Invited Speakers


Anthony TS Ho

On the Intertwining of Information Hiding and Multimedia Security: A Personal Perspective

Over the past decade or so, the tremendous growth and proliferation of multimedia content has led to the important need to protect and verify the content integrity, particularly if the data are to be used for law enforcement, media, legal and financial applications. This has resulted in the research and applications of information hiding, and multimedia security and forensics becoming more and more integrated and intertwined and as clearly demonstrated, amongst other common activities, with the merging of the two prestigious and popular conferences of IH and ACM MMSec into ACM IHMMSEC'2013.

In this keynote presentation, I will present a personal perspective on some of the various changes, challenges, threats and opportunities in the areas of watermarking, steganography/steganalysis, and multimedia security and forensics that I have faced and experienced since I first stumbled upon digital watermarking and steganography some 16 years ago which I am still very much actively involved today. The talk with provide a chronological overview of some key milestones related to watermarking, information hiding and digital forensics, as well as including some personal events from setting up and managing a University spinout, to technology transfer and product commercialization.

Bio and Abstract, Homepage

Carmela Tronsoco

Bayesian inference to evaluate information leakage in complex scenarios

In this talk we explore the suitability of Bayesian Inference techniques, specifically Markov Chain Monte Carlo methods, to evaluate information leakage in complex scenarios. Using anonymity systems, in particular mix networks, as case study we show that casting problems in the context of Bayesian inference provides an appropriate framework to evaluate security properties (e.g., traceability of messages) in complex constraints. We present a generative probabilistic model of mix network architectures that incorporates a number of attack techniques in the trace analysis literature. We use the model to build a Markov Chain Monte Carlo inference engine based on the Metropolis-Hastings algorithm that calculates the probabilities of who is talking to whom given an observation of network traces. Finally, we briefly overview other Bayesian techniques, such as Gibbs sampling and particle filtering, that are useful to tackle other security problems, like user profiling, or to consider dynamic behaviour.

Dominik Engel

Privacy and Security Challenges in the Smart Grid User Domain

The term "smart grids" is used to describe the next-generation intelligent energy systems. Smart grids employ state-of-the-art information and communication technology to control generation, distribution and consumption of energy. With smart grids, the power network organization moves from a hierarchical to a decentralized structure and communication flow moves from largely uni-directional to bi-directional. The degree of information needed on network status is vastly more accurate compared to traditional power networks, and needs to be available in fine granularity in near real-time. The availability of such fine-grained data raises severe privacy concerns in the end-user domain. For example, the application of non-intrusive load monitoring techniques to high-resolution load profiles allows inferring details on user behavior such as presence, sleep-and-wake cycles and the brands of used appliances. Another challenge in the widespread adoption of smart grid technologies lies in the domain of security. Recent reports of smart meters that can easily be hacked and used to remotely control energy availability in the connected household have not helped to increase user trust.

In this talk, the main challenges in the area of smart grid privacy and security from an end-user perspective will be reviewed. At the example of smart metering, selected solutions will be discussed in detail, with a focal point on leveraging insights and methods from multimedia security to provide security and privacy the smart grid user domain. These include signal processing in the encrypted domain / secure signal processing, homomorphic encryption, conditional access based on multi-resolution analysis, as well as watermarking techniques.