@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nThe Internet of Things (IoT) has become an integral part o
 f our daily lives\, revolutionising various industries with its innovative
  applications. IoT devices\, such as smart appliances\, security systems\,
  and home hubs\, have made our lives more convenient and efficient. They a
 re used in sectors including healthcare\, agriculture\, and defence\, prov
 iding benefits like enhanced efficiency\, cost savings\, and data-driven d
 ecision-making.\n\nIn the context of business integration\, IoT cyber secu
 rity is critical to the success and security of the integration. Cyber sec
 urity concerns in any integration can be complex\, particularly due to vul
 nerabilities and breaches that may arise from non-compatible systems and p
 olicies. These risks include due diligence\, compliance\, managing IoT sys
 tems\, finance-related risks\, and asset-related risks.\n\nSeveral high-pr
 ofile integration transactions have suffered due to cyber security issues.
  For instance\, Experian's acquisition of Court Ventures and Verizon's pur
 chase of Yahoo! were impacted by cyber security issues that surfaced after
  the transactions were announced. Furthermore\, several IoT providers have
  been through critical cyber security breaches\, which can significantly a
 ffect any business. \n\n\nAs an Assistant Manager at Evelyn Partners\, I s
 tand at the vanguard of our cyber security initiatives\, offering expert c
 onsulting services that ensure the integrity of our clients' digital asset
 s. My leadership in projects spanning IoT security\, security analysis\, a
 nd risk management has been pivotal in fortifying our cyber defences.\nCon
 currently\, I am honing my expertise through a PhD in advanced cyber secur
 ity and AI at the University of Southampton. This scholarly pursuit not on
 ly ignites my passion for the field but also enriches the strategies I imp
 lement at Evelyn Partners. I am privileged to hold esteemed certifications
  such as SC-300\, SC-100\, SC-200\, and CEH\, underscoring my dedication t
 o professional excellence.\nAs a published author and certified trainer\, 
 I am fervently committed to disseminating knowledge and nurturing a cultur
 e of cyber security awareness. I eagerly anticipate engaging in a dialogue
  about the multifaceted nature of cyber threats and sharing actionable ins
 ights on how we can continue to excel in our cyber security endeavours\,\n
 \nOh\, and did I mention my diverse cultural heritage? It's an integral pa
 rt of who I am\, infusing a touch of global perspective and a dash of char
 m into my work. Join me as we explore the cutting-edge strategies that wil
 l keep us at the forefront of cyber security.
LOCATION:Bush House (S) 5.01 - CUSP Room
END:VEVENT
BEGIN:VEVENT
SUMMARY:Modular Design of Secure Group Messaging Protocols and the Securit
 y of MLS by Yiannis Tselekounis
DTSTART;TZID=Europe/London:20240318T150000
DTEND;TZID=Europe/London:20240318T160000
DTSTAMP:20260404T155626Z
UID:202403181500@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nEnd-to-end encrypted secure messaging is a widely used cla
 ss of cryptographic protocols enabling clients to communicate securely and
  asynchronously over untrusted network and server infrastructure. The term
  “secure” encompasses several security guarantees\, including message 
 authenticity and a robust level of message confidentiality\, captured by t
 he notions of post-compromise security (PCS) and forward secrecy (FS). Int
 uitively\, these notions require that current messages remain secure again
 st any adversary that controls all network traffic and can leak all partic
 ipants’ local states both in the past (PCS) and in the future (FS).\n\nA
  new class of messaging applications are based on underlying Continuous Gr
 oup Key Agreement (CGKA) protocols\, including the IETF’s upcoming Messa
 ging Layer Security (MLS) standard. Most of the functionality\, security a
 nd efficiency properties of these protocols is inherited directly from the
 ir underlying CGKAs\, rendering CGKA a growing subject of cryptographic re
 search in recent years. In this work we analyse the security and propose i
 mprovements for the CGKA protocol proposed by the MLS standard.    \n\nYia
 nnis Tselekounis is a Lecturer at the Department of Information Security a
 t Royal Holloway\, University of London. His research focuses on applied a
 nd theoretical aspects of cryptography\, including the security of cryptog
 raphic protocols\, leakage/tamper-resilient cryptography\, and blockchains
 . Before joining RHUL\, Yiannis was a postdoctoral researcher at Carnegie 
 Mellon University and Faculty Fellow at New York University. He obtained h
 is PhD degree from the Department of Informatics of the University of Edin
 burgh.
LOCATION:Bush House (S) 5.01 - CUSP Room
END:VEVENT
BEGIN:VEVENT
SUMMARY:Lattice Gaussian Sampling Using Markov Chain Monte Carlo (MCMC)\, 
 With Applications to Trapdoor Sampling by Cong Ling
DTSTART;TZID=Europe/London:20240311T150000
DTEND;TZID=Europe/London:20240311T160000
DTSTAMP:20260404T155626Z
UID:202403111500@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nSampling from a lattice Gaussian distribution has emerged 
 as a common theme in various areas such as coding and cryptography. The de
  facto sampling algorithm—Klein’s algorithm yields a distribution clos
 e to the lattice Gaussian only if the standard deviation is sufficiently l
 arge. This talk is concerned with a new method based on Markov chain Monte
  Carlo (MCMC) for lattice Gaussian sampling\, which converges to the targe
 t lattice Gaussian distribution for any value of the standard deviation. A
  number of algorithms will be presented\, such as Gibbs and Metropolis-Has
 tings. A problem of central importance is to determine the mixing time. It
  is proven that some of these Markov chains are geometrically ergodic\, na
 mely\, the sampling algorithms converge to the stationary distribution exp
 onentially fast. Finally\, an application to trapdoor sampling based on NT
 RU is demonstrated\, potentially outperforming the FALCON signature scheme
 .\n\nCong Ling is currently a Reader (equivalent to Professor/Associate Pr
 ofessor) in the Electrical and Electronic Engineering Department at Imperi
 al College London. His research interest is focused on lattices and their 
 applications to coding and cryptography.
LOCATION:Bush House (S) 5.01 - CUSP Room
END:VEVENT
BEGIN:VEVENT
SUMMARY:Understanding the Security Limitations of Encrypted Cloud Data by 
 Evangelia Anna (Lilika) Markatou 
DTSTART;TZID=Europe/London:20240226T150000
DTEND;TZID=Europe/London:20240226T160000
DTSTAMP:20260404T155626Z
UID:202402261500@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nIn order to protect data in the cloud\, a database should 
 be stored in encrypted form and queries executed without prior decryption.
  Searchable encryption schemes are being deployed in real-world applicatio
 ns to achieve this objective. They balance security and performance by pro
 viding efficient algorithms that\, however\, leak some information about t
 he data. This talk considers range queries on encrypted multidimensional d
 ata and explores the feasibility of reconstructing the plaintext data by e
 xploiting the information leakage from such queries. We analyze common typ
 es of leakage\, like access pattern\, i.e.\, individually encrypted record
 s in query responses\, and volume pattern\, i.e.\, encrypted entire query 
 responses. We also develop efficient searchable encryption schemes and ass
 ess both theoretically and experimentally their vulnerability to reconstru
 ction attacks that exploit their leakage. By furthering the understanding 
 of the security limitations of encrypted cloud data\, our work enables dev
 elopers to make more informed choices when deploying searchable encryption
  solutions.\n\nEvangelia Anna (Lilika) Markatou is an assistant professor 
 of cybersecurity at TU Delft. She received her PhD from Brown University\,
  advised by Roberto Tamassia. She graduated with a Bachelor's degree in El
 ectrical Engineering and Computer Science in 2016 from the Massachusetts I
 nstitute of Technology (MIT). In 2018\, she received a Master of Engineeri
 ng from MIT advised by Nancy Lynch. In her research\, she aims to develop 
 secure and private protocols that enable users to utilize cloud computing 
 resources without sacrificing their data.
LOCATION:Bush House (S) 5.01 - CUSP Room
END:VEVENT
BEGIN:VEVENT
SUMMARY:Concrete Security for Succinct Arguments from Vector Commitment Sc
 hemes by Ziyi  Guan
DTSTART;TZID=Europe/London:20240207T160000
DTEND;TZID=Europe/London:20240207T170000
DTSTAMP:20260404T155626Z
UID:202402071600@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nWe study the concrete security for succinct interactive ar
 guments realized from probabilistic proofs and vector commitment schemes i
 n the standard model. \n\nWe establish the tightest bound on the security 
 of Kilian’s succinct interactive argument based on probabilistically che
 ckable proofs (PCPs). Then we show tight bounds for succint interactive ar
 guments based on public-coin interactive oracle proofs (IOPs)\, for which 
 no previous analysis is known. Finally we conclude that this VC-based appr
 oach is secure when realized with any public-query IOP (a special type of 
 private-coin IOP) that admits a random continuation sampler.\n\nBased on h
 ttps://eprint.iacr.org/2023/1737.pdf\, joint work with Alessandro Chiesa\,
  Marcel Dall’Agnol\, and Nick Spooner. \n\n\nZiyi Guan is a third-year P
 hD student at EPFL\, supervised by Alessandro Chiesa and Mika Göös. She 
 is interested in theoretical computer science\, in particular complexity t
 heory and cryptography. 
LOCATION:Bush House (S)2.05 
END:VEVENT
BEGIN:VEVENT
SUMMARY:When cybersecurity meets psychology: Toward usable online scam det
 ection by Sarah  Zheng 
DTSTART;TZID=Europe/London:20240129T140000
DTEND;TZID=Europe/London:20240129T150000
DTSTAMP:20260404T155626Z
UID:202401291400@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nOnline scams are taking an emotional and financial toll on
  people around the globe. Artificial intelligence (AI) is already being us
 ed to create targeted campaigns and humans are not able to distinguish AI-
 generated from "human" content. Evidently\, technical systems alone cannot
  prevent people from falling for online scams. We also need to update the 
 human computer user. \nI will present three studies from my PhD that exami
 ned novel paradigms to improve people's ability to detect phishing e-mails
  - a quintessential type of online scam. The first study tested what psych
 ological and demographic factors relate to people's likelihood to fall for
  phishing e-mails\, using an experimental setting with behavioural trackin
 g and a representative participants sample. The result gave rise to design
 ing three e-mail security tools to scan e-mails in a usable fashion\, whic
 h we evaluated in the second study. Third\, I used the psychological conce
 pt of "self-projection" to design and test an adversarial phishing detecti
 on training. Indeed\, engaging people with how phishing e-mails are create
 d can improve their detection ability. \nI will end the talk with a reflec
 tion on the implications of our findings and future directions for researc
 h.\n\nSarah recently completed her PhD in Security & Crime Science at UCL 
 with a full scholarship from the Dawes Centre for Future Crime. She has a 
 background in psychology and neuroscience\, and four years of experience i
 n AI and data science consulting. These roles include developing machine l
 earning models for credit card fraud detection and working on AI use cases
  for the Dutch MoD. She started programming websites in primary school\, b
 ut a fascination with how the human mind works made her a psychological re
 searcher in the first place. With her work\, she aims to bridge the gap be
 tween cognitive and computer science.
LOCATION:Bush House (S) 5.01 - CUSP Room
END:VEVENT
BEGIN:VEVENT
SUMMARY:Obfuscation from Lattice-Based Equivocal Assumption by Ivy K. Y. W
 oo
DTSTART;TZID=Europe/London:20231218T160000
DTEND;TZID=Europe/London:20231218T170000
DTSTAMP:20260404T155626Z
UID:202312181600@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nIndistinguishability obfuscation allows one to turn a prog
 ram unintelligible\, without altering its functionality. Because it captur
 es the power of most known cryptographic primitives and enables new ones\,
  obfuscation is often referred to as being crypto-complete. In this work w
 e investigate constructions of indistinguishability obfuscation\, whose se
 curity can be reduced from potentially hard problems over lattices. Compar
 ed to other candidates\, a purely lattice-based obfuscator has the advanta
 ge of being based on a single source of hardness and being plausibly post-
 quantum\, enabling many applications in quantum cryptography.\n\nWe propos
 e a new construction of lattice-based obfuscation whose security relies on
  an instance-independent assumption over lattices called the Equivocal Lea
 rning with Errors (LWE) assumption\, which is closely related to the recen
 tly introduced Evasive LWE assumption. Our main technical ingredient is a 
 new statistical trapdoor algorithm for equivocating LWE secrets over latti
 ces with exceptionally short vectors\, which may be of independent interes
 t.\n\nIvy K. Y. Woo is a PhD student in cryptography at Aalto University\,
  Finland since 2022. Her research focuses on cryptographic constructions f
 rom lattices. Recently she is working on advanced encryption such as attri
 bute-based encryption. More generally\, she is interested in constructing 
 cryptographic objects from an algebraic perspective.
LOCATION:Bush House (S) 5.01 - CUSP Room
END:VEVENT
BEGIN:VEVENT
SUMMARY:Three Years of Shouting at Computers: Security and Privacy for Spe
 ech Interfaces by Will Seymour
DTSTART;TZID=Europe/London:20231211T160000
DTEND;TZID=Europe/London:20231211T170000
DTSTAMP:20260404T155626Z
UID:202312111600@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nIt can feel like every new consumer device comes with some
  kind of voice integration. While this is often a win for usability\, free
 ing up our hands and eyes to do other tasks\, there's also something inher
 ently creepy/unsettling about devices that speak and listen to us.\n\nIn t
 his talk I'll be covering a range of exploratory work on privacy and secur
 ity issues with conversational devices\, how these are intensified by the 
 way that computer speech is processed in the brain\, and how we might be a
 ble to navigate a path out of the mess we've gotten ourselves into.\n\n\nW
 illiam Seymour is a Lecturer in Cybersecurity and member of the Cyber Secu
 rity Group in the Department of Informatics at King’s College London. Be
 fore coming to King’s as a postdoctoral researcher\, he obtained a DPhil
  in Cybersecurity from the University of Oxford and an MEng in Computer Sc
 ience from the University of Warwick.\n\nWilliam conducts interdisciplinar
 y work at the intersection of security\, privacy\, HCI\, ethics\, and law 
 using a combination of computational and social science research methods. 
 His work explores people’s concerns about using AI systems\, what values
  those systems should embody\, and how they can better meet the needs of t
 he people who use them. He has worked with a wide range of public sector a
 nd industry partners including Microsoft\, BRE Group\, and the Information
  Commissioner’s Office.
LOCATION:Bush House (S) 5.01 - CUSP Room
END:VEVENT
BEGIN:VEVENT
SUMMARY:Lattice-Based Polynomial Commitments: Towards Asymptotic and Concr
 ete Efficiency by Ngoc Khanh Nguyen
DTSTART;TZID=Europe/London:20231204T160000
DTEND;TZID=Europe/London:20231204T170000
DTSTAMP:20260404T155626Z
UID:202312041600@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nPolynomial commitments schemes are a powerful tool that en
 ables one party to commit to a polynomial p of degree d\, and prove that t
 he committed function evaluates to a certain value z at a specified point 
 u\, i.e. p(u) = z\, without revealing any additional information about the
  polynomial. Recently\, polynomial commitments have been extensively used 
 as a cryptographic building block to transform polynomial interactive orac
 le proofs (PIOPs) into efficient succinct arguments.\n\nIn this talk\, we 
 present new constructions of lattice-based polynomial commitments that ach
 ieve succinct proof size and verification time in the degree d of the poly
 nomial. Extractability of the schemes holds in the random oracle model und
 er the standard Module-SIS assumption. Concretely\, the most optimized ver
 sion achieves proof in the order of 600KB for d = 2^20\, which becomes com
 petitive with the hash-based FRI commitment.\n\nNgoc Khanh Nguyen is a lec
 turer at King's College London. His current topics of interests are (but n
 ot limited to) efficient lattice-based constructions and efficient post-qu
 antum zero-knowledge proofs.\n\nPreviously\, Khanh was a postdoctoral rese
 archer at EPFL\, hosted by Prof. Alessandro Chiesa. He obtained his PhD de
 gree at ETH Zurich and IBM Research Europe - Zurich\, supervised by Dr Vad
 im Lyubashevsky and Prof. Dennis Hofheinz. Before that\, he did his underg
 raduate and master studies at the University of Bristol\, UK.
LOCATION:Bush House (S) 5.01 - CUSP Room
END:VEVENT
BEGIN:VEVENT
SUMMARY:Protecting Humans from Misused Generative AI by Shawn Shan
DTSTART;TZID=Europe/London:20231121T153000
DTEND;TZID=Europe/London:20231121T163000
DTSTAMP:20260404T155626Z
UID:202311211530@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:In-person seminar\n\nGenerative AI is revolutionizing the art 
 industry by training models on billions of copyrighted artwork without con
 sent\, compensation or credit for the original artists. AI's ability to co
 py artists' styles from their copyrighted work is disrupting existing arti
 sts' income and livelihood\, and discouraging aspiring art students from p
 ursuing their dreams. In this talk\, I will present our work “Glaze” t
 hat protects human artists from this threat by exploiting fundamental weak
 nesses in generative models. I will share some of the ups and downs of imp
 lementing and deploying an adversarial ML tool to a global user base\, and
  reflect on mistakes and lessons learned. \n\nShawn Shan is a PhD candidat
 e in Computer Science at University of Chicago\, advised by Ben Zhao and H
 eather Zheng. His research focuses on developing technical solutions to pr
 otect people from malicious uses of AI. His research has received the Best
  Paper and Internet Defense Award in USENIX\, and covered by media outlets
  such as the New York Times\, BBC\, Scientific American\, and MIT Tech Rev
 iew.
LOCATION:STRAND Building - Room S3.05
END:VEVENT
BEGIN:VEVENT
SUMMARY:How to Verify Privacy Automatically by Laouen Fernet
DTSTART;TZID=Europe/London:20231113T160000
DTEND;TZID=Europe/London:20231113T170000
DTSTAMP:20260404T155626Z
UID:202311131600@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nPrivacy is relevant for virtually any application handling
  data. Therefore\,\nstudying privacy is critical\, especially considering 
 the increasing\ndigitalization of applications. In order to protect sensit
 ive information\, it is\ncrucial to have strong guarantees that systems re
 spect privacy. New digital\napplications need to be secured and protected 
 against any misuse\, such as\nsurveillance\, profiling\, stalking\, or coe
 rcion (e.g.\, a doctor should be able to\nmake prescriptions without press
 ure from pharmaceutical companies).\n\nOne way to formally specify how sys
 tems and applications work is to model them\nwith security protocols. They
  are protocols defining how messages are exchanged\nbetween several partie
 s\, often relying on cryptographic operations. In this\ntalk\, I will intr
 oduce the notion of $(\\alpha\, \\beta)$-privacy in security\nprotocols an
 d illustrate the problem with examples. I will present recent\nresearch ab
 out automated verification of privacy and mention important\nchallenges.\n
 \nI am a PhD student under the supervision of Sebastian Mödersheim and Lu
 ca\nViganò. I am working in the Software Systems Engineering section at D
 TU Compute\,\nthe department of Applied Mathematics and Computer Science o
 f the Technical\nUniversity of Denmark. Previously I completed there an MS
 c in Computer Science\nand Engineering with a focus on safety and security
  by design.\n\nMy research topic is the study of privacy using formal meth
 ods and logic\, and in\nparticular automated verification techniques. The 
 goal is to better understand\nthe actual privacy guarantees of digital app
 lications so that we can develop\ntechnology respecting peoples' rights to
  privacy.
LOCATION:Bush House (S) 5.01 - CUSP Room
END:VEVENT
BEGIN:VEVENT
SUMMARY:Drift Forensics of Malware Classifiers by Theo Chow
DTSTART;TZID=Europe/London:20231106T160000
DTEND;TZID=Europe/London:20231106T170000
DTSTAMP:20260404T155626Z
UID:202311061600@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:This seminar will be a dry-run of the talk to be given at the 
 AISec workshop 2023\, co-located with ACM CCS. \n\nThe widespread occurren
 ce of mobile malware still poses a significant security threat to billions
  of smartphone users.\nTo counter this threat\, several machine learning-b
 ased detection systems have been proposed within the last decade.\nThese m
 ethods have achieved impressive detection results in many settings\, witho
 ut requiring the manual crafting of signatures.\nUnfortunately\, recent re
 search has demonstrated that these systems often suffer from significant p
 erformance drops over time if the underlying distribution changes---a phen
 omenon referred to as concept drift.\nSo far\, however\, it is still an op
 en question which main factors cause the drift in the data and\, in turn\,
  the drop in performance of current detection systems.\n\nTo address this 
 question\, we present a framework for the in-depth analysis of dataset aff
 ected by concept drift. \nThe framework allows gaining a better understand
 ing of the root causes of concept drift\, a fundamental stepping stone for
  building robust detection methods.\nTo examine the effectiveness of our f
 ramework\, we use it to analyze a commonly used dataset for Android malwar
 e detection as a first case study.\nOur analysis yields two key insights i
 nto the drift that affects several state-of-the-art methods. \nFirst\, we 
 find that most of the performance drop can be explained by the rise of two
  malware families in the dataset.\nSecond\, we can determine how the evolu
 tion of certain malware families and even goodware samples affects the cla
 ssifier's performance. \nOur findings provide a novel perspective on previ
 ous evaluations conducted using this dataset and\, at the same time\, show
  the potential of the proposed framework to obtain a better understanding 
 of concept drift in mobile malware and related settings.\n\nTheo Chow is a
  dedicated PhD candidate under the guidance of Professor Fabio Pierazzi. H
 e is an active member of the Cyber Security Group within the Department of
  Informatics at King’s College London. Prior to embarking on his doctora
 l journey at King's\, Theo completed his Master of Science (MSc) in Advanc
 ed Microelectronics and Computer Systems at the University of Bristol\, fo
 llowing a Bachelor of Engineering (BEng) in Electronics Engineering at the
  University of Warwick.\n\nTheo's research passion lies at the intersectio
 n of eXplainable AI (XAI)\, Cybersecurity\, Concept Drift\, and Machine Le
 arning Model Robustness. His work addresses the growing concerns surroundi
 ng the reliability of Machine Learning models and delves into how XAI can 
 offer solutions. He is dedicated to demystifying the 'black box' nature of
  these models\, ultimately empowering practitioners to understand and trus
 t these increasingly influential systems.
LOCATION:Bush House (S) 5.01 - CUSP Room
END:VEVENT
BEGIN:VEVENT
SUMMARY:Formally Verifying CRYSTALS-Kyber by Katharina Katharina
DTSTART;TZID=Europe/London:20230724T130000
DTEND;TZID=Europe/London:20230724T140000
DTSTAMP:20260404T155626Z
UID:202307241300@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\n\n\n
LOCATION:Online
END:VEVENT
BEGIN:VEVENT
SUMMARY:Studying Information Weaponization on the Web by Emiliano De Crist
 ofaro
DTSTART;TZID=Europe/London:20230622T160000
DTEND;TZID=Europe/London:20230622T170000
DTSTAMP:20260404T155626Z
UID:202306221600@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nOver the past 20 years or so\, the world has seen an explo
 sion of data. While in the past\, controlled experiments\, surveys\, or co
 mpilation of high-level statistics allowed us to gain insights into the pr
 oblems we explored\, the Web has brought about a host of new challenges fo
 r researchers hoping to gain an understanding of modern socio-technical be
 havior. First\, even discovering appropriate data sources is not a straigh
 tforward task. Next\, although the Web enables us to collect highly detail
 ed digital information\, there are issues of availability and ephemerality
 : simply put\, researchers have no control over what data a 3rd party plat
 form collects and exposes\, and more specifically\, no control over how lo
 ng that data will remain available. Third\, the massive scale and multiple
  data formats require creative analysis execution. Finally\, modern socio-
 technical problems\, while related to typical social problems\, are fundam
 entally different and\, in addition to posing a research challenge\, can a
 lso disrupt researchers' personal lives.\n\nIn this talk\, I will discuss 
 how our work has overcome the above challenges. Using concrete examples fr
 om our research\, I will delve into some of the unique datasets and analys
 es we have performed\, focusing on emerging issues like hate speech\, coor
 dinated harassment campaigns\, and deplatforming\, as well as modeling the
  influence that Web communities have on the spread of disinformation\, wea
 ponized memes\, etc. Finally\, I will discuss how we can design proactive 
 systems to anticipate and predict online abuse and\, if time permits\, how
  the "fringe" information ecosystem exposes researchers to attacks by the 
 very actors they study.\n\nEmiliano De Cristofaro is Professor of Security
  and Privacy Enhancing Technologies at University College London (UCL). He
  received a PhD in 2011 from the University of California\, Irvine\, advis
 ed by Gene Tsudik. Before joining UCL in 2013\, Emiliano was Research Scie
 ntist at Xerox PARC. His research background includes privacy-oriented (ap
 plied) cryptography and systems security\; currently\, he focuses on priva
 cy in machine learning and cybersafety. Emiliano has co-chaired the PETS S
 ymposium and the security/privacy tracks at WWW and ACM CCS. With his co-a
 uthors\, he received distinguished paper/honorable mention awards from ACM
  CCS\, NDSS\, ACM IMC\, and ACM CSCW. Ostensibly\, he only refers to himse
 lf in the third person when writing seminar bios.
LOCATION:Bush House (S)2.03
END:VEVENT
BEGIN:VEVENT
SUMMARY:Interrogating Slack & Discord Chatbots to Uncover S&P Issues by Gu
 illermo Suarez-Tangil
DTSTART;TZID=Europe/London:20230327T160000
DTEND;TZID=Europe/London:20230327T170000
DTSTAMP:20260404T155626Z
UID:202303271600@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nThis talk will offer an overview of two innovative methodo
 logies designed to understand what can be done when malicious or potential
 ly unwanted software runs in the cloud. In the absence of a binary to be a
 nalyzed\, traditional static and dynamic analysis becomes useless. In part
 icular\, I will present our latest IMC’22 paper focusing on the Slack ch
 atbot ecosystem. \n\n\nGuillermo Suarez-Tangil is an Assistant Professor a
 t IMDEA Networks Institute and a Ramon Y Cajal Fellow. His research focuse
 s on systems security and malware analysis and detection. In particular\, 
 his area of expertise lies in the study of smart malware\, ranging from th
 e detection of advanced obfuscated malware to the automated analysis of ta
 rgeted malware. Guillermo also holds a position at King’s College London
  (KCL) as an Assistant Professor\, where he has been part of the Cybersecu
 rity Group since 2018. Before joining KCL\, he was a Senior Research Assoc
 iate at University College London (UCL) where he explored the use of progr
 am analysis to study malware. He has also been actively involved in other 
 research directions aiming at detecting and preventing Mass-Marketing Frau
 d and security and privacy issues on the social web. \n
LOCATION:BH(S)2.07
END:VEVENT
BEGIN:VEVENT
SUMMARY:ADAPT it! APT Attribution for Heterogeneous Files by Aakanksha Sah
 a
DTSTART;TZID=Europe/London:20230323T150000
DTEND;TZID=Europe/London:20230323T160000
DTSTAMP:20260404T155626Z
UID:202303231500@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nIn recent years\, we have witnessed a surge in the growth 
 of technically sophisticated Advanced Persistent Threat (APT) attacks and 
 their impact on industry\, governance\, and democracy. APT attacks are cha
 racterized by long-running complex attack chains that utilize heterogeneou
 s files and sophisticated tactics\, techniques\, and procedures (TTPs). On
 e of the most critical questions in this context is identifying the threat
  group behind the attack\, which is known as APT attribution. Group attrib
 ution is helpful for defenders as it helps them prioritize their response 
 and remediation efforts.\nIn this talk\, we introduce ADAPT\, a static mac
 hine learning-based approach to APT attribution\, which automates and stan
 dardizes the attribution process across heterogeneous file types. We prese
 nt the findings and insights obtained from applying ADAPT to a newly craft
 ed APT dataset consisting of 5\,989 real-world APT samples from approximat
 ely 162 threat groups\, spanning from May 2006 to October 2021.\n\n\nAakan
 ksha is a second-year doctoral student at TU Wien’s Security and Privacy
  Research Unit. Before joining TU Wien\, Aakanksha did her Master’s degr
 ee in Computer Science from the University of Utah\, focusing on Cybersecu
 rity. Following that\, she worked as a Security Software Engineer at Micro
 soft\, Redmond\, USA. While working at Microsoft\, Aakanksha often engaged
  in purple-team activities where they reverse-engineered malware binaries 
 and emulated external adversaries (APT groups)\, such as APT29 and Fin7\, 
 to improve security detection and response. The experience drew her to the
  research area of malware analysis and attribution of advanced adversary a
 ttacks.\n
LOCATION:BH(S)2.05
END:VEVENT
BEGIN:VEVENT
SUMMARY:Information Flow Control in Object-Oriented Programs by Narges Kha
 kpour
DTSTART;TZID=Europe/London:20230308T160000
DTEND;TZID=Europe/London:20230308T170000
DTSTAMP:20260404T155626Z
UID:202303081600@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\n\n\n
LOCATION:BH(SE)2.11
END:VEVENT
BEGIN:VEVENT
SUMMARY:Dos and Don’ts of Machine Learning in Computer Security by Danie
 l Arp
DTSTART;TZID=Europe/London:20230224T160000
DTEND;TZID=Europe/London:20230224T170000
DTSTAMP:20260404T155626Z
UID:202302241600@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nWith the growing processing power of computing systems and
  the increasing availability of massive datasets\, machine learning algori
 thms have led to major breakthroughs in many different areas. Despite grea
 t potential\, machine learning in security is prone to subtle pitfalls tha
 t undermine its performance and render learning-based systems potentially 
 unsuitable for security tasks and practical deployment. In the talk\, we l
 ook at this problem with critical eyes. First\, we identify common pitfall
 s in the design\, implementation\, and evaluation of learning-based securi
 ty systems. We conduct a study of 30 papers from top-tier security confere
 nces within the past ten years\, confirming that these pitfalls are widesp
 read in the current security literature. In an empirical analysis\, we fur
 ther demonstrate how individual pitfalls can lead to unrealistic performan
 ce and interpretations\, obstructing the understanding of the security pro
 blem at hand. As a remedy\, we propose actionable recommendations to suppo
 rt researchers in avoiding or mitigating the pitfalls where possible. Furt
 hermore\, we identify open problems when applying machine learning in secu
 rity and provide directions for further research. \n\n\n
LOCATION:BH(SE)2.11
END:VEVENT
BEGIN:VEVENT
SUMMARY:Practically-exploitable Cryptographic Vulnerabilities in Matrix by
  Martin Albrecht
DTSTART;TZID=Europe/London:20230125T160000
DTEND;TZID=Europe/London:20230125T170000
DTSTAMP:20260404T155626Z
UID:202301251600@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nWe report several practically-exploitable cryptographic vu
 lnerabilities in the Matrix standard for federated real-time communication
  and its flagship client and prototype implementation\, Element. These\, 
 together\, invalidate the confidentiality and authentication guarantees c
 laimed by Matrix against a malicious server. This is despite Matrix’ cry
 ptographic routines being constructed from well-known and studied cryptogr
 aphic building blocks. On the one hand\, one of our attacks proceeds by ch
 aining three attacks to achieve a full authentication and confidentiality
  break. On the other hand\, the vulnerabilities we exploit differ in their
  nature (insecure by design\, protocol confusion\, lack of domain separati
 on\, implementation bugs) and are distributed broadly across the different
  subprotocols and libraries that make up the cryptographic core of Matrix.
  Together\, these vulnerabilities highlight the need for a systematic and 
 formal analysis of the cryptography in the Matrix standard. \n\n\nMartin w
 orks across the field of cryptography and recently joined King’s College
  London as a professor. \n
LOCATION:BH(S)5.01
END:VEVENT
BEGIN:VEVENT
SUMMARY:On the Security of Machine Learning by Erwin Quiring
DTSTART;TZID=Europe/London:20221114T170000
DTEND;TZID=Europe/London:20221114T180000
DTSTAMP:20260404T155626Z
UID:202211141700@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nMachine learning is increasingly used in security-critical
  applications\, such as malware detection\, face recognition\, and autonom
 ous driving. But can we trust machine learning? Unfortunately\, the answer
  is `No`. Learning methods are vulnerable to different types of attacks th
 at thwart their secure application. However\, most research has focused on
  attacks in the feature space of machine learning.\n\nIn my talk\, we will
  learn that we should think beyond the feature space when thinking about t
 he security of machine learning. First\, the problem space with real-world
  objects such as PDF files or malicious code should be considered. Real at
 tacks are possible but require specialized techniques. Second\, the mappin
 g from problem to feature space can introduce a considerable vulnerability
  in learning-based systems. Using the example of image scaling\, we will e
 xamine how an adversary can exactly control the input to a learning algori
 thm. Third\, we will also learn that the feature space also has an inheren
 t connection to the media space of digital watermarking.\n\nErwin Quiring 
 is a postdoctoral researcher at the Ruhr University Bochum \nas part of Ge
 rmany's Excellence Cluster CASA. His main research focus \nlies in the int
 ersection between machine learning and security\, with \ntopics such as ma
 lware detection\, deep fake detection\, or adversarial \nlearning.\n
LOCATION:BH(S)5.01
END:VEVENT
BEGIN:VEVENT
SUMMARY:Malware: The Never-Ending Arms Race by Héctor Menendez
DTSTART;TZID=Europe/London:20221108T140000
DTEND;TZID=Europe/London:20221108T150000
DTSTAMP:20260404T155626Z
UID:202211081400@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\n"Antivirus is death" and probably every detection system t
 hat focuses on a single strategy for indicators of compromise. This famous
  quote that Brian Dye --Symantec's senior vice president-- stated in 2014 
 is the best representation of the current situation with malware detection
  and mitigation. Concealment strategies evolved significantly during the l
 ast years\, not just like the classical ones based on polymorphic and meta
 morphic methodologies\, which killed the signature-based detection that an
 tiviruses use\, but also the capabilities to fileless malware\, i.e. malwa
 re only resident in volatile memory that makes every disk analysis sensele
 ss. This review provides a historical background of different concealment 
 strategies introduced to protect malicious --and not necessarily malicious
 -- software from different detection or analysis techniques. It will cover
  binary\, static and dynamic analysis\, and also new strategies based on m
 achine learning from both perspectives\, the attackers and the defenders.\
 n\n\n
LOCATION:BH(S)5.01 
END:VEVENT
BEGIN:VEVENT
SUMMARY:Integrating Security by Design and Automated Security Analysis for
  Digital Identity Management by Marco Pernpruner
DTSTART;TZID=Europe/London:20221024T160000
DTEND;TZID=Europe/London:20221024T170000
DTSTAMP:20260404T155626Z
UID:202210241600@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nWith the rapid growth of technology\, the concept of ident
 ity had to evolve towards a new paradigm: digital identity. This requires 
 the establishment of digital identity management protocols to handle all t
 he related processes. The design of these protocols is a very sensitive pr
 ocess that should be supported by specific methodologies to help security 
 designers reach the best trade-off between all the dimensions at stake. In
  this seminar\, we will dive into identity management protocols by both pr
 oviding some relevant examples and describing a security methodology that 
 we have developed to evaluate the security and risk of these protocols dur
 ing the design process.\n\n\nMarco Pernpruner is a PhD student in Security
 \, Risk and Vulnerability\, jointly offered by the University of Genoa and
  Fondazione Bruno Kessler (Italy). He received the BSc degree in Informati
 on and Business Organisation Engineering from the University of Trento in 
 2016\, and the MSc degree in Computer Science and Engineering from the Uni
 versity of Verona in 2019. He is currently visiting King’s College Londo
 n under the supervision of Prof. Luca Viganò. His research focuses on dig
 ital identity\, with a specialization in the design\, security and risk as
 sessment of multi-factor authentication and fully-remote enrollment proced
 ures.
LOCATION:Bush House (S)2.01
END:VEVENT
BEGIN:VEVENT
SUMMARY:Cosmic Rays: a Neglected Potential Threat to Evidential Integrity 
 in Digital Forensic Investigations? by Richard Overill
DTSTART;TZID=Europe/London:20221004T160000
DTEND;TZID=Europe/London:20221004T170000
DTSTAMP:20260404T155626Z
UID:202210041600@https://cys-seminars.kcl.ac.uk/
DESCRIPTION:\n\nThe Cosmic Ray Defence is introduced and its plausibility 
 in various cybercrime scenarios is evaluated quantitatively.\n\n
LOCATION:BH(N)5.11
END:VEVENT
END:VCALENDAR