This project explores the internet of things (IoT) at home, especially the aspects related to the quantity and the quality of the of data collected by the smart devices and the violation of the users’ privacy this situation represents, since with the help of machine learning algorithms, these devices are capable of storing and analysing information related to the daily routine of each user at home. Therefore, this research enquires new ways to raise the user's’ awareness about the flow of the data within the IoT at home in order to empower them and give them back the status of administrators of this context by designing devices that are capable of obfuscating the data before it leaves the home.During this process, several methods were used together in order to reach the outcomes. From the use of annotated portfolios to evaluate the state of the art related with the field, to video sketching as a useful and quick tool to embrace the user’s perspective in parallel with the use of cultural probes in order to test some conceptual scenarios and find new ways to explore this project based on the experiences of the participants.As a result, this project’s outcome is based on the use of the materialization of the data as the proper way to bring the abstract process that happens in the background closer to the user's reality in order to display how this data is actually flowing through the environment and at the end generate a call­to­action to guide the user into the execution of the obfuscation of the data.This project opens up the discussion within the interaction design field about the way we are communicating with the technology and if it is the proper way to do it when this technology coexist with the user at home. Additionally, it questions the way in which the interfaces should be designed in order to create a transparent dialogue between the users, the objects and the vendors.

Nachhaltige und ethisch vertretbare Beschaffung und Produktion gehören zu den großen Herausforderungen, die aus dem rasanten Klimawandel und der wachsenden Weltbevölkerung resultieren. Die Erneuerbare-Energien-Richtlinie II der EU und das deutsche Lieferkettensorgfaltspflichtengesetz sind nur zwei Beispiele für die Vielzahl von Gesetzen und Vorschriften, die Standards für nachhaltige und ethisch vertretbare Beschaffung und Produktion vorgeben. Sie implizieren einen Bedarf an Transparenz, Rückverfolgbarkeit und Verifizierbarkeit von Lieferketten und Transaktionen. Öffentliche Verifikationen von Transaktionen entlang von Lieferketten ermöglichen es Dritten, die Einhaltung von Standards und Richtlinien und den Wahrheitsgehalt von Nachhaltigkeitsversprechen zu überprüfen. Folglich kann die öffentliche Überprüfbarkeit Kunden, öffentlichen Stellen und Nichtregierungsorganisationen dabei helfen, Verstöße und Betrug in Lieferketten aufzudecken. Dies wiederum kann dazu beitragen, den Druck zur Einhaltung geltender Standards und Vorschriften zu erhöhen. Transaktionen in Lieferketten basieren oft auf vertraulichen Informationen, wie beispielsweise Mengen und Preise. Die Transparenz derartiger Daten könnte auf Geschäftsgeheimnisse schließen lassen, was direkten Einfluss auf die Wettbewerbsvorteile der beteiligten Firmen hätte. Die Vereinbarkeit von Transparenz und Vertraulichkeit scheint jedoch auf den ersten Blick widersprüchlich zu sein. Diese Dissertation stellt sich der Herausforderung, die öffentliche Verifizierbarkeit von Transaktionen in Lieferketten unter Wahrung der Vertraulichkeit zu ermöglichen. Ausgehend von zwei Fallbeispielen für Lieferketten-Verifikationen werden zunächst Anforderungen an Lösungen untersucht und fünf Forschungsfragen abgeleitet. Anschließend wird eine universelle Lösung entworfen, welche Transparenz und Vertraulichkeit in Einklang bringt. Das vorgestellte Systemmodell ermöglicht sichere öffentliche Verifikationen durch den Einsatz von Fully Homomorphic Encryption (FHE) und Proxy Re-Encryption (PRE). Um die Eignung des Systemmodells für eine Vielzahl realer Szenarien zu verdeutlichen, werden in dieser Dissertation Protokolle für verschiedene Verifikationsfunktionen entworfen. Dies umfasst die Verifikation von Bilanzen, motiviert durch den Handel mit nachhaltigem Palmöl, sowie die Verifikation von Verhältnissen, veranschaulicht durch die Verarbeitung verschiedener Arten von Kobalt. Durch theoretische und empirische Untersuchungen wird nachgewiesen, dass die Protokolle sichere öffentliche Verifikationen für realitätsnahe Szenarien in praktikabler Zeit ermöglichen. Im Weiteren werden die Sicherheitseigenschaften und -implikationen des vorgeschlagenen Systemmodells und der Protokolle untersucht. Dies beinhaltet eine formale Analyse des Risikos, vertrauliche Informationen im Falle wiederholter, gleicher Verifikationen preiszugeben. Aufgrund der Anfälligkeit gegenüber derartigen Angriffen beim Verwenden probabilistischer Output Obfuscation, wird das Paradigma der Data-Dependent Deterministic Obfuscation (D3O) vorgestellt. D3O ist ein universelles Konzept und damit unabhängig vom Anwendungsfall der Lieferketten-Verifikation. Daher kann es in einer Vielzahl weiterer Protokolle für sichere Berechnungen eingesetzt werden, um das Abfließen vertraulicher Informationen zu reduzieren. / Sustainable and ethical sourcing and production are major challenges that arise from rapid climate change and our growing world population. The EU's Renewable Energy Directive II and the German Supply Chain Act are just two examples of the multitude of laws and regulations that define standards for sustainable and ethical sourcing and production. They imply a need for supply chain transparency, traceability, and verification. Public verification of supply chain transactions gives any third-party verifier the chance to evaluate compliance and the correctness of claims based on supply chain transaction details. Therefore, public verification can help customers, buyers, regulators, and non-governmental organizations uncover non-compliance and fraud committed by supply chain actors. This, in turn, can help increase the pressure to comply with applicable standards and regulations. Supply chain transactions often involve confidential data like amounts or prices. Transparency of such data could leak trade secrets and affect companies' competitive advantages. However, reconciling transparency with confidentiality seems contradictory at first glance. This thesis takes up the challenge of enabling privacy-preserving public verification of confidential supply chain transactions. Given two exemplary real-world use cases for supply chain verification, the thesis first investigates requirements for valid solutions and infers five research questions. It then designs a universal solution that combines transparency with confidentiality. The proposed system model achieves privacy-preserving public verification by employing the cryptographic techniques of fully homomorphic encryption (FHE) and proxy re-encryption (PRE). To demonstrate the suitability of the system model for a large variety of lifelike supply chain verification scenarios, the thesis designs privacy-preserving protocols for different verification functions. This includes the verification of balances, using the trade in sustainable palm oil as an example, as well as the verification of ratios, motivated by different forms of cobalt sourcing. These protocols are evaluated both theoretically and empirically. Through extensive empirical evaluation, the proposed protocols prove to enable privacy-preserving public verification for the mentioned supply chain scenarios in practical time. Additionally, this thesis investigates the security implications of the proposed system model and protocols and formally analyzes the risk of leaking information through repeated similar verifications. Based on the identified vulnerability to such attacks in the case of probabilistically obfuscated protocol outputs, the thesis introduces and investigates the paradigm of data-dependent deterministic obfuscation (D3O). D3O is a universal concept that is independent of the field of supply chain verification. It can reduce the leakage of confidential information in a large class of privacy-preserving protocols.

Our world of people and objects is on the verge of transforming to a world of highly-interconnected wireless devices. Incredible advances in wireless communications, hardware design, and power storage have facilitated hasty spread of wireless technologies in human life. In this new world, individuals are often identified and reached via one or multiple wireless devices that they always carry (e.g., smartphones, smart wearable, implantable medical devices, etc.), and their biometrics identities are replaced by their digital fingerprints. In near future, vehicles will be controlled and monitored via wireless monitoring systems and various physical objects (e.g., home appliance and retail store items) will be connected to the Internet. The list of these changes goes on. Unfortunately, as different aspects of our lives are being immerged in and dependent to wireless devices and services, we will become more vulnerable to wireless service/connection interruptions due to adversarial behavior and our privacy will become more potent to be exposed to adversaries. An adversary can learn the procedures of a wireless system and analyze its stages, and accordingly, launch various attacks against the operations of the system or the privacy of the people. Existing data confidentiality and integrity services (e.g., advanced encryption algorithms) have been able to prevent the leakage of users' messages. However, in wireless networks, even when upper-layer payloads are encrypted, the users' privacy and the operation of a wireless network can be threatened by the leakage of transmission attributes at the physical (PHY) layer. Examples of these attributes are payload size, frequency offset (FO), modulation scheme, and the transmission rate. These attributes can be exploited by an adversary to launch passive or active attacks. A passive attacker may learn about the interests, sexual orientation, political views, and patentable ideas of the user through analyzing these features, whereas an active attacker exploits captured attributes to launch selective packet jamming/dropping and disrupt wireless services. These call for novel privacy preserving techniques beyond encryption. In this dissertation, we study the vulnerability of current wireless systems to the leakage of transmission attributes at the PHY layer and propose several schemes to prevent it. First, we design and experimentally demonstrate with USRPs an energy-efficient and highly disruptive jamming attack on the FO estimation of an OFDM system. OFDM is the core multiplexing scheme in many modern wireless systems (e.g., LTE/5G and 802.11a/n/ac) and is highly susceptible to FO. FO is the difference in the operating frequencies of two radio oscillators. This estimation is done by the receiver using the publicly-known frame preamble. We show that the leakage of FO value via the preamble can facilitate an optimally designed jamming signal without needing to know the channel between the transmitter and the legitimate receiver. Our results show that the jammer can guarantee a successful attack even when its power is slightly less than the transmitter's power. We then propose four mitigation approaches against the proposed FO attack. Next, we consider certain transmission attributes that are disclosed via unencrypted PHY/MAC headers. Example of these attributes are payload size, transmission rate, and MAC addresses. Beyond unencrypted headers, the adversary can estimate the frame size and transmission rate through identifying the payload's modulation scheme and measuring the transmission time. To prevent the leakage of these attributes, we propose Friendly CryptoJam scheme, which consists of three components: First, a modulation-aware encryption scheme to encrypt the headers. Second, an efficient modulation obfuscation techniques. Specifically, the proposed modulation obfuscation scheme embeds the modulation symbols of a frame's payload into the constellation of the highest-order modulation scheme supported by the system. Together with effective PHY/MAC header encryption at the modulation level, the proposed obfuscation scheme hides the transmission rate, payload size, and other attributes announced in the headers while avoiding any BER performance loss. Compared with prior art, Friendly CryptoJam enjoys less complexity and less susceptibility to FO estimation errors. The third component is a novel PHY-level identification method. To facilitate PHY/MAC header encryption when a MAC layer sender identifier cannot be used (e.g., due to MAC address encryption), we propose two preamble-based sender identification methods, one for OFDM and one for non-OFDM systems. A sender identifier is special message that can be embedded in the frame preamble. The extent of the applications of our embedding scheme goes beyond identifier embedding and include embedding part of the data frame, the sender's digital signature, or any meta-data that the sender provides. Our message embedding method can further be used to mitigate the FO estimation attack because the jammer can no longer optimize its jamming signal with respect to a fixed preamble signal. In addition, we considered friendly jamming technique in a multi-link/hop network to degrade the channels of the eavesdroppers and prevent successful decoding of the headers, while minimizing the required jamming power by optimally placing the friendly jamming devices.

Privacy is defined as the freedom from unauthorized intrusion. The availability of personal information through online databases, such as government records, medical records, and voters and #146; lists, pose a threat to personal privacy. The concern over individual privacy has led to the development of legal codes for safeguarding privacy in several countries. However, the ignorance of individuals as well as loopholes in the systems, have led to information breaches even in the presence of such rules and regulations. Protection against data privacy requires modification of the data itself. The term {em data obfuscation} is used to refer to the class of algorithms that modify the values of the data items without distorting the usefulness of the data. The main goal of this thesis is the development of a data obfuscation technique that provides robust privacy protection with minimal loss in usability of the data. Although medical and financial services are two of the major areas where information privacy is a concern, privacy breaches are not restricted to these domains. One of the areas where the concern over data privacy is of growing interest is collaborative filtering. Collaborative filtering systems are being widely used in E-commerce applications to provide recommendations to users regarding products that might be of interest to them. The prediction accuracy of these systems is dependent on the size and accuracy of the data provided by users. However, the lack of sufficient guidelines governing the use and distribution of user data raises concerns over individual privacy. Users often provide the minimal information that is required for accessing these E-commerce services. The lack of rules governing the use and distribution of data disallows sharing of data among different communities for collaborative filtering. The goals of this thesis are (a) the definition of a standard for classifying DO techniques, (b) the development of a robust cluster preserving data obfuscation algorithm, and (c) the design and implementation of a privacy-preserving shared collaborative filtering framework using the data obfuscation algorithm.

Cloud Computing is emerging as a new paradigm that aims at delivering computing as a utility. For the cloud computing paradigm to be fully adopted and effectively used it is critical that the security mechanisms are robust and resilient to malicious faults and attacks. Securing cloud is a challenging research problem because it suffers from current cybersecurity problems in computer networks and data centers and additional complexity introduced by virtualizations, multi-tenant occupancy, remote storage, and cloud management. It is widely accepted that we cannot build software and computing systems that are free from vulnerabilities and that cannot be penetrated or attacked. Furthermore, it is widely accepted that cyber resilient techniques are the most promising solutions to mitigate cyberattacks and change the game to advantage defender over attacker. Moving Target Defense (MTD) has been proposed as a mechanism to make it extremely challenging for an attacker to exploit existing vulnerabilities by varying different aspects of the execution environment. By continuously changing the environment (e.g. Programming language, Operating System, etc.) we can reduce the attack surface and consequently, the attackers will have very limited time to figure out current execution environment and vulnerabilities to be exploited. In this dissertation, we present a methodology to develop an Autonomic Resilient Cloud Management (ARCM) based on MTD and autonomic computing. The proposed research will utilize the following capabilities: Software Behavior Obfuscation (SBO), replication, diversity, and Autonomic Management (AM). SBO employs spatiotemporal behavior hiding or encryption and MTD to make software components change their implementation versions and resources randomly to avoid exploitations and penetrations. Diversity and random execution is achieved by using AM that will randomly "hot" shuffling multiple functionally-equivalent, behaviorally-different software versions at runtime (e.g., the software task can have multiple versions implemented in a different language and/or run on a different platform). The execution environment encryption will make it extremely difficult for an attack to disrupt normal operations of cloud. In this work, we evaluated the performance overhead and effectiveness of the proposed ARCM approach to secure and protect a wide range of cloud applications such as MapReduce and scientific and engineering applications.

The work analyze current detection methods of anomalies and security incidents in DNS traffic, and than design new obfuscation techniques which are capable of evading anomaly detection. Network attacks, exploiting the DNS protocol for tunneling of other network traffic, were selected for implementation part of the work. Control of botnet is considered as malicious application of tunneling through the DNS protocol. The main result of the work is to emphasize the necessity of discovering new detection principles of anomalies and security incidents in DNS traffic.

No description available.

Darbo tikslas – sudaryti ir praktiškai realizuoti metodą užmaskuoto kenkėjiško programinio kodo tinklalapiuose aptikimui pagal jo savybes. Darbe nagrinėjamos tinklalapiuose talpinamo užmaskuoto kenkėjiško kodo aptikimo problemos. Išanalizuoti kenkėjiško kodo maskavimo metodai ir jo savybės. Aprašytas užmaskuoto JavaScript kodo aptikimo metodas, paremtas nustatytomis užmaskuoto kodo savybėmis ir pagal jas aprašytais paieškos kriterijais: žodžio ilgiu, simbolių skaičiumi žodyje ir simbolių dažniu žodyje. Metodas pristatytas pranešime 14-oje Lietuvos jaunųjų mokslininkų konferencijoje „Mokslas - Lietuvos ateitis“, įvykusioje Vilniuje 2011 m. balandžio 15 d. Remiantis šiuo metodu atliktas tyrimas, kurio rezultatai rodo pasiūlyto metodo veiksmingumą – pasiektas 98% užmaskuoto kodo aptikimo tinklalapiuose tikslumas. Tyrimo rezultatai paskelbti straipsnyje, kuris priimtas spausdinimui recenzuojamame periodiniame mokslo žurnale „Jaunųjų mokslininkų darbai“. Darbą sudaro: įvadas, 6 skyriai, išvados, literatūros sąrašas, priedai. Darbo apimtis – 55 p. teksto be priedų, 23 iliustr., 4 lent., 44 bibliografiniai šaltiniai. Atskirai pridedami darbo priedai. / The aim of this thesis is to suggest and practically implement a method of malicious obfuscated code detection using its characteristics. In this thesis we analyze problems of obfuscated malicious code detection in websites, malicious code obfuscation techniques and obfuscated code characteristics. In this paper suggested method of malicious obfuscated code detection in websites using its characteristics is described. Method is based on three search characteristics: word size, number of characters in word and frequency of particular characters. Method was presented in the 14th Conference for Lithuania Junior Researchers SCIENCE FOR FUTURE held in Vilnius, April 15, 2011. An experiment based on this study was made. Results show the effectiveness of the proposed method – 98% accuracy of obfuscated code detection in websites was reached. Experiment results were published in an article, which is being published in a reviewed periodical academic journal "Young Scientists". Structure: introduction, 6 chapters, conclusions and suggestions, references. Thesis consists of – 55 p. text without appendixes, 23 pictures, 4 tables, 44 bibliographical entries. Appendixes included.

<p>У овој докторској дисертацији анализиран је утицај једне од техника заштите софтвера, позната као маскирање (енг. obfuscation), на енергетску ефикасност извршавања кода. Циљ рада је да проучи колико овакви захвати утичу на промену профила потрошње електричне енергије, односно рангирање алата за промену разумљивости програма на основу енергетског профила за чије генерисање је развијена програмска подршка. Тестирање је реализовано коришћењем различитих комерцијалних алата над релевантним тест сценаријима и резултати су приказани уз одговарајућу анализу.</p> / <p>U ovoj doktorskoj disertaciji analiziran je uticaj jedne od tehnika zaštite softvera, poznata kao maskiranje (eng. obfuscation), na energetsku efikasnost izvršavanja koda. Cilj rada je da prouči koliko ovakvi zahvati utiču na promenu profila potrošnje električne energije, odnosno rangiranje alata za promenu razumljivosti programa na osnovu energetskog profila za čije generisanje je razvijena programska podrška. Testiranje je realizovano korišćenjem različitih komercijalnih alata nad relevantnim test scenarijima i rezultati su prikazani uz odgovarajuću analizu.</p> / <p>This doctoral dissertation analyze the influence of one of the software protection<br />techniques known as obfuscation, to the power efficiency of code obfuscation. The aim<br />of the dissertation is to study the effect of these techniques on the change of power<br />profile consumption, i.e., ranking of tools for changing the program intelligibility based<br />on energy profile for the generation of witch a program support has been developed.<br />The testing is realized by using various commercial software for relevant test scenarious<br />and the results are presented with the corresponding analysis.</p>

Software obfuscation is a protection technique for making code unintelligible to automated program comprehension and analysis tools. It works by performing semantic preserving transformations such that the difficulty of automatically extracting the computational logic out of code is increased. Obfuscating transforms in existing literature have been designed with the ambitious goal of being resilient against all possible reverse engineering attacks. Even though some of the constructions are based on intractable computational problems, we do not know, in practice, how to generate hard instances of obfuscated problems such that all forms of program analyses would fail. In this thesis, we address the problem of software protection by developing a weaker notion of obfuscation under which it is not required to guarantee an absolute blackbox security. Using this notion, we develop provably-correct obfuscating transforms using dependencies existing within program structures and indeterminacies in communication characteristics between programs in a distributed computing environment. We show how several well known static analysis tools can be used for reverse engineering obfuscating transforms that derive resilience from computationally hard problems. In particular, we restrict ourselves to one common and potent static analysis tool, the static slicer, and use it as our attack tool. We show the use of derived software engineering metrics to indicate the degree of success or failure of a slicer attack on a piece of obfuscated code. We address the issue of proving correctness of obfuscating transforms by adapting existing proof techniques for functional program refinement and communicating sequential processes. The results of this thesis could be used for future work in two ways: first, future researchers may extend our proposed techniques to design obfuscations using a wider range of dependencies that exist between dynamic program structures. Our restricted attack model using one static analysis tool can also be relaxed and obfuscations capable of withstanding a broader class of static and dynamic analysis attacks could be developed based on the same principles. Secondly, our obfuscatory strength evaluation techniques could guide anti-malware researchers in the development of tools to detect obfuscated strains of polymorphic viruses. / Whole document restricted, but available by request, use the feedback form to request access.