Re-visiting the One-Time Pad

In 1949, Shannon proved the perfect secrecy of the Vernam cryptographic system,also popularly known as the One-Time Pad (OTP). Since then, it has been believed that the perfectly random and uncompressible OTP which is transmitted needs to have a length equal to the message length for this result to be true. In this paper, we prove that the length of the transmitted OTP which actually contains useful information need not be compromised and could be less than the message length without sacrificing perfect secrecy. We also provide a new interpretation for the OTP encryption by treating the message bits as making True/False statements about the pad, which we define as a private-object. We introduce the paradigm of private-object cryptography where messages are transmitted by verifying statements about a secret-object. We conclude by suggesting the use of Formal Axiomatic Systems for investing N bits of secret.Comment: 13 pages, 3 figures, submitted for publication to IndoCrypt 2005 conferenc

Re-visiting the One-Time Pad

In 1949, Shannon proved the perfect secrecy of the Vernam cryptographic system (One-Time Pad or OTP). It has generally been believed that the perfectly random and uncompressible OTP which is transmitted needs to have a length equal to the message length for this result to be true. In this paper, we prove that the length of the transmitted OTP actually contains useful information and could be exploited to compress the transmitted-OTP while retaining perfect secrecy. The message bits can be interpreted as True/False statements about the OTP, a private object, leading to the notion of private object cryptography

Measuring Information Leakage in Website Fingerprinting Attacks and Defenses

Tor provides low-latency anonymous and uncensored network access against a local or network adversary. Due to the design choice to minimize traffic overhead (and increase the pool of potential users) Tor allows some information about the client's connections to leak. Attacks using (features extracted from) this information to infer the website a user visits are called Website Fingerprinting (WF) attacks. We develop a methodology and tools to measure the amount of leaked information about a website. We apply this tool to a comprehensive set of features extracted from a large set of websites and WF defense mechanisms, allowing us to make more fine-grained observations about WF attacks and defenses.Comment: In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security (CCS '18

Mockingbird: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces

Website Fingerprinting (WF) is a type of traffic analysis attack that enables a local passive eavesdropper to infer the victim's activity, even when the traffic is protected by a VPN or an anonymity system like Tor. Leveraging a deep-learning classifier, a WF attacker can gain over 98% accuracy on Tor traffic. In this paper, we explore a novel defense, Mockingbird, based on the idea of adversarial examples that have been shown to undermine machine-learning classifiers in other domains. Since the attacker gets to design and train his attack classifier based on the defense, we first demonstrate that at a straightforward technique for generating adversarial-example based traces fails to protect against an attacker using adversarial training for robust classification. We then propose Mockingbird, a technique for generating traces that resists adversarial training by moving randomly in the space of viable traces and not following more predictable gradients. The technique drops the accuracy of the state-of-the-art attack hardened with adversarial training from 98% to 42-58% while incurring only 58% bandwidth overhead. The attack accuracy is generally lower than state-of-the-art defenses, and much lower when considering Top-2 accuracy, while incurring lower bandwidth overheads.Comment: 18 pages, 13 figures and 8 Tables. Accepted in IEEE Transactions on Information Forensics and Security (TIFS

Barriers to positive mental health in a young offenders institution: A qualitative study

Objective: To explore the barriers to positive mental health in a group of young offenders. Design A qualitative approach was used to provide insight into the ways in which mental health for young offenders is experienced and managed. Setting A Young Offenders Institute (YOI) accommodating males aged between 18 and 21 years. Method: Participants were recruited voluntarily using posters. Twelve offenders participated in focus groups and an additional three interviews were carried out with individuals who felt uncomfortable in the focus group situation. Results: Participants stressed that feelings in a YOI could not be shared due to the masculine ethos that had been created on the wings. Listener services were reported to be ineffective for support because using them would show weakness and vulnerability to other prisoners. Visiting time was the main highlight in the routine for most young offenders; however, leaving family and friends was difficult. In dealing with these emotions young offenders would use coping mechanisms, including acts of aggression to vent built-up frustrations. The issue of prison staff and their effect on mental health was raised by all offenders involved in the research. Unanimously, it was suggested that there are both excellent prison officers who engage with the prisoners, and staff who abuse their power and treat prisoners disrespectfully. Conclusion: Promoting mental health is not the principle business of a YOI. However, this research has generated some issues for consideration for governors and those working within this setting

On distributed virtual network embedding with guarantees

To provide wide-area network services, resources from different infrastructure providers are needed. Leveraging the consensus-based resource allocation literature, we propose a general distributed auction mechanism for the (NP-hard) virtual network (VNET) embedding problem. Under reasonable assumptions on the bidding scheme, the proposed mechanism is proven to converge, and it is shown that the solutions guarantee a worst-case efficiency of (1-(1/e)) relative to the optimal node embedding, or VNET embedding if virtual links are mapped to exactly one physical link. This bound is optimal, that is, no better polynomial-time approximation algorithm exists, unless P=NP. Using extensive simulations, we confirm superior convergence properties and resource utilization when compared to existing distributed VNET embedding solutions, and we show how by appropriate policy design, our mechanism can be instantiated to accommodate the embedding goals of different service and infrastructure providers, resulting in an attractive and flexible resource allocation solution.CNS-0963974 - National Science Foundationhttp://www.cs.bu.edu/fac/matta/Papers/ToN-CAD.pdfAccepted manuscrip

Count-Based Exploration with the Successor Representation

In this paper we introduce a simple approach for exploration in reinforcement learning (RL) that allows us to develop theoretically justified algorithms in the tabular case but that is also extendable to settings where function approximation is required. Our approach is based on the successor representation (SR), which was originally introduced as a representation defining state generalization by the similarity of successor states. Here we show that the norm of the SR, while it is being learned, can be used as a reward bonus to incentivize exploration. In order to better understand this transient behavior of the norm of the SR we introduce the substochastic successor representation (SSR) and we show that it implicitly counts the number of times each state (or feature) has been observed. We use this result to introduce an algorithm that performs as well as some theoretically sample-efficient approaches. Finally, we extend these ideas to a deep RL algorithm and show that it achieves state-of-the-art performance in Atari 2600 games when in a low sample-complexity regime.Comment: This paper appears in the Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI 2020

Processing of above/below categorical spatial relations by baboons (Papio papio)

Three video-formatted experiments investigated the categorization of ‘above’ and ‘below’ spatial relations in baboons (Papio papio). Using an identity matching-to-sample task, six baboons correctly matched line–dot stimuli based on the ‘above’ or ‘below’ location of the dot relative to the line (Experiment 1). Positive transfer of performance was then observed when the line–dot distance depicted in the sample stimulus differed from that of the two comparison stimuli (Experiment 2). Using a go:nogo procedure, two baboons were further trained to discriminate whether a ‘B’ character was displayed ‘above’ or ‘below’ a ‘3’ character (Experiment 3). After training, a positive transfer of performance was observed with the same type of stimuli depicted in different type fonts. Altogether, these results suggest that baboons may form conceptual representations of ‘above’ and ‘below’ spatial relations, and categorize visual forms on that basis