Practical privacy in WDM networks with all-optical layered encryption

Information technology is developing rapidly, especially in the field of computer science, telecommunications and information systems. In the early days of telecommunications, voice networks could not be combined with data networks. However, more recently it became possible to integrate data, audio and video services onto a single network, known as a multimedia network. The capabilities of the Internet are also rapidly increasing, and now, in addition to data packets (email, web browsing) the Internet transfers audio and video packets. Voice over Internet Protocol (VoIP) is a multimedia service. This technology can be used to transmit audio, video, and data packets. Consequently, it is becoming the most preferred communications technology. VoIP will eventually replace the use of traditional telephony – Public Switched Telephone Networks (PSTN), although the switchover process is challenging. A chief concern it that, while PSTN transmits audio packets over a closed network, VoIP sends audio packets using an open network – the Internet. In PSTN, eavesdroppers must have direct access to physical network to obtain information from communications. Whereas with VoIP, eavesdroppers can monitor data packets from they are connected to the Internet. Hence, security and privacy are important considerations when switching to VoIP systems. One solution is anonymous systems, which can be used to implement security and privacy protocols. However, this typically reduces the Quality of Service (QoS) of the VoIP. This empirical research study examines VoIP performance in an anonymous network – The Onion Routing (Tor). Two scenarios are implemented using the real Tor network to investigate three QoS metrics for VoIP: latency, jitter and packet loss. As recommended, latency in VoIP should be less than 400 ms, jitter should be less than 50 ms and packet loss should not be more than 5%. In addition, the research calculates the probability of attackers in the two scenarios implemented and evaluate Tor network forecasting. Experiments were conducted in reference to two scenarios. The first scenario is VoIP calls routed through a Tor network with three Tor relays (default Tor). And the second scenario is VoIP calls routed through a Tor network with two Tor relays. Experiments were performed in three periods; December 2012, July 2013, and October 2013. During each experimental time period, a hundred calls were captured for each scenario. Experimental results show that the QoS of VoIP over the two Tor relays was better than the VoIP over the three Tor relays. However, a probability of attackers calculation found that the VoIP with three Tor relays returned better anonymity than that with two Tor relays. The best results were returned over the experimental period in July 2013, when the acceptable calls using two Tor relays reached 64 calls at 5% packet loss. Meanwhile, the worst experimental results were returned in October 2013, when acceptable calls numbered 11 using three Tor relays at 1% packet loss. At the end of 2013, the actual data for relay numbers and bandwidth approached forecast result with time series analysis. Meanwhile, the numbers of Tor users differed from the Tor users forecast. In August 2013, Tor users increased dramatically; this is attributed to the fact that BotNet attack was using the Tor network to attack their target leading to a fivefold increase.

This full paper presents an innovative approach in teaching anonymity algorithms. Teaching end-to-end anonymity algorithms, such as onion routing, has been a challenging task. This is primarily because of the inaccessibility of all the components that make up the end-to-end anonymity network. For example, an onion is the data structure formed by "wrapping" a message with successive layers of encryption to be decrypted by as many intermediary computers as there are layers before arriving at its destination. The intent of the onion routing algorithms is to protect the privacy of its users as well as their freedom and ability to conduct confidential communication by keeping their Internet activities from being monitored. In recent years, community research, specifically at the university level, into onion routing has ground to a halt and the limited resources for establishing private testing networks have fallen into a derelict state. The proposed solution is an elaborate walk-through, detailing the construction of an isolated onion routing network in which onion routing can be observed and verified in a controlled environment. Achieving this will require the configuration of several Directory Authorities, multiple nodes configured as Entry, Middle, and Exit relays, and the generation of a consensus. Once the consensus has been generated, the network will be able to build circuits across the nodes and fulfill the client's requests for information. When a packet capturing tool is applied to the various entities, the life of the packet as it traverses the network will be observed. The product of this endeavor was the creation of a complete virtual environment and detailed documentation of the steps necessary to construct a private onion routing network that can be readily utilized by educators and students to teach and learn the innerworkings of the OR algorithms. Constructing an isolated OR network, where all the network traffic is observable, is an essential first step in peeling back the next layer of onion routing.

The present paper introduces the Onion Router (TOR) also known as anonymity network. In the time of cloud technologies, when everything is stored partially or completely remote the question for our information safety is felicitous all the time. Usually the answer is no. Of course, there is an explanation for that, too. Companies think that their software is perfectly safe, because they previse every known threat and make it stable—no known viruses and bugs are provided with this implementation. The key word is known. Yes, expert programmers can write safe and reliable code, to resist on any familiar menace, but attackers are always a step forward—they find a new code vulnerability and prevail the software. Then developers provide a fix. Then everything starts all over—that is the vulnerability life cycle. For the first time developers take a step forward—so called TOR. It is an attempt for a safer network, a tentative to stop tracing packets, so our personal data could be safe even in the cloud. Main purpose of this paper is to provide discussion about cloud technologies, TOR network and how they can work together. As main subject is pointed a group parameter hold solution which purpose is to increase the security level of the TOR network itself.

Anonymous network provides user privacy to protect identity. The onion routing (TOR) project is one kind of Internet anonymous networks which attracts many researchers and clients nowadays, because of its simplicity and scalability. However, there are some difficulties to analyze TOR performance within live TOR networks since it is distributed and its security nature. This paper presents a TOR network simulation using shadow-plugin-TOR to configure a small scale virtual computer network within a host, running TOR, and then to analyze TOR performance in several measurements. One main advantage is that the shadow—plugin-T OR application can be implemented within a host in which used to build a client-server architecture of TOR network. Various number of relays and clients have been set to examine TOR network performance. The small scale simulations conducted using maximal CPU capacity between 60%–75% and memory (RAM) usage between 320 MiB-1.5 GiB for each configuration. The simulation results show that average transmission time is shortened and bandwidth is faster along with increasing number of relay rather than adding more client.

People require privacy when doing transaction via Internet connection. For example, some people do not want other people to know what web page they request. Anonymous cash is not anonymous anymore if the channel used for the connection identifies the identity of the participating entities. Email users sometimes want to hide their email addresses. These days, the Internet does not really care about privacy. Encryption is provided to protect privacy, but it only protects the content of a transaction. Thus an eavesdropper can still learn the IP addresses of the internet users to infer their identities. Special networks, called the anonymity network, were created to protect privacy, especially the identities of the entities participating in a communication via Internet connections. This paper discusses probabilistic analysis of the anonymity provided by anonymity networks, namely Onion Routing, by using a model-checker tool called PRISM.

Despite the growth of the Internet and the increasing concern for privacy of online communications, current deployments of anonymization networks depends on a very small set of nodes that volunteer their bandwidth. We believe that the main reason is not disbelief in their ability to protect anonymity, but rather the practical limitations in bandwidth and latency that stem from limited participation. This limited participation, in turn, is due to a lack of incentives. We propose providing economic incentives, which historically have worked very well. In this technical report, we demonstrate a payment scheme that can be used to compensate nodes which provide anonymity in Tor, an existing onion routing, anonymizing network. We show that current anonymous payment schemes are not suitable and introduce a hybrid payment system based on a combination of the Peppercoin Micropayment system and a new type of “one use” electronic cash. Our system claims to maintain users’ anonymity, although payment techniques mentioned previously — when adopted individually — provably fail.

Anonymous network communication using onion routing networks such as Tor are used to guard the privacy of sender by encrypting all messages in the overlapped network. These days most of the onion routed communications are not only used for decent cause but also cyber offenders are ill-using onion routings for scanning the ports, hacking, exfiltration of theft data, and other types of online frauds. These cyber-crime attempts are very vulnerable for cloud security. Deep learning is highly effective machine learning method for prediction and classification. Ensembling multiple models is an influential approach to increase the efficiency of learning models. In this work, an ensemble deep learning-based classification model is proposed to detect communication through Tor and non-Tor network. Three different deep learning models are combined to achieve the ensemble model. The proposed model is also compared with other machine learning models. Classification results shows the superiority of the proposed model than other models.

Modern ransomware often generate and manage cryptographic keys on the victim's machine, giving defenders an opportunity to capture exposed keys and recover encrypted data without paying the ransom. However, recent work has raised the possibility of future enclave-enhanced malware that could avoid such mitigations using emerging support for hardware-enforced secure enclaves in commodity CPUs. Nonetheless, the practicality of such enclave-enhanced malware and its potential impact on all phases of the ransomware lifecyle remain unclear. Given the demonstrated capacity of ransomware authors to innovate in order to better extort their victims (e.g. through the adoption of untraceable virtual currencies and anonymity networks), it is important to better understand the risks involved and identify potential mitigations. As a basis for comprehensive security and performance analysis of enclave-enhanced ransomware, we present RansomClave, a family of ransomware that securely manage their cryptographic keys using an enclave. We use RansomClave to explore the implications of enclave-enhanced ransomware for the key generation, encryption and key release phases of the ransomware lifecycle, and to identify potential limitations and mitigations. We propose two plausible victim models and analyse, from an attacker's perspective, how RansomClave can protect cryptographic keys from each type of victim. We find that some existing mitigations are likely to be effective during the key generation and encryption phases, but that RansomClave enables new trustless key release schemes that could potentially improve attacker's profitability and, by extension, make enclaves an attractive target for future attackers.

Anonymous networks provide security for users by obfuscating messages with encryption and hiding communications amongst cover traffic provided by other network participants. The traditional goal of academic research into these networks has been attacks that aim to uncover the identity of network users. But the success of an anonymous network relies not only on it's technical capabilities, but on adoption by a large enough user base to provide adequate cover traffic. If anonymous network nodes can be identified, the users can be harassed, discouraging participation. Tor is an example of widely used anonymous network which uses a form of Onion Routing to provide low latency anonymous communications. This paper demonstrates that traffic from a simulated Tor network can be distinguished from regular encrypted traffic, suggesting that real world Tor users may be vulnerable to the same analysis.

Users' anonymity and privacy are among the major concerns of today's Internet. Anonymizing networks are then poised to become an important service to support anonymous-driven Internet communications and consequently enhance users' privacy protection. Indeed, Tor an example of anonymizing networks based on onion routing concept attracts more and more volunteers, and is now popular among dozens of thousands of Internet users. Surprisingly, very few researches shed light on such an anonymizing network. Beyond providing global statistics on the typical usage of Tor in the wild, we show that Tor is actually being is-used, as most of the observed traffic belongs to P2P applications. In particular, we quantify the BitTorrent traffic and show that the load of the latter on the Tor network is underestimated because of encrypted BitTorrent traffic (that can go unnoticed). Furthermore, this paper provides a deep analysis of both the HTTP and BitTorrent protocols giving a complete overview of their usage. We do not only report such usage in terms of traffic size and number of connections but also depict how users behave on top of Tor. We also show that Tor usage is now diverted from the onion routing concept and that Tor exit nodes are frequently used as 1-hop SOCKS proxies, through a so-called tunneling technique. We provide an efficient method allowing an exit node to detect such an abnormal usage. Finally, we report our experience in effectively crawling bridge nodes, supposedly revealed sparingly in Tor.

Despite increasing popularity of anonymous communications, current anonymity networks are still vulnerable to traffic analysis attacks. We propose Homomorphic EnCrypTion enabled Onion Routing (HECTor) to defeat existing traffic analysis attacks. Instead of mixing traffic at the packet level as current anonymity networks, HECTor mixes traffic at the bit level with network coding techniques. In HECTor, homomorphic encryption enables onion-like layered encryption which has been proven successful in existing anonymity networks. We theoretically analyze the performance of HECTor. Our extensive experiments on HECTor show that HECTor can effectively mitigate existing traffic analysis attacks with high throughput.

A doppler delay-time frequency (DD-TF) cross-domain high-security transmission scheme based on orthogonal time frequency space (OTFS) is proposed, which is compatible with high-speed and large-capacity optical transmission systems. In this scheme, 36 sets of chaotic sequences are mapped out through a two-dimensional chaotic system with variable control parameters and variable initial values for optical physical layer encryption. The data modulated based on OTFS is encrypted by multiple sets of chaotic sequences, achieving cross-domain joint encryption in the DD domains and TF domains. This method improves security performance of the optical transmission system. An experiment is conducted, in which the encrypted 16-quadrature amplitude modulation (QAM) OTFS signals over 25km standard single-mode fiber (SSMF) is achieved, and the key space is 101140 to effectively prevent malicious attacks from illegal Optical Network Units (ONUs). This key space is the reported maximum key space of the physical layer of two-dimensional chaotic systems. Compared with orthogonal frequency division multiplexing (OFDM) encryption scheme, this scheme obtains better transmission performance. It is shown that OTFS system with cyclic prefix (CP) of 1/16 obtains 2.1dB gain than the OTFS system with CP of 1/32 in terms of receiver sensitivity when the bit error rate (BER) is 10-3. Due to its comprehensive advantages in error rate and security performance, this chaotic encryption based on OTFS has a high application prospect in low-cost and reliable optical access system.

Bandwidth management for high speed LANs using wavelength division multiplexing

Dynamic grooming capabilities lies at the hearth of many envisaged scenarios for IP over Optical networks, but studies on its performance are still in their infancy. This work addresses two fundamental aspects of the problem. First of all it presents a novel tool for the study of IP over Optical networks. The tool, freely available on-line, is a network level simulator named GANCLES that includes several innovative features allowing the study of realistic scenarios in IP over Optical networking, making it an ideal tool for Traffic Engineering purposes. GANCLES architecture enables the simulation of dynamic traffic grooming on top of a realistic network model that correctly describes the logical interaction between the optical and the IP layer, i.e., the mutual relationship between routing algorithms and lightpath assignment procedures at the optical layer and routing at the IP layer. Adding or removing lightpaths changes the logical IP topology, which affects IP routing and traffic patterns. The simulator allows for the description of Overlay, Augmented or Peer IP over Optical architectures, depending on the amount of information shared between the IP and optical domain. Second it analyzes and discusses several performance indices and aspects of different grooming policies in the IPO Overlay model, using different traffic models, some of them including elasticity of best effort traffic. Both regular and mesh topolo- gies are analyzed, and results clearly show that the correct evaluation of dynamic grooming policies in IPO networks requires a sophisticated level of modeling, since simplistic assumptions like Poisson traffic, or the incorrect representation of the interaction of IP and Optical control planes, may induce misleading results.

Password-based authentication systems are vulnerable to a variety of security risks, such as phishing, credential theft, and user fatigue due to complex password requirements. This paper introduces a novel passwordless authentication framework that leverages advanced cryptographic techniques, including Zero-Knowledge Proofs (ZKP), Secure Multi-Party Computation (SMPC), and Homomorphic Encryption to enhance security, privacy, and user experience. The proposed system eliminates the need for traditional passwords by utilizing biometric data to generate cryptographic keys, ensuring that sensitive information remains secure. The architecture is composed of three primary components: the client device, the authentication server, and the key management system (KMS). The client device captures biometric data and transforms it into cryptographic keys using SMPC, while the server verifies the authentication using ZKP and establishes secure communication channels via Diffie-Hellman key exchange. The KMS handles key generation, storage, and rotation to ensure secure communication. Evaluation results show that the system is highly resistant to common attack vectors such as replay and man-in-the-middle attacks, with a 0% attack success rate. Performance analysis reveals an average authentication time of 180 ms, which is 10% faster than WebAuthn.