Presence Of Encryption Research Articles

Triplex: an Efficient and One-Pass Leakage-Resistant Mode of Operation

This paper introduces and analyzes Triplex, a leakage-resistant mode of operation based on Tweakable Block Ciphers (TBCs) with 2n-bit tweaks. Triplex enjoys beyond-birthday ciphertext integrity in the presence of encryption and decryption leakage in a liberal model where all intermediate computations are leaked in full and only two TBC calls operating a long-term secret are protected with implementationlevel countermeasures. It provides beyond-birthday confidentiality guarantees without leakage, and standard confidentiality guarantees with leakage for a single-pass mode embedding a re-keying process for the bulk of its computations (i.e., birthday confidentiality with encryption leakage under a bounded leakage assumption). Triplex improves leakage-resistant modes of operation relying on TBCs with n-bit tweaks when instantiated with large-tweak TBCs like Deoxys-TBC (a CAESAR competition laureate) or Skinny (used by the Romulus finalist of the NIST lightweight crypto competition). Its security guarantees are maintained in the multi-user setting.

An assessment of reprocessed GPS/MET observations spanning 1995–1997

Abstract. We have performed an analysis of reprocessed GPS/MET data spanning 1995–1997 generated by the COSMIC Data Analysis and Archive Center (CDAAC) in 2007. CDAAC developed modified dual-frequency processing methods for the encrypted data (anti-spoofing (AS)-on) during 1995–1997. We compared the CDAAC data set to the Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA-2) reanalysis, separately for AS-on and AS-off, focusing on the altitude range 10–30 km. MERRA-2 did not assimilate GPS/MET data in the period 1995–1997. To gain insight into the CDAAC data set, we developed a single-frequency data set for GPS/MET, which is unaffected by the presence of encryption. We find excellent agreement between the more limited single-frequency data set and the CDAAC data set: the bias between these two data sets is consistently less than 0.25 % in refractivity, whether or not AS is on. Given the different techniques applied between the CDAAC and the new data set presented here (designated JPL), agreement suggests that the CDAAC AS-on processing and the single-frequency processing are not biased in an aggregate sense greater than 0.25 % in refractivity, which corresponds approximately to a temperature bias less than 0.5 K. Since the profiles contained in the new single-frequency data set are not a subset of the CDAAC profiles, the combination of the CDAAC data set, consisting of 9579 profiles, and the new single-frequency data set, consisting of 4729 profiles, yields a total number of 11 531 unique profiles from combining the JPL and CDAAC data sets. All numbers are after quality control has been applied by the respective processing activities.

AdaptiveMutate: a technique for privacy preservation

Mobile apps are known to be rich sources for gathering privacy-sensitive information about smartphone users. Despite the presence of encryption, passive network adversaries who have access to the network infrastructure can eavesdrop on the traffic and therefore fingerprint a user’s app by means of packet-level traffic analysis. Since it is difficult to prevent the adversaries from accessing the network, providing secrecy in hostile environments becomes a serious concern.In this study, we propose AdaptiveMutate, a privacy-leak thwarting technique to defend against the statistical traffic analysis of apps. First, we present a method for the identification of mobile apps using traffic analysis. Further, we propose a confusion system in which we obfuscate packet lengths, and/or inter-arrival time information leaked by the mobile traffic to make it hard for intruders to differentiate between the altered app traffic and the actual one using statistical analysis. Our aim is to shape one class of app traffic to obscure its features with the minimum overhead. Our system strives to dynamically maximize its efficiency by matching each app with the corresponding most dissimilar app. Also, AdaptiveMutate has an adaptive capability that allows it to choose the most suitable feature to mutate, depending on the type of apps analyzed and the classifier used, if known.We evaluate the efficiency of our model by conducting a comprehensive simulation analysis that mutates different apps to each other using AdaptiveMutate. We conclude that our algorithm is most efficient when we mutate a feature of one app to its most dissimilar one in another app. When applying the identification technique, we achieve a classification accuracy of 91.1%. Then, using our obfuscation technique, we are able to reduce this accuracy to 7%. Also, we test our algorithm against a recently published approach for mobile apps classification and we are able to reduce its accuracy from 94.8% to 17.9%. Additionally, we analyze the tradeoff between the shaping cost and traffic privacy protection, specifically, the associated overhead and the feasibility for real-time implementation.

Network pricing: can both ISP and P2P benefit?

SummaryInternet service providers are facing increasing back pressure from rising access demand by users, especially peer‐to‐peer (P2P)‐based applications that greatly enhance the large‐scale distribution of content into and out of their networks. With the ever increasing consumption pressure on scarce bandwidth resources, ISPs have been forced to reconsider their business model of overselling ‘all‐you‐can‐eat’ broadband at flat rates. Technical solutions such as traffic differentiation or blocking violate the principle of network neutrality; traffic shaping and deep packet analysis fall short in the presence of encryption; and P4P (localized P2P)‐based solutions are difficult to achieve in a heterogeneous environment. Economically, various usage‐based pricing schemes have been proposed and discussed. While they can improve efficiency in bandwidth consumption, they tend to face strong customer resistance as users have strong preference in favour of simple flat rates. We argue that any feasible pricing reforms cannot deviate much from the current flat rates while providing financial incentives for bandwidth hogs to limit their bandwidth access. In contrast to normal usage‐based pricing models that charge by volume, we propose a temporal‐based pricing model that may generate a mutually beneficial solution that can not only increase the profitability of ISPs but also accommodate P2P, rather than killing it, without changing the software, protocols or hardware that clients or ISPs use on the network.Copyright © 2014 John Wiley & Sons, Ltd