Industrial Internet of Things (IIoT) systems are advanced IoT systems composed of sensor devices supported with dynamic objects such as smart vehicles and drones. The collaboration among static and heterogeneous mobile objects makes the topologies of IIoT systems dynamic and complex. This dynamic topology is also partially due to the fact that the static devices are typically partitioned into categories of collaborating sensors (called swarms) managed by side servers. However, existing authentication techniques for IIoT systems do not consider realistic system models simultaneously hosting different types of dynamic objects. For such scenarios, there is a need for a protocol that guarantees a secure Entity-to-Entity (E2E) communication, thus ensuring a smooth and safe production process. In this paper, for IIoT with swarms (SIIoT), we propose a novel key agreement and authentication protocol, HASAO (Honey-list Authentication for SIIoT with Autonomous Objects). HASAO enables efficient and secure E2E communication between devices in the same or different swarms. HASAO fills the gap of considering a realistic system model simultaneously hosting different types of dynamic objects. We employ Honey lists (lists with algorithms used to prevent guessing passwords) and mutual authentication technologies in HASAO to guarantee its security against different attacks, even in public-channel communication scenarios. Using the well-established Real-Or-Random (ROR) model, we proved the security of HASAO in detail. We also provide a prototype implementation of HASAO in the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. This tool confirms the results of our theoretical proofs, thus verifying the security of HASAO. We also carried out a detailed comparative study of HASAO against existing related authentication techniques. Compared to these techniques, HASAO offers more functionality (serving more types of dynamic objects) and superior security (via proving backup plans for session key establishment). Finally, we prove that HASAO is practical by implementing it in a well-known network simulator, Omnet++.

With the rapid technological advancement in the Internet of Things (IoT) and Internet of Vehicles (IoV), we witness exponential growth of Connected and Autonomous Vehicles (CAVs). However, these integrations of IoV with other technologies make the IoV network and its interaction between different network components highly complex. Therefore, ensuring the correct functioning of the firmware and software running on these next-generation vehicles becomes an essential requirement. A feasible method to address the aforementioned security issues is Remote Attestation (RA). However, the advancement in the attackers' approaches and the increased complexity, large network size, and vehicle mobility allow the attacks to bypass these security solutions, making RA less effective. In this paper, we propose LHASIoV, an attestation and healing protocol for IoV. LHASIoV has many features such as competent-wise (treats different entities of the system differently), geographical location-aware (traces forensics of security breaches and eases healing compromised vehicles), gradual healing (via slicing the healing software) of compromised vehicles, and resistance to single-point-of-failure. We provide proof-of-concept implementation and formal operational and security analysis for LHASIoV. To show its practical feasibility and effectiveness, we provide performance analysis by implementing it on the Omnetpp simulator. The simulation results show that for an IoV system that has 100 vehicles moving with a speed range of 15-25 mph, LHASIoV needed only 5.27 seconds to complete the vehicle's attestation. For this number of vehicles and compared to the existing protocols, LHASIoV reduced the communication and storage costs on average by 54.46% and 43.92%, respectively.

The Android application framework has a pervasive presence. In early 2021, Android has over 70 % share of the operating system mobile market (according to GlobalStats). Components are the main building blocks of Android Applications. These blocks communicate via a rich Inter-Component Communication (ICC) model rather than the traditional inter-process communication model. Intents, Intent-filters, and their Intents resolution (matching) algorithm are main elements of the ICC. However, the Intent resolution algorithm is not robust enough and has flaws that can lead to security breaches. In this paper, we present DLAIR, as an enrichment of the Intent resolution algorithm to overcome its security issues. To this end, we start by presenting a formal model to express and validate the ICC semantics. This includes defining key properties guaranteeing consistent and realistic semantic states. We then demonstrate how the semantics can be used to formally validate ICC aspects and to express and check ICC system updates. We verified our proposed model and all its lemmas and theorems in the Coq Proof Assistant, a machine-assisted verification tool. We extend our semantics to develop DLAIR which is assisted by a heuristic, and lightweight tool, LekInt. This tool identifies suspicious execution paths responsible for intent based sensitive user-information leakage. On a dataset of 2000 real-world apps, we evaluated LekInt against Flowdroid, a state-of-the-art information leakage analysis tool. Experiments show that LekInt is more effective and efficient than Flowdroid which has a higher false-negative rate and lower false-positive rate than LekInt. Considering the dynamic context in which LekInt is designed to work, the advantage of efficiency overcomes the disadvantage of higher false-negative.

Internet of Drones (IoD) is a framework to set up drones networks that may serve multiple purposes, e.g., data collection. New IoD applications (such as drone assisted internet of vehicles) envision the simultaneous collection of multiple data types. Although authentication may prevent unauthorized users to access the collected data, existing authentication solutions do not distinguish between the different types of data collected by drones. Therefore, authenticated users may receive sensitive data regarding another user incurring hence in a privacy leakage. In this paper, we propose SETCAP, a novel Service-Based Energy-Efficient Temporal Credential Authentication Protocol for IoD. SETCAP exploits the distinction between data types to prevent information leakage. We formally test SETCAP against the Real-Or-Random (ROR) model and implemented SETCAP in Automated Validation of Internet Security Protocols and Applications (AVISPA) simulation tool. Moreover, we validated SETCAP via non-mathematical security analysis to show its security against many attacks. We assessed the superiority of SETCAP in terms of functionality and security characteristics as well as computation, communication, and energy costs. The communication cost of creating a session in SETCAP is approximately 20% smaller than that of creating a session in the closest state-of-the-art protocol. Furthermore, the framework that we propose requires the creation of a number of sessions that are additive in terms of the number of drones and users, whereas the existing solutions are multiplicative. SETCAP is therefore a secure and scalable solution for resource-constrained devices such as drones.

The inclusion of drones in Internet of Vehicles (IoV) is a current trend that presents significant trade-offs. On the one hand, Unmanned Aerial Vehicles (UAVs) provide advantages such as enabling ground communications also when physical obstacles limit the connectivity. On the other hand, they increase the attack surface. For instance, physical attacks on drones provide the attacker with credentials that can be used to inject bogus information into the IoV network, thus jeopardizing not only security but also users' safety. In this scenario, authentication plays a fundamental role to guarantee security. It is however fundamental to develop authentication protocols that can, at the same time, protect ground users' data and prevent attacks to drones. However, currently available authentication schemes cannot guarantee security in case of attacks to drones. In this paper, we propose a Blockchain-supported authentication protocol for Drone-assisted IoV using Elliptic curve cryptography (BDIVE). Compared to existing authentication protocols, we extend the threat model from an honest-but-curious drone to active attacks against drones. BDIVE provides both energy-efficiency, traceability, and accountability thanks to the use of blockchain at the Trusted Authority (TA). Using Burrow-Abadi-Needham (BAN) logic, we analyze and prove the security of mutual authentication in BDIVE. We also prove the security of BDIVE against several attacks by implementing it in AVISPA. To assess its scalability and energy efficiency, we implement BDIVE using Omnetpp with its Castalia simulator. The comparison of BDIVE with currently existing authentication protocols, shows that it reduces the energy consumption up to 70% and the computational cost up to 68%, while providing resistance to previously unconsidered attack vectors.

Android is currently the most widespread operating system (OS) worldwide, but also the most prone to attacks. Despite the challenges faced by Industry and Academia to improve the Android OS security, it still has several vulnerabilities. Among those, the severity of the Next-Intent Vulnerability (NIV) can be immediately grasped. Android apps are made of components, which by default are private and cannot be targeted by other apps on the same phone. However, NIV allows any app to access the private components of a different app, eventually generating a crash or stealing sensitive data. NIV occurs when there is a chain of calls among different components based on the Intent messaging model and there is no control over the reliability of the first component triggering the call. NIV was first detected in 2013, but it is still an open issue. In this paper, we present Next-Intent Vulnerability Detector (NI VD), a novel approach to detect NIV in Android apps by relying on type systems. NI VD applies the inference rules of its type system to the app execution paths containing a sequence of calls to three NIV-related Android APIs. Compared to the state-of-the-art, NI VD is faster and more efficient, without losing precision in detecting NIV. Finally, through NI VD Google Photos was found to be vulnerable, and we disclosed the finding on the Google official bug report website (issue number 124342801).

WebView objects allow Android apps to render web content in the app context. More specifically, in Android hybrid apps (i.e., those having both Android code and web code) the web content can interact with the underlying Android framework through Java interfaces and WebViewClient objects. Thus, while rendering web content a hybrid app can execute malicious Javascript code that can access the sensitive data on the device, bypassing the sandbox model usually adopted by standalone browsers. Researchers already analyzed the security issues of WebView objects, by focusing on Javascript interfaces. However, we believe that there are other aspects related to the rendering of web content in Android apps, such as WebViewClient objects, that could lead to security issues. In this paper, we introduce three new types of vulnerabilities related to WebView, that expose new attack surfaces concerning the most well-known vulnerability related to JavaScript interfaces. To detect these new types of vulnerabilities, we designed WebVSec, a static analysis system that relies on a set of custom inference rules, heuristically formalized. By designing WebVSec to detect also the vulnerability already described in the state-of-art, we were able to compare WebVSec with BabelView on a set of 2000 applications. BabelView was found not able to detect our new three types of vulnerabilities and also less precise and efficient in detecting the already known vulnerability. In particular, over the 2000 analyzed apps, WebVSec and BabelView identified 48 and 18 vulnerable apps, respectively. Among those, WebVSec found 20 apps having a specific type of vulnerabilities and 36 apps having another type of vulnerabilities, while BabelView found 11 and 0 apps, respectively. In terms of efficiency, WebVSec took 27.16 hours to analyze the whole set of 2000 applications against the 63.64 hours required by BabelView.