Despite the prevalence and the high impact of command injection attacks, little attention has been given by the research community to this type of code injections. Although there are many software tools to detect and exploit other types of code injections, such as SQL injections or cross-site scripting, there is no dedicated and specialized software that detects and exploits, automatically, command injection vulnerabilities. This paper proposes an open-source tool that automates the process of detecting and exploiting command injection flaws on Web applications, named as COMMand Injection eXploiter (Commix). We present and elaborate on the software architecture and detection engine of Commix as well its extra functionalities that greatly facilitate penetration testers and security researchers in the detection and exploitation of command injection vulnerabilities. Moreover, based on the knowledge and the practical experience gained from the development of Commix, we propose and analyze new identified techniques that perform side-channel exploitation for command injections allowing an attacker to indirectly deduce the output of the executed command (i.e., also known as blind command injections). Furthermore, we evaluate the detection capabilities of Commix, by performing experiments against various applications. The experimental results show that Commix presents high detection accuracy, while at the same time false positives are eliminated. Finally and more importantly, we analyze several 0-day command injection vulnerabilities that Commix detected in real-world applications. Despite its short release time, Commix has been embraced by the security community and comes preinstalled in many security-oriented operating systems including the well-known Kali Linux.

The blackhole attack is one of the simplest yet effective attacks that target the AODV protocol. Blackhole attackers exploit AODV parameters in order to win route requests, and thus, attract traffic, which they subsequently capture and drop. However, the first part of the attack is often neglected in present literature, while the majority of attempts in detection focus only on the second part of the attack (i.e., packet drop). This paper provides a comprehensive analysis of the blackhole attack, focusing not only on the effects of the attack, but also on the exploitation of the route discovery process. As a result, a new critical attack parameter is identified (i.e., blackhole intensity), which quantifies the relation between AODV's sequence number parameter and the performance of blackhole attacks. In addition, a novel blackhole detection mechanism is also proposed. This mechanism utilizes a dynamic threshold cumulative sum (CUSUM) test in order to detect abrupt changes in the normal behavior of AODV's sequence number parameter. A key advantage of the proposed mechanism is its ability to accurately detect blackhole attacks with a minimal rate of false positives, even if the malicious node selectively drops packets. (C) 2016 Elsevier B.V. All rights reserved.

In modern healthcare systems, data sources are highly integrated, and the privacy challenges are becoming a paramount concern. Despite the critical importance of privacy preservation in safeguarding sensitive and private information across various domains, there is a notable deficiency of learning and training material for privacy preservation. In this research, we present a k-anonymity algorithm explicitly for educational purposes. The development of the k-anonymity algorithm is complemented by seven validation tests, that have also been used as a basis for constructing five learning scenarios on privacy preservation. The outcomes of this research provide a practical understanding of a well-known privacy preservation technique and extends the familiarity of k-anonymity and the fundamental concepts of privacy protection to a broader audience.

Due to its flexibility in terms of charging and billing, the smart grid is an enabler of many innovative energy consumption scenarios. One such example is when a landlord rents their property for a specific period to tenants. Then the electricity bill could be redirected from the landlord’s utility to the tenant’s utility. This novel scenario of the smart grid ecosystem, defined in this paper as Grid-to-Go (G2Go), promotes a green economy and can drive rent reductions. However, it also creates critical privacy issues, since utilities may be able to track the tenant’s activities. This paper presents P4G2Go, a novel privacy-preserving scheme that provides strong security and privacy assertions for roaming consumers against honest but curious entities of the smart grid. At the heart of P4G2Go lies the Idemix cryptographic protocol suite, which utilizes anonymous credentials and provides unlinkability of the consumer activities. Our scheme is complemented by the MASKER protocol, used to protect the consumption readings, and the FIDO2 protocol for strong and passwordless authentication. We have implemented the main components of P4G2Go, to quantitatively assess its performance. Finally, we reason about its security and privacy properties, proving that P4G2Go achieves to fulfill the relevant objectives.

TrustZone-based Trusted Execution Environments (TEEs) have been utilized extensively for the implementation of security-oriented solutions for several smart intra and inter-connected devices. Although TEEs have been promoted as the starting point for establishing a device root of trust, a number of published attacks against the most broadly utilized TEE implementations request a second view on their security. The aim of this research is to provide an analytical and educational exploration of TrustZone-based TEE vulnerabilities with the goal of pinpointing design and implementation flaws. To this end, we provide a taxonomy of TrustZone attacks, analyze them, and more importantly derive a set of critical observations regarding their nature. We perform a critical appraisal of the vulnerabilities to shed light on their underlying causes and we deduce that their manifestation is the joint effect of several parameters that lead to this situation. The most important ones are the closed implementations, the lack of security mechanisms, the shared resource architecture, and the absence of tools to audit trusted applications. Finally, given the severity of the identified issues, we propose possible improvements that could be adopted by TEE implementers to remedy and improve the security posture of TrustZone and future research directions.

Security smart industrial systems is prominent due to the proliferation of cyber threats threatening national critical infrastructures. The smart grid comes with intelligent applications based on a bidirectional communication network among its entities. Microgrids are small-scale smart grids that enable Machine-to-Machine (M2) communications as they can operate with some degree of independence from the main grid. Besides protecting critical microgrid applications, an underlying key management scheme is needed to enable secure M2M message transmission and authentication. Existing key management schemes are not adequate due to microgrid special requirements in comparison to traditional networks, while existing schemes intended for the smart grid present weaknesses. We propose the Micro sElf-orgaNiSed mAnagement (MENSA), which is the first hybrid key management and authentication scheme that combines Public Key Infrastructure (PKI) and Web-of-Trust concepts in microgrids. The experimental results to demonstrate the efficiency of MENSA in terms of scalability and swiftness.