arXiv subjects

Shishir Nagaraja

Publications and source records attributed to Shishir Nagaraja.

29 records · Page 2Linked to original sources

arXiv2020

Secure Calibration for Safety-Critical IoT: Traceability for Safety Resilience

Secure sensor calibration constitutes a foundational step that underpins operational safety in the Industrial Internet of Things. While much attention has been given to IoT security such as the use of TLS to secure sensed data, little thought has been given to securing the calibration infrastructure itself. Currently traceability is achieved via manual verification using paper-based datasheets which is both time consuming and insecure. For instance, when the calibration status of parent devices is revoked as mistakes or mischance is detected, calibrated devices are not updated until the next calibration cycle, leaving much of the calibration parameters invalid. Aside from error, any party within the calibration infrastructure can maliciously introduce errors since the current paper based system lacks authentication as well as non-repudiation. In this paper, we propose a novel resilient architecture for calibration infrastructure, where the calibration status of sensor elements can be verified on-the-fly to the root of trust preserving the properties of authentication and non-repudiation. We propose an implementation based on smart contracts on the Ethereum network. Our evaluation shows that Ethereum is likely to address the protection requirements of traceable measurements.

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arXiv2019

Privacy with Surgical Robotics: Challenges in Applying Contextual Privacy Theory

The use of connected surgical robotics to automate medical procedures presents new privacy challenges. We argue that conventional patient consent protocols no longer work. Indeed robots that replace human surgeons take on an extraordinary level of responsibility. Surgeons undergo years of training and peer review in a strongly regulated environment, and derive trust via a patient's faith in the hospital system. Robots on the other hand derive trust differently, via the integrity of the software that governs their operation. From a privacy perspective, there are two fundamental shifts. First, the threat model has shifted from one where the humans involved were untrusted to one where the robotic software is untrusted. Second, the basic unit of privacy control is no longer a medical record, but is replaced by four new basic units: the subject on which the robot is taking action; the tools used by the robot; the sensors (i.e data) the robot can access; and, finally access to monitoring and calibration services which afford correct operation of the robot. We suggest that contextual privacy provides useful theoretical tools to solve the privacy problems posed by surgical robots. However, it also poses some challenges: not least that the complexity of the contextual-privacy policies, if rigorously specified to achieve verification and enforceability, will be exceedingly high to directly expose to humans that review contextual privacy policies. A medical robot works with both information and physical material. While informational norms allow for judgements about contextual integrity and the transmission principle governs the constraints applied on information transfer, nothing is said about material property. Certainly, contextual privacy provides an anchor for useful notions of privacy in this scenario and thus should be considered to be extended to cover both information and material flows.

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arXiv2019

Clicktok: Click Fraud Detection using Traffic Analysis

Advertising is a primary means for revenue generation for millions of websites and smartphone apps (publishers). Naturally, a fraction of publishers abuse the ad-network to systematically defraud advertisers of their money. Defenses have matured to overcome some forms of click fraud but are inadequate against the threat of organic click fraud attacks. Malware detection systems including honeypots fail to stop click fraud apps; ad-network filters are better but measurement studies have reported that a third of the clicks supplied by ad-networks are fake; collaborations between ad-networks and app stores that bad-lists malicious apps works better still, but fails to prevent criminals from writing fraudulent apps which they monetise until they get banned and start over again. This work develops novel inference techniques that can isolate click fraud attacks using their fundamental properties. In the {\em mimicry defence}, we leverage the observation that organic click fraud involves the re-use of legitimate clicks. Thus we can isolate fake-clicks by detecting patterns of click-reuse within ad-network clickstreams with historical behaviour serving as a baseline. Second, in {\em bait-click defence}. we leverage the vantage point of an ad-network to inject a pattern of bait clicks into the user's device, to trigger click fraud-apps that are gated on user-behaviour. Our experiments show that the mimicry defence detects around 81\% of fake-clicks in stealthy (low rate) attacks with a false-positive rate of 110110 per hundred thousand clicks. Bait-click defence enables further improvements in detection rates of 95\% and reduction in false-positive rates of between 0 and 30 clicks per million, a substantial improvement over current approaches.

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arXiv2019

A game-theoretic analysis of DoS attacks on driverless vehicles

Driverless vehicles are expected to form the foundation of future connected transport infrastructure. A key weakness of connected vehicles is their vulnerability to physical-proximity attacks such as sensor saturation attacks. It is natural to study whether such attacks can be used to disrupt swarms of autonomous vehicles used as part of a large fleet providing taxi and courier delivery services. In this paper, we start to examine the strategic options available to attackers and defenders (autonomous-fleet operators) in such conflicts. We find that attackers have the upper hand in most cases and are able to carry out crippling denial-of-service attacks on fleets, by leveraging the inherent deficiencies of road networks identified by techniques from graph analysis. Experimental results on ten cities using real-world courier traces shows that most cities will require upgraded infrastructure to defend driverless vehicles against denial-of-service attacks. We found several hidden costs that impact equipment designers and operators of driverless vehicles - not least, that road-networks need to be redesigned for robustness against attacks thus raising some fundamental questions about the benefits.

cs.GT↗

arXiv2018

Do we have the time for IRM?: Service denial attacks and SDN-based defences

Distributed sensor networks such as IoT deployments generate large quantities of measurement data. Often, the analytics that runs on this data is available as a web service which can be purchased for a fee. A major concern in the analytics ecosystem is ensuring the security of the data. Often, companies offer Information Rights Management (IRM) as a solution to the problem of managing usage and access rights of the data that transits administrative boundaries. IRM enables individuals and corporations to create restricted IoT data, which can have its flow from organisation to individual control -- disabling copying, forwarding, and allowing timed expiry. We describe our investigations into this functionality and uncover a weak-spot in the architecture -- its dependence upon the accurate global availability of \emph{time}. We present an amplified denial-of-service attack which attacks time synchronisation and could prevent all the users in an organisation from reading any sort of restricted data until their software has been re-installed and re-configured. We argue that IRM systems built on current technology will be too fragile for businesses to risk widespread use. We also present defences that leverage the capabilities of Software-Defined Networks to apply a simple filter-based approach to detect and isolate attack traffic.

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arXiv2015

Command & Control: Understanding, Denying and Detecting - A review of malware C2 techniques, detection and defences

In this survey, we first briefly review the current state of cyber attacks, highlighting significant recent changes in how and why such attacks are performed. We then investigate the mechanics of malware command and control (C2) establishment: we provide a comprehensive review of the techniques used by attackers to set up such a channel and to hide its presence from the attacked parties and the security tools they use. We then switch to the defensive side of the problem, and review approaches that have been proposed for the detection and disruption of C2 channels. We also map such techniques to widely-adopted security controls, emphasizing gaps or limitations (and success stories) in current best practices.

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arXiv2014

Blindspot: Indistinguishable Anonymous Communications

Communication anonymity is a key requirement for individuals under targeted surveillance. Practical anonymous communications also require indistinguishability - an adversary should be unable to distinguish between anonymised and non-anonymised traffic for a given user. We propose Blindspot, a design for high-latency anonymous communications that offers indistinguishability and unobservability under a (qualified) global active adversary. Blindspot creates anonymous routes between sender-receiver pairs by subliminally encoding messages within the pre-existing communication behaviour of users within a social network. Specifically, the organic image sharing behaviour of users. Thus channel bandwidth depends on the intensity of image sharing behaviour of users along a route. A major challenge we successfully overcome is that routing must be accomplished in the face of significant restrictions - channel bandwidth is stochastic. We show that conventional social network routing strategies do not work. To solve this problem, we propose a novel routing algorithm. We evaluate Blindspot using a real-world dataset. We find that it delivers reasonable results for applications requiring low-volume unobservable communication.

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arXiv2011

Stegobot: construction of an unobservable communication network leveraging social behavior

We propose the construction of an unobservable communications network using social networks. The communication endpoints are vertices on a social network. Probabilistically unobservable communication channels are built by leveraging image steganography and the social image sharing behavior of users. All communication takes place along the edges of a social network overlay connecting friends. We show that such a network can provide decent bandwidth even with a far from optimal routing mechanism such as restricted flooding. We show that such a network is indeed usable by constructing a botnet on top of it, called Stegobot. It is designed to spread via social malware attacks and steal information from its victims. Unlike conventional botnets, Stegobot traffic does not introduce new communication endpoints between bots. We analyzed a real-world dataset of image sharing between members of an online social network. Analysis of Stegobot's network throughput indicates that stealthy as it is, it is also functionally powerful -- capable of channeling fair quantities of sensitive data from its victims to the botmaster at tens of megabytes every month.

cs.CR↗

arXiv2011

Who clicks there!: Anonymizing the photographer in a camera saturated society

In recent years, social media has played an increasingly important role in reporting world events. The publication of crowd-sourced photographs and videos in near real-time is one of the reasons behind the high impact. However, the use of a camera can draw the photographer into a situation of conflict. Examples include the use of cameras by regulators collecting evidence of Mafia operations; citizens collecting evidence of corruption at a public service outlet; and political dissidents protesting at public rallies. In all these cases, the published images contain fairly unambiguous clues about the location of the photographer (scene viewpoint information). In the presence of adversary operated cameras, it can be easy to identify the photographer by also combining leaked information from the photographs themselves. We call this the camera location detection attack. We propose and review defense techniques against such attacks. Defenses such as image obfuscation techniques do not protect camera-location information; current anonymous publication technologies do not help either. However, the use of view synthesis algorithms could be a promising step in the direction of providing probabilistic privacy guarantees.

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arXiv2007

Anonymity in the Wild: Mixes on unstructured networks

As decentralized computing scenarios get ever more popular, unstructured topologies are natural candidates to consider running mix networks upon. We consider mix network topologies where mixes are placed on the nodes of an unstructured network, such as social networks and scale-free random networks. We explore the efficiency and traffic analysis resistance properties of mix networks based on unstructured topologies as opposed to theoretically optimal structured topologies, under high latency conditions. We consider a mix of directed and undirected network models, as well as one real world case study -- the LiveJournal friendship network topology. Our analysis indicates that mix-networks based on scale-free and small-world topologies have, firstly, mix-route lengths that are roughly comparable to those in expander graphs; second, that compromise of the most central nodes has little effect on anonymization properties, and third, batch sizes required for warding off intersection attacks need to be an order of magnitude higher in unstructured networks in comparison with expander graph topologies.

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arXiv2006

The topology of covert conflict

Often an attacker tries to disconnect a network by destroying nodes or edges, while the defender counters using various resilience mechanisms. Examples include a music industry body attempting to close down a peer-to-peer file-sharing network; medics attempting to halt the spread of an infectious disease by selective vaccination; and a police agency trying to decapitate a terrorist organisation. Albert, Jeong and Barabasi famously analysed the static case, and showed that vertex-order attacks are effective against scale-free networks. We extend this work to the dynamic case by developing a framework based on evolutionary game theory to explore the interaction of attack and defence strategies. We show, first, that naive defences don't work against vertex-order attack; second, that defences based on simple redundancy don't work much better, but that defences based on cliques work well; third, that attacks based on centrality work better against clique defences than vertex-order attacks do; and fourth, that defences based on complex strategies such as delegation plus clique resist centrality attacks better than simple clique defences. Our models thus build a bridge between network analysis and evolutionary game theory, and provide a framework for analysing defence and attack in networks where topology matters. They suggest definitions of efficiency of attack and defence, and may even explain the evolution of insurgent organisations from networks of cells to a more virtual leadership that facilitates operations rather than directing them. Finally, we draw some conclusions and present possible directions for future research.

cs.NI↗