News 2017

Maria Christakis receives Facebook Faculty Research Award

December 2017
Maria Christakis, an MPI-SWS faculty member, has received a Facebook Faculty Research Award. The award is given in recognition of Maria's work on combining static and dynamic program analysis, which is of particular relevance to Facebook as they are developing sophisticated program analysis tools to handle real-world code.

Maria Christakis receives Facebook Faculty Research Award

December 2017
Maria Christakis, an MPI-SWS faculty member, has received a Facebook Faculty Research Award. The award is given in recognition of Maria's work on combining static and dynamic program analysis, which is of particular relevance to Facebook as they are developing sophisticated program analysis tools to handle real-world code.

Two MPI-SWS faculty awarded DFG grants

December 2017
Two MPI-SWS faculty members have received 3-year research grants from DFG, the German Research Organization.

Eva Darulova has received a single-PI DFG grant entitled "Automated Rigorous Verification and Synthesis of Approximations." Björn Brandenburg has received a DFG grant entitled "RT-Proofs: Formal proofs for real-time systems." This award is for a collaborative grant, with co-PIs at INRIA (Grenoble), Verimag (Grenoble), ONERA (Toulouse), and TU Braunschweig (Germany).

Both projects are actively recruiting doctoral students. Interested students can apply online.

Automated Rigorous Verification and Synthesis of Approximations

Computing resources are fundamentally limited and sometimes an exact solution may not even exist. Thus, when implementing real-world systems, approximations are inevitable, as are the errors introduced by them. The magnitude of errors is problem-dependent but higher accuracy generally comes at a cost in terms of memory, energy or runtime, effectively creating an accuracy-efficiency tradeoff. To take advantage of this tradeoff, we need to ensure that the computed results are sufficiently accurate, otherwise we risk disastrously incorrect results or system failures. Unfortunately, the current way of programming with approximations is mostly manual, and consequently costly, error prone and often produces suboptimal results.

The goal of this project is to develop an end-to-end system which approximates numerical programs in an automated and trustworthy fashion. The programmer will be able to write exact high-level code and our `approximating compiler' will generate an efficient implementation satisfying a given accuracy specification. In order to achieve this vision, we will develop novel sound techniques for verifying the accuracy of approximate numerical programs, as well as new synthesis approaches to generate such approximations automatically.

RT-Proofs: Formal proofs for real-time systems

Real-time systems, i.e., computer systems subject to stringent timing constraints, are at the heart of most modern safety-critical technologies, including automotive systems, avionics, robotics, and factory automation, to name just a few prominent domains in which incorrect timing can have potentially catastrophic consequences. To assure the always-correct operation of such systems, i.e., to make sure that they always react in a timely fashion even in a worst-case scenario, rigorous validation efforts are required prior to deployment. However, establishing that all timing constraints are met is far from trivial --- and requires sophisticated analysis techniques --- because software timing varies in complex and difficult to predict ways, e.g., due to scheduling delays, shared resources, or communication, even when executing on a dedicated processor. Unfortunately, the theoretical foundations of current analysis methods are not nearly as rock-solid as one might expect.

The key problem is that the state-of-the-art methods are backed by only informal or abbreviated proofs, which are typically difficult to understand, check, adapt, or reuse. As a result, there is a non-trivial risk of subtle, but fatal mistakes, either lingering in the published literature, or arising when combining results with unstated, inconsistent assumptions. And indeed, this is not just a hypothetical concern --- most famously, the timing analysis of the CAN real-time bus (widely deployed in virtually all modern cars) was refuted in 2007, 13 years after initial publication. Similarly, other lesser-known examples of incorrect worst-case analyses abound in the literature, including off-by-one errors, incorrect generalizations, and even claims that are simply wrong. Worse, even if the underlying theory is indeed flawless, there is still no guarantee that it is actually implemented correctly in the toolchains used in practice. In short, the state of the art in the analysis of safety-critical real-time systems leaves a lot to be desired --- informal "pen and paper" proofs are simply inadequate.

There is a better way: timing analysis results should be formally proved, machine-checkable, and independently verifiable. To this end, the RT-proofs project will lay the foundations for the computer-assisted verification of schedulability analysis results by (i) formalizing foundational real-time concepts using the Coq proof assistant and (ii) mechanizing proofs of busy-window-based end-to-end latency analysis, the analysis approach of greatest practical relevance (e.g., used by SymTA/S). Additionally, we will (iii) demonstrate with a practical prototype how trust in a vendor's toolchain can be established by certifying the produced analysis results (rather than the tool itself). Leading by example, RT-proofs will fundamentally raise the level of rigor, to the benefit of the academic community, tool vendors, and real-time systems engineers in practice.

Arpan Gujarati wins Middleware 2017 Best Student Paper Award

December 2017
MPI-SWS PhD student Arpan Gujarati has won the Middleware 2017 Best Student Paper award for his paper "Swayam: Distributed Autoscaling to Meet SLAs of Machine Learning Inference Services with Resource Efficiency.” The paper was co-authored with MPI-SWS faculty member Björn Brandenburg, as well as with Sameh Elnikety, Yuxiong He, and Kathryn McKinley. This paper is the result of the work Arpan did during his internship at Microsoft Research.

MPI-SWS researchers win RTAS 2017 Best Paper award

December 2017
Pratyush Patel, Manohar Vanga, and Björn Brandenburg have won the Best Paper award at the 23rd IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 2017) for their paper entitled "TimerShield: Protecting High-Priority Tasks from Low-Priority Timer Interference".

Research Spotlight: Teaching machine learning algorithms to be fair

December 2017
Machine learning algorithms are increasingly being used to automate decision making in several domains such as hiring, lending and crime-risk prediction. These algorithms have shown significant promise in leveraging large or “big” training datasets to achieve high prediction accuracy, sometimes surpassing even human accuracy.

Unfortunately, some recent investigations have shown that machine learning algorithms can also lead to unfair outcomes. For example, a recent ProPublica study found that COMPAS, a tool used in US courtrooms for assisting judges with crime risk prediction, was unfair towards black defendants. In fact, several studies from governments, regulatory authorities, researchers as well as civil rights groups have raised concerns about machine learning potentially acting as a tool for perpetuating existing unfair practices in society, and worse, introducing new kinds of unfairness in prediction tasks. As a consequence, a flurry of recent research has focused on defining and implementing appropriate computational notions of fairness for machine learning algorithms.



Parity-based fairness


Existing computational notions of fairness in the machine learning literature are largely inspired by the concept of discrimination in social sciences and law. These notions require the decision outcomes to ensure parity (i.e. equality) in treatment and in impact.

Notions based on parity in treatment require that the decision algorithm should not take into account the sensitive feature information (e.g., gender, race) of a user. Notions based on parity in impact require that the decision algorithm should give beneficial decision outcomes (e.g., granting a loan) to similar percentages of people from all sensitive feature groups (e.g., men, women).

However, in many cases, these existing notions are too stringent and can lead to unexpected side effects. For example, ensuring parity has been shown to lead to significant reductions in prediction accuracy. Parity may also lead to scenarios where none of the groups involved in decision making (e.g., neither men nor women) get beneficial outcomes. In other words, these scenarios might be preferred neither by the decision maker using the algorithm (due to diminished accuracy), nor by the groups involved (due to very little benefits).

User preferences and fairness


In recent work, to appear at NIPS 2017, researchers at MPI-SWS have introduced two new computational notions of algorithmic fairness: preferred treatment and preferred impact. These notions are inspired by ideas related to envy-freeness and bargaining problem in economics and game theory. Preferred treatment and preferred impact leverage these ideas to build more accurate solutions that are preferable for both the decision maker and the user groups.

The new notion of preferred treatment allows basing the decisions on sensitive feature information (thereby relaxing the parity treatment criterion) as long as the decision outcomes do not lead to envy. That is, each group of users prefers their own group membership over other groups and does not feel that presenting itself to the algorithm as another group would have led to better outcomes for the group.

The new notion of preferred impact allows differences in beneficial outcome rates for different groups (thereby relaxing the parity impact criterion) as long as all the groups get more beneficial outcomes than what they would have received under the parity impact criterion.

In their work, MPI-SWS researchers have developed a technique to ensure machine learning algorithms satisfy preferred treatment and / or preferred impact. They also tested their technique by designing crime-predicting machine-learning algorithms that satisfy the above-mentioned notions. In their experiments, they show that preference-based fairness notions can provide significant gains in overall decision-making accuracy as compared to parity-based fairness, while simultaneously increasing the beneficial outcomes for the groups involved.

This work is one of the most recent additions to an expanding set of techniques developed by MPI-SWS researchers to enable fairness, accountability and interpretability of machine learning algorithms.

References


Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez, Krishna Gummadi and Adrian Weller. From Parity to Preference: Learning with Cost-effective Notions of Fairness. Neural Information Processing Systems (NIPS), Long Beach (CA, USA), December 2017

MPI-SWS paper accepted into WSDM '18

November 2017
The paper "Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation " by MPI-SWS researchers, in collaboration with researchers at KAIST and MPI-IS, has been accepted to WSDM 2018, one of the flagship conferences in data mining.

WSDM will take place in Los Angeles (CA, USA) in February 2018.

MPI-SWS researchers win OOPSLA 2017 Distinguished Paper award

October 2017
David Swasey, Deepak Garg, and Derek Dreyer have won a Distinguished Paper award at the 2017 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA 2017) for their paper "Robust and Compositional Verification of Object Capability Patterns."

Distinguished Paper awards are given to about 10% of papers at OOPSLA.

Multiple Tenure-Track Faculty Openings

September 2017
Applications are invited for faculty positions at all career stages in computer science, with a particular emphasis on systems (broadly construed). We expect multiple positions to be filled in systems, but exceptional candidates in other areas of computer science are also strongly encouraged to apply.

A doctoral degree in computer science or related areas and an outstanding research record (commensurate for the applicant's career stage) are required. Successful candidates are expected to build a team and pursue a highly visible research agenda, both independently and in collaboration with other groups.

MPI-SWS is part of a network of over 80 Max Planck Institutes, Germany's premier basic-research organisations. MPIs have an established record of world-class, foundational research in the sciences, technology, and the humanities. The institute offers a unique environment that combines the best aspects of a university department and a research laboratory: Faculty enjoy full academic freedom, lead a team of doctoral students and post-docs, and have the opportunity to teach university courses; at the same time, they enjoy ongoing institutional funding in addition to third-party funds, a technical infrastructure unrivaled for an academic institution, as well as internationally competitive compensation.

The institute is located in the German cities of Saarbruecken and Kaiserslautern, in the tri-border area of Germany, France, and Luxembourg. We maintain an international and diverse work environment and seek applications from outstanding researchers worldwide. The working language is English; knowledge of the German language is not required for a successful career at the institute.

Qualified candidates should apply on our application website (apply.mpi-sws.org). To receive full consideration, applications should be received by December 1st, 2017.

The institute is committed to increasing the representation of minorities, women, and individuals with physical disabilities. We particularly encourage such individuals to apply. The initial tenure-track appointment is for five years; it can be extended to seven years based on a midterm evaluation in the fourth year. A permanent contract can be awarded upon a successful tenure evaluation in the sixth year.

Multiple Tenure-Track Faculty Openings

September 2017
Applications are invited for faculty positions at all career stages in computer science, with a particular emphasis on systems (broadly construed). We expect multiple positions to be filled in systems, but exceptional candidates in other areas of computer science are also strongly encouraged to apply.

A doctoral degree in computer science or related areas and an outstanding research record (commensurate for the applicant's career stage) are required. Successful candidates are expected to build a team and pursue a highly visible research agenda, both independently and in collaboration with other groups.

MPI-SWS is part of a network of over 80 Max Planck Institutes, Germany's premier basic-research organisations. MPIs have an established record of world-class, foundational research in the sciences, technology, and the humanities. The institute offers a unique environment that combines the best aspects of a university department and a research laboratory: Faculty enjoy full academic freedom, lead a team of doctoral students and post-docs, and have the opportunity to teach university courses; at the same time, they enjoy ongoing institutional funding in addition to third-party funds, a technical infrastructure unrivaled for an academic institution, as well as internationally competitive compensation.

The institute is located in the German cities of Saarbruecken and Kaiserslautern, in the tri-border area of Germany, France, and Luxembourg. We maintain an international and diverse work environment and seek applications from outstanding researchers worldwide. The working language is English; knowledge of the German language is not required for a successful career at the institute.

Qualified candidates should apply on our application website (apply.mpi-sws.org). To receive full consideration, applications should be received by December 1st, 2017.

The institute is committed to increasing the representation of minorities, women, and individuals with physical disabilities. We particularly encourage such individuals to apply. The initial tenure-track appointment is for five years; it can be extended to seven years based on a midterm evaluation in the fourth year. A permanent contract can be awarded upon a successful tenure evaluation in the sixth year.

MPI-SWS paper accepted into NIPS '17

September 2017
The paper "From Parity to Preference: Learning with Cost-effective Notions of Fairness" by MPI-SWS researchers, in collaboration with researchers at the University of Cambridge and MPI-IS, has been accepted to NIPS 2017, the flagship conference in machine learning.

NIPS will take place in Long Beach (CA, USA) in December 2017.

Derek Dreyer receives Robin Milner Young Researcher Award

September 2017
MPI-SWS faculty member Derek Dreyer has received the 2017 Robin Milner Young Researcher Award, which is given by ACM SIGPLAN to recognize outstanding contributions by young investigators in the area of programming languages.  The award citation reads as follows:

"Derek Dreyer has made deep, creative research contributions of great breadth. His areas of impact are as diverse as module systems, data abstraction in higher-order languages, mechanized proof systems and techniques, and concurrency models and semantics. He has refactored and generalized the complex module systems of SML and OCaml; devised logical relations and techniques that enabled advances in reasoning about higher-order imperative programs; and developed novel separation logics for modular verification of low-level concurrent programs. His research papers are a model of clarity and depth, and he has worked actively to translate his foundational ideas into practice – most recently with the RustBelt project to provide formal foundations for the Rust language. Additionally, Dreyer has contributed leadership, support, and mentorship in activities such as the PLMW series of workshops, which are instrumental in growing the next generation of PL researchers."

Previous recipients of the award have included Stephanie Weirich, David Walker, Sumit Gulwani, Lars Birkedal, and Shriram Krishnamurthi.

Derek Dreyer receives Robin Milner Young Researcher Award

September 2017
MPI-SWS faculty member Derek Dreyer has received the 2017 Robin Milner Young Researcher Award, which is given by ACM SIGPLAN to recognize outstanding contributions by young investigators in the area of programming languages.  The award citation reads as follows:

"Derek Dreyer has made deep, creative research contributions of great breadth. His areas of impact are as diverse as module systems, data abstraction in higher-order languages, mechanized proof systems and techniques, and concurrency models and semantics. He has refactored and generalized the complex module systems of SML and OCaml; devised logical relations and techniques that enabled advances in reasoning about higher-order imperative programs; and developed novel separation logics for modular verification of low-level concurrent programs. His research papers are a model of clarity and depth, and he has worked actively to translate his foundational ideas into practice – most recently with the RustBelt project to provide formal foundations for the Rust language. Additionally, Dreyer has contributed leadership, support, and mentorship in activities such as the PLMW series of workshops, which are instrumental in growing the next generation of PL researchers."

Previous recipients of the award have included Stephanie Weirich, David Walker, Sumit Gulwani, Lars Birkedal, and Shriram Krishnamurthi.

Krishna Gummadi and Peter Druschel win ACM SIGCOMM test-of-time award

July 2017
MPI-SWS researchers—faculty members Krishna Gummadi and Peter Druschel and former SWS doctoral students Alan Mislove and Massimiliano Marcon—have received the ACM SIGCOMM Test of Time Award for their IMC 2007 paper on "Measurement and Analysis of Online Social Networks." The work was done in collaboration with Bobby Bhattacharjee of the University of Maryland.

The award citation reads as follows: "This is one of the first papers that examine multiple online social networks at scale. By introducing novel measurement techniques, the paper has had an enduring influence on the analysis, modeling and design of modern social media and social networking services."
The ACM SIGCOMM Test of Time Award is a retrospective award. It recognizes papers published 10 to 12 years in the past in Computer Communication Review or any SIGCOMM sponsored or co-sponsored conference that is deemed to be an outstanding paper whose contents are still a vibrant and useful contribution today.

MPI-SWS paper accepted into RTSS'17

July 2017
The paper entitled "An Exact and Sustainable Analysis of Non-Preemptive Scheduling" by MPI-SWS researchers Mitra Nasri and Björn Brandenburg was accepted into the program of the 38th IEEE Real-Time Systems Symposium (RTSS 2017).

RTSS 2017 will be held from December 6 to December 8 in Paris, France.

 

Amaury Pouly wins Ackermann Award

July 2017
Amaury Pouly, a postdoc in Joël Oukanine's Foundations of Automatic Verification Group, has received the 2017 Ackermann Award for his PhD thesis, “Continuous-time computation models: From computability to computational complexity.” The Ackermann Award is an international prize presented annually to the author of an exceptional doctoral dissertation in the field of Computer Science Logic.

Amaury Pouly's thesis shows that problems which can be solved with a computer in a reasonable amount of time (more specifically problems which belong to the class P of the famous open problem “P = NP?”) can be characterized as polynomial length solutions of polynomial differential equations. This result paves the way for reformulating certain questions and concepts of theoretical computer science in terms of ordinary polynomial differential equations. It also revisits analog computational models and demonstrates that analog and digital computers actually have the same computing power, both in terms of what they can calculate (computability) and what they can solve in reasonable (polynomial) time.

Amaury Pouly wins Ackermann Award

June 2017
Amaury Pouly, a postdoc in Joël Oukanine's Foundations of Automatic Verification Group, has received the 2017 Ackermann Award for his PhD thesis, “Continuous-time computation models: From computability to computational complexity.” The Ackermann Award is an international prize presented annually to the author of an exceptional doctoral dissertation in the field of Computer Science Logic.

Amaury Pouly's thesis shows that problems which can be solved with a computer in a reasonable amount of time (more specifically problems which belong to the class P of the famous open problem “P = NP?”) can be characterized as polynomial length solutions of polynomial differential equations. This result paves the way for reformulating certain questions and concepts of theoretical computer science in terms of ordinary polynomial differential equations. It also revisits analog computational models and demonstrates that analog and digital computers actually have the same computing power, both in terms of what they can calculate (computability) and what they can solve in reasonable (polynomial) time.

MPI-SWS wins best-paper awards at PLDI and ECOOP

June 2017
MPI-SWS researchers made a very strong showing at PLDI and ECOOP in Barcelona this year.  They received two Best Paper Awards, one from PLDI and one from ECOOP, for the following two papers:

PLDI 2017: Repairing Sequential Consistency in C/C++11, by Ori Lahav, Viktor Vafeiadis, Jeehoon Kang, Chung-Kil Hur, and Derek Dreyer.

ECOOP 2017: Strong Logic for Weak Memory: Reasoning About Release-Acquire Consistency in Iris, by Jan-Oliver Kaiser, Hoang-Hai Dang, Derek Dreyer, Ori Lahav, and Viktor Vafeiadis.

In addition, another PLDI best paper award went to the paper "Bringing the Web Up to Speed with WebAssembly", which was presented by Andreas Rossberg, former member of the Foundations of Programming group, who is now a senior engineer at Google.  WebAssembly is the result of an unprecedented collaboration between engineers at Google, Microsoft, Mozilla, and Apple to develop a new portable low-level byte code language to replace JavaScript as a target language for web development.

Adish Singla to join MPI-SWS as tenure-track faculty

June 2017


Adish Singla is joining us from ETH Zurich, where he has completed his Ph.D. in computer science. His research focuses on designing new machine learning frameworks and developing algorithmic techniques, particularly for situations where people are an integral part of computational systems. Adish joins the institute as a tenure-track faculty member, effective Oct 1, 2017.

Before starting his Ph.D., he worked as a Senior Development Lead in Bing Search for over three years. Adish received his Bachelor's degree from IIT Delhi and his Master's degree from EPFL. He is a recipient of the Facebook Fellowship in the area of Machine Learning, the Microsoft Research Tech Transfer Award, and the Microsoft Gold Star Award.

Maria Christakis to join MPI-SWS as tenure-track faculty

June 2017
Maria Christakis joins the institute as a tenure-track faculty member, effective Oct 16, 2017. Maria’s goal is to develop theoretical foundations and practical tools for building more reliable and usable software and increasing developer productivity. She is mostly interested in software engineering, programming languages, and formal methods. Maria particularly likes investigating topics in automatic test generation, software verification, program analysis, and empirical software engineering. Her tools and techniques explore novel ways of writing, specifying, verifying, testing, and debugging programs in order to make them more robust while at the same time improving the user experience.

Maria joins MPI-SWS from the University of Kent, England, where she is a Lecturer at the School of Computing. She was previously a postdoctoral researcher at Microsoft Research Redmond. Maria received her Ph.D. from the Department of Computer Science of ETH Zurich and was awarded with the ETH medal and the EAPLS Best PhD Dissertation Award. She completed her Bachelor’s and Master’s degrees at the Department of Electrical and Computer Engineering of the National Technical University of Athens, Greece.

Two new faculty to join MPI-SWS

June 2017
We are pleased to announce that two new faculty will join MPI-SWS.

Maria Christakis is joining us from the University of Kent, England, where she is a Lecturer at the School of Computing. Maria’s goal is to develop theoretical foundations and practical tools for building more reliable and usable software and increasing developer productivity. She is primarily interested in software engineering, programming languages, and formal methods. Maria joins the institute as a tenure-track faculty member, effective Oct 16, 2017. Maria was previously a post-doctoral researcher at Microsoft Research Redmond. She received her Ph.D. from ETH Zurich and her Bachelor’s and Master’s degrees from the National Technical University of Athens, Greece. Maria is the recipient of the ETH medal and the EAPLS Best PhD Dissertation Award.
Adish Singla is joining us from ETH Zurich, where he has completed his Ph.D. in computer science. His research focuses on designing new machine learning frameworks and developing algorithmic techniques, particularly for situations where people are an integral part of computational systems. Adish joins the institute as a tenure-track faculty member, effective Oct 1, 2017. Before starting his Ph.D., he worked as a Senior Development Lead in Bing Search for over three years. Adish received his Bachelor's degree from IIT Delhi and his Master's degree from EPFL. He is a recipient of the Facebook Fellowship in the area of Machine Learning, the Microsoft Research Tech Transfer Award, and the Microsoft Gold Star Award.

Peter Druschel receives EuroSys Lifetime Achievement Award

April 2017
Peter Druschel has received the 2017 EuroSys Lifetime Achievement Award for his numerous and valuable contributions to research in computer systems. It is the highest honor accorded by EuroSys to systems researchers.

MPI-SWS researchers win RTAS 2017 Outstanding Paper award

April 2017
Mitra Nasri and Björn Brandenburg have won an Outstanding Paper award at the 23rd IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 2017) for their paper entitled "Offline Equivalence: A Non-Preemptive Scheduling Technique for Resource-Constrained Embedded Real-Time Systems".

Real-Time Systems group wins 3 best-paper awards in a row

April 2017
The MPI-SWS Real-Time Systems group, led by Björn Brandenburg, has won the best paper award at ECRTS’16, the best paper award at RTSS’16, and the best paper award at RTAS’17. These are the three main conferences in real-time systems.  This is the first time a group has won best paper awards in all three consecutive top real-time systems conferences. Congratulations to Björn and the postdocs and students in the real-time systems group!

Paul Francis to give keynote at Oakland '17 Workshop on Privacy Engineering

April 2017
Paul Francis will give the keynote address at the Oakland (IEEE S&P) Workshop on Privacy Engineering. The talk, entitled "The Diffix Framework: Revisiting Noise, Again", presents the first database anonymization system that exhibits low noise, unlimited queries, simple configuration, and rich query semantics while still giving strong anonymity.

The workshop will be held May 25 in San Jose, CA.

Talk Abstract:

For over 40 years, the holy grail of database anonymization is a system that allows a wide variety of statistical queries with minimal answer distortion, places no limits on the number of queries, is easy to configure, and gives strong protection of individual user data.  This keynote presents Diffix, a database anonymization system that promises to finally bring us within reach of that goal.  Diffix adds noise to query responses, but "fixes" the noise to the response so that repeated instances of the same response produce the same noise.  While this addresses the problem of averaging attacks, it opens the system to "difference attacks" which can reveal individual user data merely through the fact that two responses differ.  Diffix proactively examines queries and responses to defend against difference attacks.  This talk presents the design of Diffix, gives a demo of a commercial-quality implementation, and discusses shortcomings and next steps.

Principles of Cyber-Physical Systems Course at TU Kaiserslautern

April 2017
Sadegh Soudjani is teaching Principles of Cyber-physical Systems at the University of Kaiserslautern in Summer 2017.

The course meets Tuesdays 11:45-13:15 and Thursdays 10:00-11:30 in 11-260.

Advanced Automata Theory Course at TU Kaiserslautern

April 2017
Rupak Majumdar and Daniel Neider are co-teaching Advanced Automata Theory at the University of Kaiserslautern in the Summer 2017 semester.

The course meets Tuesdays 08:15-09:45 in room 48-210 and Wednesdays 13:45-15:15 in room 46-280 on the University of Kaiserslautern campus.

Paul Francis to lead session at the IAPP Europe Data Protection Congress 2017

April 2017
The session, entitled “Challenges and Strategies for Certifying Data Anonymization for Data Sharing,” brings together technical and legal experts to explore how Data Protection Officers (DPOs) can manage the complexities and uncertainties of GDPR-compliant data anonymization. The IAPP Congress will be held November 7-9 in Brussels.

Session Abstract:

Data sharing is increasingly important. Companies share data internally across business units to gain business insights, they share data externally with data analytics vendors, and they often share data simply to make money. Ensuring the anonymity of users in the data set is necessary. The process of approving or certifying anonymization however is costly, time consuming, and uncertain. Current approaches to anonymization are ad hoc at best. They require a custom strategy for each new data sharing scenario, and it is often unclear whether the data is really anonymized or not.

In this informative and lively session, corporate DPOs, vendors of analytics solutions, and privacy researchers share their experiences with data anonymization and the approval process. They provide case studies illustrating the pitfalls of "do it yourself" anonymization, and show how some new ready-for-use anonymization can eliminate the delays and guesswork of data anonymization.

Paul Francis to give keynote at Oakland '17 Workshop on Privacy Engineering

April 2017
Paul Francis will give the keynote address at the Oakland (IEEE S&P) Workshop on Privacy Engineering. The talk, entitled "The Diffix Framework: Revisiting Noise, Again", presents the first database anonymization system that exhibits low noise, unlimited queries, simple configuration, and rich query semantics while still giving strong anonymity.

The workshop will be held May 25 in San Jose, CA.

Talk Abstract:

For over 40 years, the holy grail of database anonymization is a system that allows a wide variety of statistical queries with minimal answer distortion, places no limits on the number of queries, is easy to configure, and gives strong protection of individual user data.  This keynote presents Diffix, a database anonymization system that promises to finally bring us within reach of that goal.  Diffix adds noise to query responses, but "fixes" the noise to the response so that repeated instances of the same response produce the same noise.  While this addresses the problem of averaging attacks, it opens the system to "difference attacks" which can reveal individual user data merely through the fact that two responses differ.  Diffix proactively examines queries and responses to defend against difference attacks.  This talk presents the design of Diffix, gives a demo of a commercial-quality implementation, and discusses shortcomings and next steps.

Best Paper Award Honorable Mention at WWW '17

April 2017
The MPI-SWS paper "Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate" has received a Best Paper Award Honorable Mention at WWW 2017.

The 26th International World Wide Web Conference (WWW) took place in Perth (Australia) in April 2017.

eine quatsch news

March 2017
ohne excerpt

 

Girls' Day 2017

March 2017
MPI-INF and MPI-SWS jointly participated in Girl's Day this year.

The Max Planck Institutes for Informatics and Software Systems pursue basic research in many areas of computer science. But what exactly is computer science? And what does a day in the life of a scientist look like in computer science? We addressed these questions by way of hands-on examples and demonstrated, for instance, how a computer learns, how the car navigation system knows how to get from A to B, and also how one doesn’t always need a computer for doing computer science. Along the way, the school girls were able to ask our students and researchers all sorts of questions about what it is like to work in research.

--------

Die Max-Planck Institute für Informatik und Software Systeme betreiben Grundlagenforschung in vielen Bereichen der Informatik. Aber was genau ist Informatik? Und wie sieht ein Tag im Leben einer Wissenschaftlerin in der Informatik aus? Genau dies haben wir anhand von Beispielen zum Anfassen und Ausprobieren gezeigt und dabei z.B. illustriert, wie ein Computer lernt, wie das Navi weiß wie man von A nach B kommt, und auch dass man für Informatik nicht immer einen Computer braucht. Nebenbei hatten die Schülerinnen die Gelegenheit unseren StudentInnen, DoktorandInnen und WissenschaftlerInnen allerlei Fragen zu stellen, wie es denn ist in der Forschung zu arbeiten.

Reinhard Munz interns at Nokia/Bell Labs

February 2017
Reinhard Munz, a doctoral student in Paul Francis' group, is doing an internship at Nokia/Bell Labs. His internship will last from January to May, and is in the Autonomous Software Systems Research Group led by Volker Hilt.

Targeted malware paper accepted at NDSS '17

January 2017
The paper "A Broad View of the Ecosystem of Socially Engineered Exploit Documents" was accepted at NDSS '17 (Network and Distributed System Security Symposium).  The authors include Stevens Le Blond, Cédric Gilbert, Utkarsh Upadhyay, and Manuel Gomez Rodriguez from MPI-SWS, as well as David Choffnes from Northeastern University.

Our understanding of exploit documents as a vector to deliver targeted malware is limited to a handful of studies done in collaboration with the Tibetans, Uyghurs, and political dissidents in the Middle East. In this measurement study, we present a complementary methodology relying only on publicly available data to capture and analyze targeted attacks with both greater scale and depth. In particular, we detect exploit documents uploaded over one year to a large anti-virus aggregator (VirusTotal) and then mine the social engineering information they embed to infer their likely targets and contextual information of the attacks. We identify attacks against two ethnic groups (Tibet and Uyghur) as well as 12 countries spanning America, Asia, and Europe. We then analyze the exploit documents dynamically in sandboxes to correlate and compare the exploited vulnerabilities and malware families targeting different groups. Finally, we use machine learning to infer the role of the uploaders of these documents to VirusTotal (i.e., attacker, targeted victim, or third-party), which enables their classification based only on their metadata, without any dynamic analysis. We make our datasets available to the academic community.

A week-long school for outstanding undergrad/MS students curious about research in computing. Apply by Feb 7!

January 2017
Outstanding undergraduate and Masters students are invited to learn about world-class research in security and privacy, social systems, distributed systems, machine learning, programming languages, and verification. Leading researchers will engage with attendees in their areas of expertise: the curriculum will include lectures, projects, and interaction with faculty from participating institutions.

Attendees will be exposed to state-of-the-art research in computer science, have the opportunity to interact one-on-one with internationally leading scientists from three of the foremost academic institutions in research and higher learning in the US and in Europe, and network with like-minded students. They will get a sense of what it is like to pursue an academic or industrial research career in computer science and have a head start when applying for graduate school.

Applications are due by February 7, 2017. Travel and accommodation will be covered for accepted students.

More info can be found on the CMMRS website.