Developing Best Practices for Securing VoIP Communication for a non-profit Organization

Voice over Internet Protocol (VoIP) is the most widely used service around the world. The proficiency of it utilizing the web has increased awesome ubiquity in the current years. With this notoriety, there is expanding worry about the wellbeing of the system. The robbery or loss of the information being exchanged is great concern. For example, a basic problem for researchers who are developing safeguards for VoIP systems is the level of threats and other issues experienced by the non-profit organizations while implementing VoIP communication. This problem originated when non-profits received pressure from their donors not to implement VoIP communication because it will record important and valuable information of their bank account, including their bank balance, and consequently, exposing them to the public. Other dangers include safeguarding secrecy, respectability, and accessibility of the system, known as CIA. dangers. To battle these dangers, some security conventions and calculations have been produced. For example, the H.235 has been investigated, their calculations updated, and it is currently regarded as the most recent and effective system for security of the VoIP system. Another method for battling issues and concerns, and one that is the most proficient due to bigger budgets than non-profits, is VoIP being utilized in new structures and the IT work force. Fortunately, the expanding interest of VoIP has guaranteed and emphasized the requirement for more research to build up the effective security structures and countermeasures of CIA threats. This investigation examines the methods by which such security issues concerning VoIP can be set out to give an appropriate, secure and effective method for correspondence and data trade. In this postulation, the analyst will profoundly examine the relief of VoIP security issues

Synesthesia: Detecting Screen Content via Remote Acoustic Side Channels

We show that subtle acoustic noises emanating from within computer screens can be used to detect the content displayed on the screens. This sound can be picked up by ordinary microphones built into webcams or screens, and is inadvertently transmitted to other parties, e.g., during a videoconference call or archived recordings. It can also be recorded by a smartphone or "smart speaker" placed on a desk next to the screen, or from as far as 10 meters away using a parabolic microphone. Empirically demonstrating various attack scenarios, we show how this channel can be used for real-time detection of on-screen text, or users' input into on-screen virtual keyboards. We also demonstrate how an attacker can analyze the audio received during video call (e.g., on Google Hangout) to infer whether the other side is browsing the web in lieu of watching the video call, and which web site is displayed on their screen

From Understanding Telephone Scams to Implementing Authenticated Caller ID Transmission

abstract: The telephone network is used by almost every person in the modern world. With the rise of Internet access to the PSTN, the telephone network today is rife with telephone spam and scams. Spam calls are significant annoyances for telephone users, unlike email spam, spam calls demand immediate attention. They are not only significant annoyances but also result in significant financial losses in the economy. According to complaint data from the FTC, complaints on illegal calls have made record numbers in recent years. Americans lose billions to fraud due to malicious telephone communication, despite various efforts to subdue telephone spam, scam, and robocalls. In this dissertation, a study of what causes the users to fall victim to telephone scams is presented, and it demonstrates that impersonation is at the heart of the problem. Most solutions today primarily rely on gathering offending caller IDs, however, they do not work effectively when the caller ID has been spoofed. Due to a lack of authentication in the PSTN caller ID transmission scheme, fraudsters can manipulate the caller ID to impersonate a trusted entity and further a variety of scams. To provide a solution to this fundamental problem, a novel architecture and method to authenticate the transmission of the caller ID is proposed. The solution enables the possibility of a security indicator which can provide an early warning to help users stay vigilant against telephone impersonation scams, as well as provide a foundation for existing and future defenses to stop unwanted telephone communication based on the caller ID information.Dissertation/ThesisDoctoral Dissertation Computer Science 201

LightBox: Full-stack Protected Stateful Middlebox at Lightning Speed

Running off-site software middleboxes at third-party service providers has been a popular practice. However, routing large volumes of raw traffic, which may carry sensitive information, to a remote site for processing raises severe security concerns. Prior solutions often abstract away important factors pertinent to real-world deployment. In particular, they overlook the significance of metadata protection and stateful processing. Unprotected traffic metadata like low-level headers, size and count, can be exploited to learn supposedly encrypted application contents. Meanwhile, tracking the states of 100,000s of flows concurrently is often indispensable in production-level middleboxes deployed at real networks. We present LightBox, the first system that can drive off-site middleboxes at near-native speed with stateful processing and the most comprehensive protection to date. Built upon commodity trusted hardware, Intel SGX, LightBox is the product of our systematic investigation of how to overcome the inherent limitations of secure enclaves using domain knowledge and customization. First, we introduce an elegant virtual network interface that allows convenient access to fully protected packets at line rate without leaving the enclave, as if from the trusted source network. Second, we provide complete flow state management for efficient stateful processing, by tailoring a set of data structures and algorithms optimized for the highly constrained enclave space. Extensive evaluations demonstrate that LightBox, with all security benefits, can achieve 10Gbps packet I/O, and that with case studies on three stateful middleboxes, it can operate at near-native speed.Comment: Accepted at ACM CCS 201

Persuasive technology and digital design for behaviour change

Copyright @ 2012 Social Science Research NetworkThe convergence of the 'digital' and 'real' worlds has been rapid and transformative of everyday life, as well as design practice - to the extent that talking about 'digital design' and 'the digital context' seems anachronistic and redundant. Nevertheless, the arrival of digital technology, the Internet and social media has, from a design perspective, created a new field of a ffordances, constraints, information flows and possibilities. This paper reviews some of the ways in which digital architecture infl uences behaviour, and what the implications could be for designers seeking to infl uence behaviour for social and environmental bene fit. Topics covered include Persuasive Technology, gami fication, Lessig's 'Code is Law' perspective, digital rights management and Zittrain's concept of generativity

Detection and Mitigation of Steganographic Malware

A new attack trend concerns the use of some form of steganography and information hiding to make malware stealthier and able to elude many standard security mechanisms. Therefore, this Thesis addresses the detection and the mitigation of this class of threats. In particular, it considers malware implementing covert communications within network traffic or cloaking malicious payloads within digital images. The first research contribution of this Thesis is in the detection of network covert channels. Unfortunately, the literature on the topic lacks of real traffic traces or attack samples to perform precise tests or security assessments. Thus, a propaedeutic research activity has been devoted to develop two ad-hoc tools. The first allows to create covert channels targeting the IPv6 protocol by eavesdropping flows, whereas the second allows to embed secret data within arbitrary traffic traces that can be replayed to perform investigations in realistic conditions. This Thesis then starts with a security assessment concerning the impact of hidden network communications in production-quality scenarios. Results have been obtained by considering channels cloaking data in the most popular protocols (e.g., TLS, IPv4/v6, and ICMPv4/v6) and showcased that de-facto standard intrusion detection systems and firewalls (i.e., Snort, Suricata, and Zeek) are unable to spot this class of hazards. Since malware can conceal information (e.g., commands and configuration files) in almost every protocol, traffic feature or network element, configuring or adapting pre-existent security solutions could be not straightforward. Moreover, inspecting multiple protocols, fields or conversations at the same time could lead to performance issues. Thus, a major effort has been devoted to develop a suite based on the extended Berkeley Packet Filter (eBPF) to gain visibility over different network protocols/components and to efficiently collect various performance indicators or statistics by using a unique technology. This part of research allowed to spot the presence of network covert channels targeting the header of the IPv6 protocol or the inter-packet time of generic network conversations. In addition, the approach based on eBPF turned out to be very flexible and also allowed to reveal hidden data transfers between two processes co-located within the same host. Another important contribution of this part of the Thesis concerns the deployment of the suite in realistic scenarios and its comparison with other similar tools. Specifically, a thorough performance evaluation demonstrated that eBPF can be used to inspect traffic and reveal the presence of covert communications also when in the presence of high loads, e.g., it can sustain rates up to 3 Gbit/s with commodity hardware. To further address the problem of revealing network covert channels in realistic environments, this Thesis also investigates malware targeting traffic generated by Internet of Things devices. In this case, an incremental ensemble of autoencoders has been considered to face the ''unknown'' location of the hidden data generated by a threat covertly exchanging commands towards a remote attacker. The second research contribution of this Thesis is in the detection of malicious payloads hidden within digital images. In fact, the majority of real-world malware exploits hiding methods based on Least Significant Bit steganography and some of its variants, such as the Invoke-PSImage mechanism. Therefore, a relevant amount of research has been done to detect the presence of hidden data and classify the payload (e.g., malicious PowerShell scripts or PHP fragments). To this aim, mechanisms leveraging Deep Neural Networks (DNNs) proved to be flexible and effective since they can learn by combining raw low-level data and can be updated or retrained to consider unseen payloads or images with different features. To take into account realistic threat models, this Thesis studies malware targeting different types of images (i.e., favicons and icons) and various payloads (e.g., URLs and Ethereum addresses, as well as webshells). Obtained results showcased that DNNs can be considered a valid tool for spotting the presence of hidden contents since their detection accuracy is always above 90% also when facing ''elusion'' mechanisms such as basic obfuscation techniques or alternative encoding schemes. Lastly, when detection or classification are not possible (e.g., due to resource constraints), approaches enforcing ''sanitization'' can be applied. Thus, this Thesis also considers autoencoders able to disrupt hidden malicious contents without degrading the quality of the image

Social engineering in social network: a systematic literature review

Social engineering is hacking and manipulating people's minds to obtain access to networks and systems in order to acquire sensitive data. A social engineering attack happens when victims are unaware of the strategies utilised and how to avoid them. Although rapid developments in communication technology made communication between individuals easier and faster, on the other hand, individuals' personal and private information is likely to be available online via social networking or other services without adequate security measures to protect such sensitive data. Hackers can use social engineering to target them no matter the technology they use to protect themselves. The methods differ, and the goal is the same, which is to manipulate and deceive organisations, companies, and individuals to obtain sensitive and private in-formation that attackers can benefit from, perhaps to sell it on the dark web or steal the payment card information of victims. The current research presents the attack techniques used in social engineering, as well as ways for pre-venting social engineering assaults. The major purpose of this study is to systematically and impartially conduct a systematic review of previous research on current social engineering attacks and the methods used to reduce these attacks