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Vulnerability Detection (VD) using machine learning faces a significant challenge: the vast diversity of vulnerability types. Each Common Weakness Enumeration (CWE) represents a unique category of vulnerabilities with distinct characteristics, code semantics, and patterns. Treating all vulnerabilities as a single label with a binary classification approach may oversimplify the problem, as it fails to capture the nuances and context-specific to each CWE. As a result, a single binary classifier might merely rely on superficial text patterns rather than understanding the intricacies of each vulnerability type. Recent reports showed that even the state-of-the-art Large Language Model (LLM) with hundreds of billions of parameters struggles to generalize well to detect vulnerabilities. Our work investigates a different approach that leverages CWE-specific classifiers to address the heterogeneity of vulnerability types. We hypothesize that training separate classifiers for each CWE will enable the models to capture the unique characteristics and code semantics associated with each vulnerability category. To confirm this, we conduct an ablation study by training individual classifiers for each CWE and evaluating their performance independently. Our results demonstrate that CWE-specific classifiers outperform a single binary classifier trained on all vulnerabilities. Building upon this, we explore strategies to combine them into a unified vulnerability detection system using a multiclass approach. Even if the lack of large and high-quality datasets for vulnerability detection is still a major obstacle, our results show that multiclass detection can be a better path toward practical vulnerability detection in the future. All our models and code to produce our results are open-sourced.

The $5^{th}$ generation of mobile networks introduces a new Network Function (NF) that was not present in previous generations, namely the Network Data Analytics Function (NWDAF). Its primary objective is to provide advanced analytics services to various entities within the network and also towards external application services in the 5G ecosystem. One of the key use cases of NWDAF is mobility trajectory prediction, which aims to accurately support efficient mobility management of User Equipment (UE) in the network by allocating ``just in time'' necessary network resources. In this paper, we show that there are potential mobility attacks that can compromise the accuracy of these predictions. In a semi-realistic scenario with 10,000 subscribers, we demonstrate that an adversary equipped with the ability to hijack cellular mobile devices and clone them can significantly reduce the prediction accuracy from 75\% to 40\% using just 100 adversarial UEs. While a defense mechanism largely depends on the attack and the mobility types in a particular area, we prove that a basic KMeans clustering is effective in distinguishing legitimate and adversarial UEs., Comment: This is the preprint version of a paper which appears in 22th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom 2023)

We determine the impact of anharmonic thermal vibrations on the fundamental band gap of CsPbBr$_3$, a prototypical model system for the broader class of halide perovskite semiconductors. Through first-principles molecular dynamics and stochastic calculations, we find that anharmonic fluctuations are a key effect in the electronic structure of these materials. We present experimental and theoretical evidence that important characteristics, such as a mildly changing band-gap value across a temperature range that includes phase-transitions, cannot be explained by harmonic phonons thermally perturbing an average crystal structure and symmetry. Instead, the thermal characteristics of the electronic structure are microscopically connected to anharmonic vibrational contributions to the band gap that reach a fairly large magnitude of 450 meV at 425 K.

We show that formamidinium lead bromide is unique among the halide perovskite crystals because its inorganic sub-lattice exhibits intrinsic local static disorder that co-exists with a well-defined average crystal structure. Our study combines THz-range Raman-scattering with single-crystal X-ray diffraction and first-principles calculations to probe the inorganic sub-lattice dynamics evolution with temperature in the range of 10-300 K. The temperature evolution of the Raman spectra shows that low-temperature, local static disorder strongly affects the crystal's structural dynamics and phase transitions at higher temperatures., Comment: Total 16 pages, 8 figures (including SI). Submitted to The Journal of Physical Chemistry Letters

Strong deviations in the finite temperature atomic structure of halide perovskites from their average geometry can have profound impacts on optoelectronic and other device-relevant properties. Detailed mechanistic understandings of these structural fluctuations and their consequences remain, however, limited by the experimental and theoretical challenges involved in characterizing strongly anharmonic vibrational characteristics and their impact on other properties. We overcome some of these challenges by a theoretical characterization of the vibrational interactions that occur among the atoms in the prototypical cubic CsPbBr$_3$. Our investigation based on first-principles molecular dynamics calculations finds that the motions of neighboring Cs-Br atoms interlock, which appears as the most likely Cs-Br distance being significantly shorter than what is inferred from an ideal cubic structure. This form of dynamic Cs-Br coupling coincides with very shallow dynamic potential wells for Br motions that occur across a locally and dynamically disordered energy landscape. We reveal an interesting dynamic coupling mechanism among the atoms within the nominal unit cell of cubic CsPbBr$_3$ and quantify the important local structural fluctuations on an atomic scale.

Despite their puzzling vibrational characteristics that include strong signatures of anharmonicity and thermal disorder already around room temperature, halide perovskites exhibit favorable optoelectronic properties for applications in photovoltaics and beyond. Whether these vibrational properties are advantageous or detrimental to their optoelectronic properties remains, however, an important open question. Here, this issue is addressed by investigation of the {finite-temperature optoelectronic properties} in the prototypical cubic CsPbBr$_3$, using first-principles molecular dynamics based on density-functional theory. It is shown that the dynamic flexibility associated with halide perovskites enables the so-called transversality, which manifests as a preference for large halide displacements perpendicular to the Pb-Br-Pb bonding axis. We find that transversality is concurrent with vibrational anharmonicity and leads to a rapid rise in the joint density of states, which is favorable for photovoltaics since this implies sharp optical absorption profiles. These findings are contrasted to the case of PbTe, a material that shares several key properties with CsPbBr$_3$ but cannot exhibit any transversality and, hence, is found to exhibit much wider band-edge distributions. We conclude that the dynamic structural flexibility in halide perovskites and their unusual vibrational characteristics might not just be a mere coincidence, but play active roles in establishing their favorable optoelectronic properties.

The central role of the certificate authority (CA) in traditional public key infrastructure (PKI) makes it fragile and prone to compromises and operational failures. Maintaining CAs and revocation lists is demanding especially in loosely-connected and large systems. Log-based PKIs have been proposed as a remedy but they do not solve the problem effectively. We provide a general model and a solution for decentralized and dynamic PKI based on a blockchain and web of trust model where the traditional CA and digital certificates are removed and instead, everything is registered on the blockchain. Registration, revocation, and update of public keys are based on a consensus mechanism between a certain number of entities that are already part of the system. Any node which is part of the system can be an auditor and initiate the revocation procedure once it finds out malicious activities. Revocation lists are no longer required as any node can efficiently verify the public keys through witnesses., Comment: 19 pages, 5 figures

Along with the rapid development of cloud computing technology, containerization technology has drawn much attention from both industry and academia. In this paper, we perform a comparative measurement analysis of Docker-sec, which is a Linux Security Module proposed in 2018, and a new AppArmor profile generator called Lic-Sec, which combines Docker-sec with a modified version of LiCShield, which is also a Linux Security Module proposed in 2015. Docker-sec and LiCShield can be used to enhance Docker container security based on mandatory access control and allows protection of the container without manually configurations. Lic-Sec brings together their strengths and provides stronger protection. We evaluate the effectiveness and performance of Docker-sec and Lic-Sec by testing them with real-world attacks. We generate an exploit database with 42 exploits effective on Docker containers selected from the latest 400 exploits on Exploit-db. We launch these exploits on containers spawned with Docker-sec and Lic-Sec separately. Our evaluations show that for demanding images, Lic-Sec gives protection for all privilege escalation attacks for which Docker-sec failed to give protection.

Basic understanding of the driving forces of ion conduction in solids is critical to the development of new solid-state ion conductors. Physical understanding of ion conduction is limited due to strong deviations from harmonic vibrational dynamics in these systems that are difficult to characterize experimentally and theoretically. We overcome this challenge in superionic AgI by combining THz-frequency Raman polarization-orientation measurements and ab-initio molecular dynamics computations. Our findings demonstrate clear signatures of strong coupling between the mobile ions and host lattice that are of importance to the diffusion process. We first derive a dynamic structural model from the Raman measurements that captures the simultaneous crystal-like and fluid-like properties of this fast-ion conductor. Then we show and discuss the importance of anharmonic relaxational motion that arises from the iodine host lattice by demonstrating its strong impact on ion conduction in superionic AgI.

Halide perovskites are semiconductors that exhibit sharp optical absorption edges and small Urbach energies allowing for efficient collection of sunlight in thin-film photovoltaic devices. However, halide perovskites also exhibit large nuclear anharmonic effects and disorder, which is unusual for efficient optoelectronic materials and difficult to rationalize in view of the small Urbach energies that indicate a low amount of disorder. To address this important issue, the disorder potential induced for electronic states by the nuclear dynamics in various paradigmatic halide perovskites is studied with molecular dynamics and density functional theory. We find that the disorder potential is dynamically shortened due to the nuclear motions in the perovskite, such that it is short-range correlated, which is shown to lead to favorable distributions of band edge energies. This dynamic mechanism allows for sharp optical absorption edges and small Urbach energies, which are highly desired properties of any solar absorber material.

We investigate the impact of various levels of approximation in density functional theory calculations for the structural and binding properties of the prototypical halide perovskite MAPbI$_3$. Specifically, we test how the inclusion of different correction schemes for including dispersive interactions, and how in addition using hybrid density functional theory, affects the results for pertinent structural observables by means of comparison to experimental data. In particular, the impact of finite temperature on the lattice constants and bulk modulus, and the role of dispersive interactions in calculating them, is examined by using molecular dynamics based on density functional theory. Our findings confirm previous theoretical work showing that including dispersive corrections is crucial for accurate calculation of structural and binding properties of MAPbI$_3$. They furthermore highlight that using a computationally much more expensive hybrid density functional has only minor consequences for these observables. This allows for suggesting the use of semilocal density functional theory, augmented by pairwise dispersive corrections, as a reasonable choice for structurally more complicated calculations of halide perovskites. Using this method, we perform molecular dynamics calculations and discuss the dynamic effect of molecular rotation on the structure of and binding in MAPbI$_3$, which allowed for rationalizing microscopically the simultaneous occurrence of cubic octahedral symmetry and MA disorder.

The evolution of Software-Defined Networking (SDN) has so far been predominantly geared towards defining and refining the abstractions on the forwarding and control planes. However, despite a maturing south-bound interface and a range of proposed network operating systems, the network management application layer is yet to be specified and standardized. It has currently poorly defined access control mechanisms that could be exposed to network applications. Available mechanisms allow only rudimentary control and lack procedures to partition resource access across multiple dimensions. We address this by extending the SDN north-bound interface to provide control over shared resources to key stakeholders of network infrastructure: network providers, operators and application developers. We introduce a taxonomy of SDN access models, describe a comprehensive design for SDN access control and implement the proposed solution as an extension of the ONOS network controller intent framework.

Software-Defined Networking (SDN) is a novel architectural model for cloud network infrastructure, improving resource utilization, scalability and administration. SDN deployments increasingly rely on virtual switches executing on commodity operating systems with large code bases, which are prime targets for adversaries attacking the net- work infrastructure. We describe and implement TruSDN, a framework for bootstrapping trust in SDN infrastructure using Intel Software Guard Extensions (SGX), allowing to securely deploy SDN components and protect communication between network endpoints. We introduce ephemeral flow-specific pre-shared keys and propose a novel defense against cuckoo attacks on SGX enclaves. TruSDN is secure under a powerful adversary model, with a minor performance overhead., Comment: SecureComm 2016 12th EAI International Conference on Security and Privacy in Communication Networks October 10-12, 2016 Guangzhou, People's Republic of China