Blockchain is offering new opportunities to develop new types of digital services. While research on the topic is still emerging, it has mostly focused on the technical and legal issues instead of taking advantage of this novel concept and creating advanced digital services. In this paper, we are going to leverage the open source Blockchain technology to propose a design for a new electronic voting system that could be used in local or national elections. The Blockchain-based system will be secure, reliable, and anonymous, and will help increase the number of voters as well as the trust of people in their governments.
Open access
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
Abstract The exponential increase of the traffic volume makes Distributed Denial-of-Service (DDoS) attacks a top security threat to service providers. Existing DDoS defense mechanisms lack resources and flexibility to cope with attacks by themselves, and by utilizing other’s companies resources, the burden of the mitigation can be shared. Technologies as blockchain and smart contracts allow distributing attack information across multiple domains, while SDN (Software-Defined Networking) and NFV (Network Function Virtualization) enables to scale defense capabilities on demand for a single network domain. This proposal presents the design of a novel architecture combining these elements and introducing novel opportunities for flexible and efficient DDoS mitigation solutions across multiple domains.
Internet voting has long been a topic both of public discussion and also of scientific research. While the introduction of Internet voting may bring many advantages, it is further important to ensure an adequate level of security of the systems and underlying schemes that are used for casting and tallying the votes in order to encourage faith and acceptance for this relatively new way of voting.
A number of cryptographic schemes have been proposed, that enable secure Internet voting. One of the most established and well-researched solutions is the Helios scheme, which is also implemented as an open-source system. Both its implementation and the scheme behind it has been extensively studied in the literature, and the Helios system has been used for numerous elections in practice, such as the IACR elections.
However, there are election settings for which Helios is currently not appropriate, either due to infrastructure demands, required functionality for the voters or assurance of the security requirements. These kinds of election settings could benefit from the advantages that secure Internet voting provides.
In this thesis we identify the election settings not currently supported by Helios, propose our extensions for each one of these settings and evaluate their security. Hence, this work describes four Internet voting schemes that are build upon Helios, with each scheme developed towards a specific setting.
The first scheme presented here enables elections within the so-called boardroom voting setting. This setting is characterized by its decentralization, whereby all the tasks within the election are distributively performed by the voters themselves, without the support of a centralized infrastructure. The election in the boardroom voting setting are further conducted in an ad-hoc manner, so that limited time is available for preparation beforehand. We propose an extension of Helios that distributes the tasks of the voting system components in Helios among the voters. For this, we use cryptographic primitives such as decentralized key exchange with short authentication strings, distributed secret sharing and distributed decryption and Byzantine agreement.
The second scheme extends Helios with proxy voting functionality. Proxy voting, as a newly emerged form of voting, enables the voter to delegate her voting right in the election to a trusted third-party, the so-called proxy, who is authorized to vote on the voter's behalf. This extension facilitates such delegation while assuring the security for delegating voters and for the proxies and preserves the security guarantees provided by Helios for the voters who vote directly (instead of delegating). For ensuring the security of our extension, we introduce the so-called delegation credentials that are assigned to the voters and are used to compute anonymized delegation tokens sent to the proxies to enable delegation. We further use cryptographic primitives such as proofs of knowledge and signatures of knowledge.
The third scheme combines the first two settings to extend Helios towards the proxy boardroom voting setting, namely, a setting in which the elections are performed in a decentralized way as in boardroom voting, yet the voters who cannot participate in the election themselves are allowed to delegate their voting right to a trusted proxy before the election. The security of our extension is assured with threshold secret sharing and Pedersen commitments.
The fourth scheme extends Helios by improving its security.
As such, it introduces participation privacy, meaning that the voting system does not reveal which voters have participated in the election, while supporting verification that only the eligible voters have cast their ballots in the election. The extension furthermore introduces receipt-freeness, ensuring that the voter cannot create a receipt that proves to a third party how she voted, thus preventing vote selling. To ensure the security of the extension, a new kind of entity is introduced, the posting trustee, and a new kind of ballot, the so-called dummy ballot that is indistinguishable from a normal ballot cast by the voter, but does not modify the election result. We furthermore use disjunctive zero-knowledge proofs and proofs of signature knowledge to prove, that a sender of a particular ballot knows the private signature key of an eligible voter, or that the ballot is a dummy ballot.
For each one of the extensions, the security model is provided, which describes the security requirements and the assumptions that are necessary for ensuring the security requirements (i.e. vote privacy or vote integrity), is provided. For the first three extensions, the security model is used as a base for the informal security evaluation, in which an informal argument is used to show, that the security requirements hold under the described assumptions. Conducting a formal security evaluation for these extensions is considered an important part of the future work, in which new formal definitions have to be developed.
For the fourth extension, we provide a formal security analysis that relies on the formal definitions for the security requirements of vote privacy, vote integrity and eligibility, available in the literature. We furthermore introduce new formal definitions for participation privacy, receipt-freeness and fairness, which we also use for the formal proofs of our extension.
Bruno Rodrigues, Thomas Bocek, Andri Lareida, David Hausheer · 6 authors
Abstract The rapid growth in the number of insecure portable and stationary devices and the exponential increase of traffic volume makes Distributed Denial-of-Service (DDoS) attacks a top security threat to services provisioning. Existing defense mechanisms lack resources and flexibility to cope with attacks by themselves, and by utilizing other’s companies resources, the burden of the mitigation can be shared. Emerging technologies such as blockchain and smart contracts allows for the sharing of attack information in a fully distributed and automated fashion. In this paper, the design of a novel architecture is proposed by combining these technologies introducing new opportunities for flexible and efficient DDoS mitigation solutions across multiple domains. Main advantages are the deployment of an already existing public and distributed infrastructure to advertise white or blacklisted IP addresses, and the usage of such infrastructure as an additional security mechanism to existing DDoS defense systems, without the need to build specialized registries or other distribution mechanisms, which enables the enforcement of rules across multiple domains.
The problem of anomaly detection has been studied for a long time, and many Network Analysis techniques have been proposed as solutions. Although some results appear to be quite promising, no method is clearly to be superior to the rest. In this paper, we particularly consider anomaly detection in the Bitcoin transaction network. Our goal is to detect which users and transactions are the most suspicious; in this case, anomalous behavior is a proxy for suspicious behavior. To this end, we use the laws of power degree and densification and local outlier factor (LOF) method (which is proceeded by k-means clustering method) on two graphs generated by the Bitcoin transaction network: one graph has users as nodes, and the other has transactions as nodes. We remark that the methods used here can be applied to any type of setting with an inherent graph structure, including, but not limited to, computer networks, telecommunications networks, auction networks, security networks, social networks, Web networks, or any financial networks. We use the Bitcoin transaction network in this paper due to the availability, size, and attractiveness of the data set.
The problem of anomaly detection has been studied for a long time. In short, anomalies are abnormal or unlikely things. In financial networks, thieves and illegal activities are often anomalous in nature. Members of a network want to detect anomalies as soon as possible to prevent them from harming the network's community and integrity. Many Machine Learning techniques have been proposed to deal with this problem; some results appear to be quite promising but there is no obvious superior method. In this paper, we consider anomaly detection particular to the Bitcoin transaction network. Our goal is to detect which users and transactions are the most suspicious; in this case, anomalous behavior is a proxy for suspicious behavior. To this end, we use three unsupervised learning methods including k-means clustering, Mahalanobis distance, and Unsupervised Support Vector Machine (SVM) on two graphs generated by the Bitcoin transaction network: one graph has users as nodes, and the other has transactions as nodes.
As the most successful cryptocurrency to date, Bitcoin constitutes a target of choice for attackers. While many attack vectors have already been uncovered, one important vector has been left out though: attacking the currency via the Internet routing infrastructure itself. Indeed, by manipulating routing advertisements (BGP hijacks) or by naturally intercepting traffic, Autonomous Systems (ASes) can intercept and manipulate a large fraction of Bitcoin traffic. This paper presents the first taxonomy of routing attacks and their impact on Bitcoin, considering both small-scale attacks, targeting individual nodes, and large-scale attacks, targeting the network as a whole. While challenging, we show that two key properties make routing attacks practical: (i) the efficiency of routing manipulation; and (ii) the significant centralization of Bitcoin in terms of mining and routing. Specifically, we find that any network attacker can hijack few (<100) BGP prefixes to isolate ~50% of the mining power---even when considering that mining pools are heavily multi-homed. We also show that on-path network attackers can considerably slow down block propagation by interfering with few key Bitcoin messages. We demonstrate the feasibility of each attack against the deployed Bitcoin software. We also quantify their effectiveness on the current Bitcoin topology using data collected from a Bitcoin supernode combined with BGP routing data. The potential damage to Bitcoin is worrying. By isolating parts of the network or delaying block propagation, attackers can cause a significant amount of mining power to be wasted, leading to revenue losses and enabling a wide range of exploits such as double spending. To prevent such effects in practice, we provide both short and long-term countermeasures, some of which can be deployed immediately.
Future wars will be cyber wars and the attacks will be a sturdy amalgamation of cryptography along with malware to distort information systems and its security. The explosive Internet growth facilitates cyber-attacks. Web threats include risks, that of loss of confidential data and erosion of consumer confidence in e-commerce. The emergence of cyber hack jacking threat in the new form in cyberspace is known as ransomware or crypto virus. The locker bot waits for specific triggering events, to become active. It blocks the task manager, command prompt and other cardinal executable files, a thread checks for their existence every few milliseconds, killing them if present. Imposing serious threats to the digital generation, ransomware pawns the Internet users by hijacking their system and encrypting entire system utility files and folders, and then demanding ransom in exchange for the decryption key it provides for release of the encrypted resources to its original form. We present in this research, the anatomical study of a ransomware family that recently picked up quite a rage and is called CTB locker, and go on to the hard money it makes per user, and its source C&C server, which lies with the Internet's greatest incognito mode-The Dark Net. Cryptolocker Ransomware or the CTB Locker makes a Bitcoin wallet per victim and payment mode is in the form of digital bitcoins which utilizes the anonymity network or Tor gateway. CTB Locker is the deadliest malware the world ever encountered.
Botnet phenomenon in smartphones is evolving with the proliferation in mobile phone technologies after leaving imperative impact on personal computers. It refers to the network of computers, laptops, mobile devices or tablets which is remotely controlled by the cybercriminals to initiate various distributed coordinated attacks including spam emails, ad-click fraud, Bitcoin mining, Distributed Denial of Service (DDoS), disseminating other malwares and much more. Likewise traditional PC based botnet, Mobile botnets have the same operational impact except the target audience is particular to smartphone users. Therefore, it is import to uncover this security issue prior to its widespread adaptation. We propose SMARTbot, a novel dynamic analysis framework augmented with machine learning techniques to automatically detect botnet binaries from malicious corpus. SMARTbot is a component based off-device behavioral analysis framework which can generate mobile botnet learning model by inducing Artificial Neural Networks' back-propagation method. Moreover, this framework can detect mobile botnet binaries with remarkable accuracy even in case of obfuscated program code. The results conclude that, a classifier model based on simple logistic regression outperform other machine learning classifier for botnet apps' detection, i.e 99.49% accuracy is achieved. Further, from manual inspection of botnet dataset we have extracted interesting trends in those applications. As an outcome of this research, a mobile botnet dataset is devised which will become the benchmark for future studies.
Botnets, in other means zombie computers that await for instructions to execute, are the greatest threat in the internet today. They are one of the leading sources of online crime. Criminals are able to take advantage of using botnets and threaten online businesses, organizations or any entity in the internet. Criminals design and implement botnets in a complex way in order to hide their identities. Most notably the fact that criminals build command-and-control (C&amp;C) infrastructures to manage their botnets. A botnet command-and-control mechanism (C&amp;C) can be designed in various ways. The key principle behind designing a C&amp;C mechanism is anonymity. Hence, criminals can propagate their instructions to botnets without revealing their identities. Since every new C&amp;C mechanism increases the bar of anonymity, it is getting harder to trace and analyze botnets. In this thesis, we designed and implemented a C&amp;C mechanism, btc-botnet, that runs over Bitcoin network. Btcbotnet has significant features over existing C&amp;C mechanisms such as anonymity and resistance by its nature. We built a library that allows to use Bitcoin network as an underlying infrastructure for C&amp;C mechanism. We evaluate our work and show that its feasibility in terms of metrics such as response time, confirmation time and fees.
Philipp Winter, Roya Ensafi, Karsten Loesing, Nick Feamster
Being a volunteer-run, distributed anonymity network, Tor is vulnerable to Sybil attacks. Little is known about real-world Sybils in the Tor network, and we lack practical tools and methods to expose Sybil attacks. In this work, we develop sybilhunter, the first system for detecting Sybil relays based on their appearance, such as configuration; and behavior, such as uptime sequences. We used sybilhunter's diverse analysis techniques to analyze nine years of archived Tor network data, providing us with new insights into the operation of real-world attackers. Our findings include diverse Sybils, ranging from botnets, to academic research, and relays that hijack Bitcoin transactions. Our work shows that existing Sybil defenses do not apply to Tor, it delivers insights into real-world attacks, and provides practical tools to uncover and characterize Sybils, making the network safer for its users.
Mobile agent brings new concept on programming, especially on distributed computing paradigm. It attracts great interest because of its mobility, autonomy and persistence. But it also brings security issues i.e. insecure networks, malicious agents, malicious hosts and malicious users. One most difficult issues is protecting mobile agent from malicious host because mobile agent execute its code on host so that host can do many things to manipulate data, code and control flow of mobile agent. This paper proposes mobile-agent's self-reliant host security examination so that mobile agent is able to identify malicious host. In this proposed scheme, every hosts must have signature in blinded form in order to ensure unauthorized host cannot use this signature. This signature serves to distinguish malicious hosts with trusted host. When mobile agent arrives at new host, it will check validation of host's signature. Mobile agent also gives challenge to host, and host has to give a valid response. If host cannot give valid signature and response, mobile agent will identify this host as malicious host and return to its previous host. Zero knowledge proof of knowledge is used on challenge-response phase so that private keys cannot be revealed.
Recent years have seen the emergence of a new class of currencies, called\ncryptocurrencies. These currencies use cryptography to provide security\nand peer-to-peer networking to provide a decentralized system. Bitcoin is\nthe most popular of these currencies. It uses a two-pass\nSHA-256 hash at its core. Producing new bitcoins is done through a process\nreferred to as "mining", which involves a brute-force search for a hash with\na specific value. This process requires large amounts of computing power.\n\nCurrent-generation hardware for bitcoin mining includes highly-optimized\nASIC chips which provide huge amounts of performance. However, designers of\nsuch chips are having problems with delivering enough power and cooling\nto the chips. To alleviate this problem, this thesis looks at the possibilities\nof using heterogeneous computing to reduce power consumption and produce a more\nenergy-efficient mining solution.\n\nA SHA-256 accelerator and a DMA module is developed and integrated into a tile for\nthe Single-ISA Heterogeneous MAny-core Computer, SHMAC, and a system with\nmultiple cores is used to exploit the thread-level parallelism provided by\nthe platform. The system is tested using a benchmark to find out what performance\nand energy efficiency can be expected when using the system for bitcoin mining.\n\nThe results show a maximum performance of 175,7 kH/s when running the benchmark\napplication on 14 cores using the SHA-256 accelerator and the DMA module. The best\nenergy efficiency was obtained when running on 14 cores without the DMA enabled,\nat 163,2 kH/J. The results does not compare well to specialized FPGA-based\nbitcoin miners, but demonstrates the SHMAC platform's large degree of thread-level parallelism\nwhich can be better exploited in other applications.
Sławomir Grzonkowski, Alejandro Mosquera, Lamine M. Aouad, Dylan Morss
The mobile threat landscape has undergone rapid growth as smartphones have increased in popularity. The first generation of mobile threats saw attackers relying on various scams delivered through SMS. As the technology progressed and Web browsers, e-mail clients, and custom applications became standard on smartphones, attackers started exploiting new possibilities beyond traditional e-mail spam and phishing attacks. The landscape continues to evolve with mobile bitcoin miners, botnets, and ransomware.
Off-Chain transactions allow for the immediate transfer of Cryptocurrency between two parties, without delays or unavoidable transaction fees. Such capabilities are critical for mainstream Cryptocurrency adaption. They allow for the "Coffee-Coin Criteria"; under which a customer orders a coffee and pays for that coffee in bitcoins. This is not possible with On-Chain transactions today. Unfortunately, all existing Off-Chain transaction protocols are notoriously unreliable The current generation of third-party facilitators are vulnerable to hacker-based attacks. As Mt. Gox tragically demonstrated, centralized-transaction institutions are easy targets for Cryptocurrency thieves. The slightest security flaw in a third-party system will pounced on by hackers, who will proceed to devour it like ants devouring a crab. Under such circumstances, it no wonder that the Public treats most Cryptocurrency services with a constant shadow of suspicion. For Bitcoin to flourish, its anti-hierarchy principles must be applied to safe Off-Chain transactions. First and foremost, we need a new hacker-proof protocol that can easily be executed by any experienced developer. Preferably, the protocol will be open-sourced for full reliability and transparency. This paper presents one such procedure, which allows for he safe transmission of Bitcoin private key control by way of Cryptocubic transactions.
This project attempts to implement an open source FPGA based Bitcoin miner on an Altera DE2-115 development board. Bitcoin is an experimental peer-to-peer digital currency based on public key cryptography. The advantages of Bitcoins are that they can be transferred between any two people anywhere in the world, and they do not have the same fees and lack of control associated with traditional methods of currency transfers. The first part of this project focuses on detailing how the Bitcoin network and open source miner work. The second part of the project attempts to improve the performance of the open source miner, but a lack of resources on the Cyclone IV EP4CE115F29C7 ultimately prevented implementing a dual pipelined design.
Gianluca Dini, Fabio Martinelli, Andrea Saracino, Daniele Sgandurra
We propose PICARD (ProbabIlistic Contract on Android), a framework to generate probabilistic contracts to detect repackaged applications for Android smart phones. A contract describes the sequences of actions that an application is allowed to perform at run-time, i.e. its legal behavior. In PICARD, contracts are generated from the set of traces that represent the usage profile of the application. Both the contract and the application's run-time behavior are represented through clustered probabilistic automata. At run-time, the PICARD monitoring system verifies the compliance of the application trace with the contract. This approach is useful in detecting repackaged applications, whose behavior is strongly similar to the original application but it differs only from small paths in the traces. In this paper, we discuss the framework of PICARD for describing and generating contracts through probabilistic automata and introduce the notion of Action Node, a cluster of related system calls, used to represent high level operations. Then, we present a first set of preliminary experiments on repackaged applications, to evaluate the viability of the proposed approach.
This paper focuses on future requirements of broadband data transmission of public protection and disaster relief, critical infrastructure protection and military, and presents the concept of redundant and secure data communication network system in the multi-organizational environment. We are proposing a fully decentralized architecture with optimized critical communication channels. Here, network actors and elements identify and authenticate by establishing physical connection. This concept also recommends, group level user-authorization mechanism for each participating organization. Their respective users of command and control centers are identified, authorized and authenticated to various data sources. The decentralized architecture concept is using the Distributed Systems intercommunication Protocol (DSiP). The concept is highly fault-tolerant in routine as well as crises operations. The software-based approach is independent of heterogeneous data communication technologies, IP networks and telecommunication operator services. The solution enables to build an effective and lasting cyber secure data network for multi organizational environment. Being a fully decentralized concept, networks of individual member organizations are virtually autonomous and hard to upset each other. That allows smooth message and information exchange to enable interoperability.
Malware and botnets are one of the most serious threats to today's Internet security. In this paper, we characterise the so-called "Miner Botnet". It received major media attention after massive distributed denial of service attacks against a wide range of German and Russian websites, mainly during August and September 2011. We use our insights on this botnet to outline current botnet-related money-making concepts and to show that multiple activities of this botnet are actually centred on the virtual anonymised currency Bitcoin, thus justifying the name. Furthermore, we provide a binary-level analysis of the malware's design and components to illustrate the modularity of the previously mentioned concepts. We give an overview of the structure of the command-and-control protocol as well as of the botnet's architecture. Both centralised as well as distributed infrastructure aspects realised through peer-to-peer are present to run the botnet, the latter for increasing its resiliency. Finally, we provide the results of our ongoing tracking efforts that started in September 2011, focusing on the development of the botnet's size and geographic distribution. In addition we point out the challenge that is generally connected with size measurements of botnets due to the reachability of individual nodes and the persistence of IP addresses over time.
Wireless Sensor Networks (WSNs) will provide an excellent opportunity to control environments. Even WSNs have lot of applications, some of them quite sensitive in nature and require full proof secured environment. The wireless security mechanism is not same as in wired networks. Because there is no user-controlling for each individual node, wireless environment, and more importantly, scarce energy resources. In this paper, we propose the 3-round zero knowledge protocol for main problem in sensor network security is that sensors are compromised once; the adversary can easily launch clone attacks by replicating the compromised node, distributing the clones throughout the network, and starting a variety of insider attacks. Previous works against clone attacks suffer from either a high communication/storage overhead or poor detection accuracy. Here, we propose a novel scheme for detecting clone attacks in sensor networks, which computes for each sensor a social fingerprint by extracting the neighbourhood characteristics and verifies the legitimacy of the originator for each message by checking the enclosed fingerprint. The fingerprint generation is based on the superimposed s-disjunct code, which incurs a very light communication and computation overhead. The fingerprint verification is conducted at both the base station and the neighbouring sensors, which ensures a high detection probability. The security and performance analysis indicate that our algorithm can identify clone attacks with a high detection probability at the cost of a low computation/communication/storage overhead. To our best knowledge, our scheme is the first to provide real-time detection of clone attacks in an effective and efficient way.